Compare commits

...

432 Commits

Author SHA1 Message Date
8dd8741100 Tweak options, dependencies, documentation 2013-08-03 21:42:49 -04:00
8e6341ae5d Verify that data timestamps are monotonic 2013-08-03 21:32:05 -04:00
422b1e2df2 More fsck improvements. Fixed two problems on sharon so far. 2013-08-03 17:50:46 -04:00
0f745b3047 More fsck tools, including fixes 2013-08-03 16:43:20 -04:00
71cd7ed9b7 Add nilmdb-fsck tool to check database consistency 2013-08-03 14:23:14 -04:00
a79d6104d5 Documentation fixups 2013-08-01 16:24:51 -04:00
8e8ec59e30 Support "nilmtool cmd --version" 2013-08-01 15:14:34 -04:00
b89b945a0f Better responses to invalid HTTP times 2013-07-31 13:37:04 -04:00
bd7bdb2eb8 Add --optimize option to nilmtool intervals 2013-07-30 15:31:51 -04:00
840cd2fd13 Remove stray print 2013-07-30 15:21:09 -04:00
bbd59c8b50 Add nilmdb.utils.interval.intersection by generalizing set_difference 2013-07-30 14:48:19 -04:00
405c110fd7 Doc updates 2013-07-29 15:36:43 -04:00
274adcd856 Documentation updates 2013-07-27 19:51:09 -04:00
a1850c9c2c Misc documentation 2013-07-25 16:08:35 -04:00
6cd28b67b1 Support iterator protocol in Serializer 2013-07-24 14:52:26 -04:00
d6d215d53d Improve boolean HTTP parameter handling 2013-07-15 14:38:28 -04:00
e02143ddb2 Remove duplicated test 2013-07-14 15:30:53 -04:00
e275384d03 Fix WSGI docs again 2013-07-11 16:36:32 -04:00
a6a67ec15c Update WSGI docs 2013-07-10 14:16:25 -04:00
fc43107307 Fill out test coverage 2013-07-09 19:06:26 -04:00
90633413bb Add nilmdb.utils.interval.human_string function 2013-07-09 19:01:53 -04:00
c7c3aff0fb Add nilmdb.utils.interval.optimize function 2013-07-09 17:50:21 -04:00
e2347c954e Split more CherrpyPy stuff into serverutil 2013-07-02 11:44:08 -04:00
222a5c6c53 Move server decorators and other utilities to a separate file
This will help with implementing nilmrun.
2013-07-02 11:32:19 -04:00
1ca2c143e5 Fix typo 2013-06-29 12:39:00 -04:00
b5df575c79 Fix tests 2013-05-09 22:27:10 -04:00
2768a5ad15 Show FQDN rather than hostname. 2013-05-09 13:33:05 -04:00
a105543c38 Show a more helpful message at the root nilmdb path 2013-05-09 13:30:10 -04:00
309f38d0ed Merge branch '32bit' 2013-05-08 17:20:31 -04:00
9a27b6ef6a Make rocket code suitable for 32-bit architectures 2013-05-08 16:35:32 -04:00
99532cf9e0 Fix coverage 2013-05-07 23:00:44 -04:00
dfdd0e5c74 Fix line parsing in http client 2013-05-07 22:56:00 -04:00
9a2699adfc Attempt at fixing up more Unicode issues with metadata. 2013-05-07 13:44:03 -04:00
9bbb95b18b Add unicode decode/encode helpers 2013-05-07 12:56:59 -04:00
6bbed322c5 Fix unicode in completion 2013-05-07 12:49:12 -04:00
2317894355 Tweak cache sizes to account for large numbers of decimated tables 2013-05-06 11:54:57 -04:00
539c92226c Add more disk space info 2013-05-06 11:36:28 -04:00
77c766d85d Bump MAX_LAYOUT_COUNT to 1024 2013-05-02 15:27:31 -04:00
49d04db1d6 Allow start==end in stream_insert_context, if no data was provided. 2013-04-11 13:25:37 -04:00
ea838d05ae Warn against reused context managers, and fix broken tests 2013-04-11 13:25:00 -04:00
f2a48bdb2a Test binary extract; fix bugs 2013-04-11 13:24:11 -04:00
6d14e0b8aa Allow binary extract 2013-04-11 11:30:41 -04:00
b31b9327b9 Add tool to fix oversize files (the bug fixed by b98ff13) 2013-04-11 11:02:53 -04:00
b98ff1331a Fix bug where too much data was getting written to each file.
We were still calculating the maximum number of rows correctly,
so the extra data was really extra and would get re-written to the
beginning of the subsequent file.

The only case in which this would lead to database issues is if the
very last file was lengthened incorrectly, and the "nrows" calculation
would therefore be wrong when the database was reopened.  Still, even
in that case, it should just leave a small gap in the data, not cause
any errors.
2013-04-10 23:22:03 -04:00
00e6ba1124 Avoid ENOENT in nilmdb.utils.diskusage.du
ENOENT might show up if we're actively deleting files in the nilmdb
thread while trying to read available space from e.g. the server
thread.
2013-04-10 22:25:22 -04:00
01029230c9 Tweaks to sorting 2013-04-10 19:59:38 -04:00
ecc4e5ef9d Improve test coverage 2013-04-10 19:08:05 -04:00
23f31c472b Split sort_streams_nicely into separate file 2013-04-10 19:07:58 -04:00
a1e2746360 Fix bug in nilmdb.stream_remove with max_removals 2013-04-10 18:37:21 -04:00
1c40d59a52 server: use a generator in /stream/remove
Instead of returning a single number at the end of N nilmdb calls, we
now use a generator that returns one line of text every time there's a
new count of rows removed.  This ensures that the connection will stay
alive for very long removals.
2013-04-10 18:11:58 -04:00
bfb09a189f Fix coverage 2013-04-10 16:33:08 -04:00
416a499866 Support wildcards for destroy 2013-04-10 16:23:07 -04:00
637d193807 Fix unicode processing of command line arguments 2013-04-10 16:22:51 -04:00
b7fa5745ce nilmtool list: allow multiple paths to be supplied 2013-04-10 15:34:33 -04:00
0104c8edd9 nilmtool remove: allow wildcards and multiple paths 2013-04-10 15:27:46 -04:00
cf3b8e787d Add test for wrong number of fields in numpy insert 2013-04-10 15:06:50 -04:00
83d022016c nilmtool list: add new --layout option to show layouts 2013-04-10 14:58:44 -04:00
43b740ecaa nilmtool list: remove old -p parameter 2013-04-10 14:48:23 -04:00
4ce059b920 Give a slightly more clear error on bad array sizes 2013-04-09 19:56:58 -04:00
99a4228285 Set up default SIGPIPE handler
This lets you do something like "nilmtool extract | head" without
triggering backtraces.
2013-04-09 18:25:09 -04:00
230ec72609 Fix timestamp display issues with --annotate 2013-04-09 18:19:32 -04:00
d36ece3767 Fix up dependencies 2013-04-08 18:53:13 -04:00
231963538e Add some info about binary interface to design docs 2013-04-08 18:53:13 -04:00
b4d6aad6de Merge branch 'binary' 2013-04-08 18:52:52 -04:00
e95142eabf Huge update to support inserting in client.numpyclient, with tests
This includes both client.stream_insert_numpy and
client.stream_insert_numpy_context().  The test code is based on
similar test code for client.stream_insert_context, so it should be
fairly complete.
2013-04-08 18:51:45 -04:00
d21c3470bc Client cleanups; fix tests to account for time epsilon = 1 2013-04-08 18:51:45 -04:00
7576883f49 Add basic binary support to client, and restructure a bit 2013-04-08 18:51:45 -04:00
cc211542f8 Add binary support to nilmdb.server; enforce content-type 2013-04-08 18:51:45 -04:00
8292dcf70b Clean up stream/extract content-type and add a test for it 2013-04-08 18:51:45 -04:00
b362fd37f6 Add binary option to nilmdb.stream_insert 2013-04-08 18:51:45 -04:00
41ec13ee17 Rename bulkdata.append_string to bulkdata.append_data 2013-04-08 18:51:45 -04:00
efa9aa9097 Add binary option to bulkdata.append_string 2013-04-08 18:51:45 -04:00
d9afb48f45 Make append_binary signature look like append_string 2013-04-08 18:51:44 -04:00
d1140e0f16 Timestamps are int64, not uint64 2013-04-08 18:51:44 -04:00
6091e44561 Fix fread return value check 2013-04-08 18:51:44 -04:00
e233ba790f Add append_binary to rocket 2013-04-08 18:51:44 -04:00
f0304b4c00 Merge branch 'binary' into HEAD 2013-04-07 18:08:10 -04:00
60594ca58e Numpy is required for tests now, due to nilmdb.client.numpyclient
Still allow installation without it, though.
2013-04-07 18:05:43 -04:00
c7f2df4abc Add nilmdb.client.numpyclient.NumpyClient with stream_extract_numpy
This is a subclass of nilmdb.client.client.Client that adds numpy
specific routines, which should be a lot faster.
2013-04-07 17:43:52 -04:00
5b7409f802 Add binary extract to client, server, nilmdb, bulkdata, and rocket. 2013-04-07 16:06:52 -04:00
06038062a2 Fix error in time parsing 2013-04-06 19:12:17 -04:00
ae9fe89759 Parse timestamps with '@' before any other checks 2013-04-04 14:43:18 -04:00
04def60021 Include stream path in "no such stream" errors 2013-04-02 21:06:49 -04:00
9ce0f69dff Add "--delete" option to "nilmtool metadata" tool
This is the same as "--update" with an empty string as the value.
2013-04-02 16:07:28 -04:00
90c3be91c4 Natural sort for streams in client.stream_list 2013-04-02 14:37:32 -04:00
ebccfb3531 Fix stream renaming when the new path is a parent of the old 2013-04-01 19:25:17 -04:00
e006f1d02e Change default URL to http://localhost/nilmdb/ 2013-04-01 18:04:31 -04:00
5292319802 server: consolidate time processing and checks 2013-03-30 21:16:40 -04:00
173121ca87 Switch URL to one that should definitely not resolve 2013-03-30 17:31:35 -04:00
26bab031bd Add StreamInserter.send() to trigger intermediate block send 2013-03-30 17:30:43 -04:00
b5fefffa09 Use a global cached server object for WSGI app
This is instead of caching it inside nilmdb.server.wsgi_application.
Might make things work a bit better in case the web server decides
to call wsgi_application multiple times.
2013-03-30 15:56:57 -04:00
dccb3e370a WSGI config needs to specify application group
This ensures that the same Python sub-instance handles the request,
even if it's coming in from two different virtual hosts.
2013-03-30 15:56:02 -04:00
95ca55aa7e Print out WSGI environment on DB init failure 2013-03-30 15:55:41 -04:00
e01813f29d Fix wsgi documentation 2013-03-25 13:52:32 -04:00
7f41e117a2 Fix tabs 2013-03-25 13:44:03 -04:00
dd5fc806e5 Restructure WSGI app to regenerate error on each call, if needed
This way, errors like "database already locked" can be fixed and the
page reloaded, without needing to restart Apache.
2013-03-24 21:52:11 -04:00
f8ca8d31e6 Remove Iteratorizer, as it's no longer needed 2013-03-24 21:31:03 -04:00
ed89d803f0 Remove aplotter code 2013-03-24 21:29:09 -04:00
3d24092cd2 Replace bare 'except:' with 'except: Exception'
Otherwise we might inadvertently catch SystemExit or KeyboardExit or
something we don't want to catch.
2013-03-24 21:28:01 -04:00
304bb43d85 Move lockfile out of data dir, to avoid stream tree conflicts 2013-03-24 21:23:45 -04:00
59a79a30a5 Remove lockfile when done.
This isn't necessary for correct behavior: if the database is killed,
the old flock() will go away when the file descriptor gets closed.
2013-03-24 21:20:47 -04:00
c0d450d39e Add locking mechanism to avoid multiple servers on one DB 2013-03-24 21:20:20 -04:00
6f14d609b2 Fix issue where bulkdata was accidentally closed 2013-03-24 21:16:18 -04:00
77ef87456f Improve WSGI application support, fix docs 2013-03-24 21:16:03 -04:00
32d6af935c Improve wsgi docs 2013-03-22 19:17:36 -04:00
6af3a6fc41 Add WSGI application support and documentation 2013-03-22 19:14:34 -04:00
f8a06fb3b7 Clarify default DB path in nilmdb_server.py help text 2013-03-22 15:09:37 -04:00
e790bb9e8a Fix test failure when tests are run as root 2013-03-21 14:33:02 -04:00
89be6f5931 Add option to include interval start/end markup on extract
When enabled, lines like "# interval-start 1234567890123456" and "#
interval-end 1234567890123456" will be added to the data output.  Note
that there may be an "interval-end" timestamp followed by an identical
"interval-start" timestamp, if the response at the nilmdb level was
split up into multiple chunks.

In general, assume contiguous data if previous_interval_end ==
new_interval_start.
2013-03-19 14:23:33 -04:00
4cdef3285d Destroy now requires that all data has been previously removed.
Added new flag "-R" to command line to perform an automatic removal.
This should be the last of the ways in which a single command could
block the nilmdb thread for a long time.
2013-03-18 19:39:03 -04:00
bcd82c4d59 Limit the number of rows removed per call to nilmdb.stream_remove
Server class will retry as needed, as with stream_extract and
stream_intervals.
2013-03-18 18:22:45 -04:00
caf63ab01f Fix stream_extract/stream_intervals restart around timestamp == 0. 2013-03-18 18:20:25 -04:00
2d72891162 Accept "min" and "max" as timestamps on command line 2013-03-18 18:19:24 -04:00
cda2ac3e77 Don't return a mutable interval from IntervalSet.intersection()
Instead, always take the subset, which creates a new interval.
Also adds a small optimization by moving the 'if orig' check outside the
loop.
2013-03-18 18:16:35 -04:00
57d3d60f6a Fix relative import problems 2013-03-18 16:27:27 -04:00
d6b5befe76 Don't use filenames as default arg completion 2013-03-16 17:27:58 -04:00
7429c1788d Update nilmdb.utils.time 2013-03-15 22:49:59 -04:00
0ef71c193b Remove layout.pyx, since rocket replaced it 2013-03-15 22:32:40 -04:00
4a50dd015e Merge branch 'python-intervals' 2013-03-15 21:39:11 -04:00
22274550ab Test python version of Interval too 2013-03-15 21:37:03 -04:00
4f06d6ae68 Move Interval set_difference inside nilmdb.utils for clients
Clients might need to to Interval math too, so move a simple Interval
class and start putting helpers in there.
2013-03-15 21:37:03 -04:00
c54d8041c3 Update design docs 2013-03-15 21:07:01 -04:00
52ae397d7d Bump database version to 3, reject old version 2 due to timestamp changes 2013-03-15 18:37:38 -04:00
d05b6f6348 Merge branch 'rocket-cleanup' 2013-03-15 18:08:36 -04:00
049375d30e Fill out test coverage 2013-03-15 18:08:21 -04:00
88eb0123f5 Add test for Table.__getitem__ indexing 2013-03-15 18:08:21 -04:00
a547ddbbba Change table.get_timestamp to table.__getitem__
This lets us use simple indexing to get timestamps from the table,
which allows us to use 'bisect' directly without needing a proxy class.
2013-03-15 18:08:21 -04:00
28e72fd53e Remove Table.__getitem__; used only by tests 2013-03-15 18:08:21 -04:00
f63107b334 Add rocket.extract_timestamp to speed up bisections 2013-03-15 18:08:21 -04:00
955d7aa871 Remove floating port time support from nilmdb.utils.time 2013-03-15 18:08:21 -04:00
b8d2cf1b78 Consolidate rocket._extract_handle.params with extract_string 2013-03-15 18:08:21 -04:00
7c465730de Remove rocket.extract_pyobject 2013-03-15 18:08:21 -04:00
aca130272d Remove rocket.extract_list 2013-03-15 18:08:21 -04:00
76e5e9883f Remove Table.append, rocket.append_iter 2013-03-15 18:08:20 -04:00
fb4f4519ff Clean up and simplify Table.get_*, including __getitem__ 2013-03-15 18:08:20 -04:00
30328714a7 Remove python implementation of rocket 2013-03-15 18:08:20 -04:00
759466de4a Merge branch 'timestamp-integers' 2013-03-15 18:07:51 -04:00
d3efb829b5 Try to parse timestamps as double, if int64 parse fails 2013-03-15 15:19:41 -04:00
90b96799ac Bulk of the switch to int64 microsecond timestamps, including test data. 2013-03-15 15:08:58 -04:00
56679ad770 Move more datetime_tz calls into common code 2013-03-15 15:08:58 -04:00
b5541722c2 Continue moving time-handling code into nilmdb.utils.time 2013-03-15 15:08:58 -04:00
aaea105861 Consolidate most timestamp <-> string conversions (outside of rocket) 2013-03-15 15:08:57 -04:00
e6a081d639 Consolidate timestamp constants into nilmdb.utils.time 2013-03-15 15:08:57 -04:00
1835d03412 Bump bulkdata database version to 3 2013-03-15 15:08:57 -04:00
c7a712d8d8 Partial test for rounding issues 2013-03-15 15:08:57 -04:00
20d315b4f7 Add documentation about upcoming timestamp changes 2013-03-15 15:08:57 -04:00
a44a5e3135 Merge branch 'argcomplete' 2013-03-15 15:08:42 -04:00
039b2a0557 Include nilmtool-bash-completion.sh script in .tar.gz 2013-03-15 15:08:28 -04:00
cd1dfe7dcd Add completion functions to most commandline arguments 2013-03-15 14:26:38 -04:00
fb35517dfa Add basic argument completion 2013-03-15 13:57:35 -04:00
b9f0b35bbe Stream renaming support, and comprehensive tests
Implemented in command line, client, server, nilmdb, bulkdata
2013-03-14 11:02:30 -04:00
b1b09f8cd0 Strengthen checks when creating paths, fix some bugs, and add tests 2013-03-13 17:45:47 -04:00
d467df7980 Add specific error for creating a path that already exists 2013-03-13 10:14:28 -04:00
09bc7eb48c Make StreamInserter.insert complain if data remains after send
Previously, we ignored problems when sending intermediate blocks,
since getting more data might make the next attempt succeed.
But in practice, malformed data would just build up, causing
problems.  Raise an exception if there's too much data remaining
after trying to send an intermediate block.
2013-03-12 18:45:56 -04:00
b77f07a4cd Fix reporting of parsing errors with malformed data
strtod() and friends will happily swallow newlines, so we need to skip
over spaces and look for that sort of thing manually.
2013-03-12 16:44:36 -04:00
59f0076306 Increase max layout count in rocket 2013-03-12 16:10:29 -04:00
83bc5bc775 Make rocket/bulkdata errors include column number and the bad data
The bad line is printed out on a new line, and a third line
with a ^ to indicate the position of the error.
2013-03-12 16:10:00 -04:00
6b1dfec828 In stream_list, return 0 instead of None for rows and seconds
For rows and seconds only.  Extents still give None if they don't
exist.
2013-03-11 19:37:52 -04:00
d827f41fa5 Fix Makefile omission 2013-03-11 17:42:02 -04:00
7eca587fdf Add 'nilmtool intervals' command, with --diff option
Can show the set-difference between the interval ranges in two
streams.
2013-03-11 17:07:26 -04:00
a351bc1b10 Add client, server, nilmdb support for listing interval differences 2013-03-11 17:07:08 -04:00
1d61d61a81 Add interval.set_difference function and associated tests 2013-03-11 15:40:50 -04:00
755255030b Clean up interval __and__ function; we don't need to __and__ sets 2013-03-11 15:15:43 -04:00
8e79998e95 Tune sqlite to use write-ahead-logging
Enable the following pragmas: synchronous=NORMAL, journal_mode=WAL.
This offers a significant speedup to INSERT times compared to
synchronous=FULL, and is roughly the same as synchronous=OFF
but should be a bit safer.
2013-03-11 15:13:43 -04:00
9f914598c2 Make /stream/list give some more extended info, like row count
Also changes the HTTP parameter from "extent" to "extended",
and the commandline parameter from "extent" to "ext".
2013-03-11 15:13:43 -04:00
0468b04538 Fix pyrocket to handle comments better 2013-03-11 15:13:43 -04:00
232a3876c2 Clean up imports to separate client and server more.
"import nilmdb" doesn't do much; "import nilmdb.client" or "import
nilmdb.server" is now required.
2013-03-11 15:13:42 -04:00
1c27dd72d6 Fill out client tests and fix various bugs
Fixes various corner cases and other bugs regarding lines with
comments, having data but no endpoints, etc.
2013-03-08 12:36:17 -05:00
de5e474001 Update benchmarks in design.md 2013-03-07 20:33:30 -05:00
0fc092779d Big rework of stream_insert_context and places that use it.
Things are now block-focused, rather than line-focused.  This should
give a pretty big speedup to inserting client data, especially when
inserting preformatted data.
2013-03-07 20:30:11 -05:00
7abfdfbf3e Add const qualifier to strings we get from Python 2013-03-07 16:27:07 -05:00
92724d10ba Rework 'nilmtool insert' and some client stuff to speed up inserting data
Still needs work.
2013-03-06 20:49:14 -05:00
1d7acbf916 Remove null timestamper, speed up insert --none a tiny bit 2013-03-06 20:46:51 -05:00
ea3ea487bc Merge branch 'rocket-insert'
Conflicts:
	nilmdb/server/bulkdata.py
	nilmdb/server/server.py
	nilmdb/utils/__init__.py
2013-03-06 20:46:04 -05:00
69ad8c4842 Merge branch 'rocket' 2013-03-06 20:38:02 -05:00
0047e0360a Implement Rocket.append_string() in C; misc cleanups along the way
This should more or less complete the rocket interface.
2013-03-06 15:50:00 -05:00
1ac6abdad0 Fix rocket.ParseError exception handling
Before, a tuple was crammed into args[0].  Now, the three arguments are
args[0:2].
2013-03-05 22:05:17 -05:00
65f09f793c When re-raising exceptions in the server, preserve original tracebacks 2013-03-05 21:48:40 -05:00
84e21ff467 Move ASCII data parsing from the server to the rocket interface.
The server buffers the string and passes it to nilmdb.  Nilmdb passes
the string to bulkdata.  Bulkdata uses the rocket interface to parse
it in chunks, as necessary.  Everything gets passed back up and
everyone is happy.

Currently, only pyrocket implements append_string.
2013-03-05 17:51:17 -05:00
11b228f77a Convert times to microsecond precision strings more consistently.
Use a new helper, nilmdb.utils.time.float_to_time_string().
This will help if we ever want to change representation (like using
uint64 microseconds since epoch, which saves us from having to
waste bits on the floating-point exponent)
2013-03-05 17:07:39 -05:00
7860a6aefb Make helper for removing or truncating a file; use it 2013-03-05 15:27:12 -05:00
454e561d69 Verify that metadata values are numbers or strings 2013-03-05 13:22:17 -05:00
fe91ff59a3 Better handling of JSON requests 2013-03-05 12:38:08 -05:00
64c24a00d6 Add --traceback argument to nilmdb-server script 2013-03-05 12:20:07 -05:00
58c0ae72f6 Support application/json POST bodies as well as x-www-form-urlencoded 2013-03-05 11:54:29 -05:00
c5f079f61f When removing data from files, try to punch a hole.
Requires fallocate(2) support with FALLOC_FL_PUNCH_HOLE, as
well as a filesystem that supports it (in Linux 3.7,
tmpfs, btrfs, xfs, or ext4)
2013-03-04 20:31:14 -05:00
16f23f4a91 Fill out pyrocket.py to fit new interfaces; fix small bugs 2013-03-04 17:01:53 -05:00
b0f12d55dd Fully replace bulkdata.File with rocket.Rocket 2013-03-04 16:43:26 -05:00
8a648c1b97 Move towards replacing bulkdata.File with rocket.Rocket
There isn't much left in File, so let's move as much as possible
over to C.
2013-03-04 16:28:40 -05:00
2d45466f66 Print version at server startup 2013-03-04 15:43:45 -05:00
c6a0e6e96f More complete CORS handling, including preflight requests (hopefully) 2013-03-04 15:40:35 -05:00
79755dc624 Fix Allow: header by switching to cherrypy's built in tools.allow().
Replaces custom tools.allow_methods which didn't return the Allow: header.
2013-03-04 14:08:37 -05:00
f260f2c83d Remove unnecessary layout argument to nilmdb.stream_extract 2013-03-04 11:09:54 -05:00
14402005bf Remove extraneous flush 2013-03-03 21:52:45 -05:00
0d372fb878 Modify old formatter to match rocket's formatting style 2013-03-03 21:50:29 -05:00
5eac924118 Ignore built modules 2013-03-03 21:44:08 -05:00
0b75da7a8f Normalize the floating point formats to %.6e and %.16e
This is mostly a matter of taste, but it matches more closely with the
old way that prep did it, and it's more consistent.  It should roughly
match the available precision of floats and doubles.
2013-03-03 21:43:04 -05:00
2dfc94b566 Remove old code 2013-03-03 21:40:48 -05:00
e318888a06 Finish Rocket.extract_string; clean up code for other functions too
This is maybe 2.5-3 times faster than the list-based code, which
still isn't amazing, but is decent.
2013-03-03 21:25:00 -05:00
7c95934cc2 Add rocket.extract_list; still not as complete as pyrocket 2013-03-03 19:04:26 -05:00
96df9d8323 Starting the C version of rocket
Currently, only append_list is written (and hardly tested)
2013-03-03 16:54:11 -05:00
31e2c7c8b4 Add some notes about rocket interface to design.md 2013-03-03 14:43:16 -05:00
2a725ee13f Add version 1 database format backwards compatibility 2013-03-03 14:37:58 -05:00
eb8037ee3c Add a description for the rocket interface 2013-03-03 14:13:26 -05:00
fadb84d703 Move ascii formatting into nilmdb thread via rocket interface 2013-03-03 14:12:01 -05:00
9d0d2415be Test bulkdata a little more carefully 2013-03-03 14:00:00 -05:00
130dae0734 Add extract_string to pyrocket 2013-03-03 13:59:47 -05:00
402234dfc3 Better layout handling in pyrocket 2013-03-03 13:37:02 -05:00
4406d51a98 First pass at Python implementation of rocket 2013-03-03 13:37:02 -05:00
9b6de6ecb7 Replace old layout strings everywhere 2013-03-03 13:37:02 -05:00
c512631184 bulkdata: Build up rows and write to disk all at once 2013-03-03 12:03:44 -05:00
19d27c31bc Fix streaming requests like stream_extract 2013-03-03 11:37:47 -05:00
28310fe886 Add test for extents 2013-03-02 15:19:25 -05:00
1ccc2bce7e Add commandline support for listing extents 2013-03-02 15:19:19 -05:00
00237e30b2 Add "extent" option to stream_list in client, server, and nilmdb 2013-03-02 15:18:54 -05:00
521ff88f7c Support 'nilmtool help command' just like 'nilmtool command --help' 2013-03-02 13:56:03 -05:00
64897a1dd1 Change port from 12380 -> 32180 when running tests
This is so tests can be run without interfering with a normal server.
2013-03-02 13:19:44 -05:00
41ce8480bb cmdline: Support NILMDB_URL environment variable for default URL 2013-03-02 13:18:33 -05:00
204a6ecb15 Optimize bulkdata.append() by postponing flushes & mmap resize
Rather than flushing and resizing after each row is written to the
file, have the file object iterate by itself and do all of the
writes.  Only flush and resize the mmap after finishing.  This should
be pretty safe to do, especially since nothing is concurrent at the
moment.
2013-03-01 16:30:49 -05:00
5db3b186a4 Make test_mustclose more complete 2013-03-01 16:30:22 -05:00
fe640cf421 Remove must_close verification wrappers on bulkdata
At this point we know that the close() behavior is correct, so it's
not worth slowing everything down for these checks.
2013-03-01 16:11:44 -05:00
ca67c79fe4 Improve test_layout_speed 2013-03-01 16:04:10 -05:00
8917bcd4bf Fix test case failures due to increased client chunk size 2013-03-01 16:04:00 -05:00
a75ec98673 Slight speed improvements in layout.pyx 2013-03-01 16:03:38 -05:00
e476338d61 Remove outdated numpy dependency 2013-03-01 16:03:19 -05:00
d752b882f2 Bump up block sizes in client
This will help amortize the sqlite synchronization costs.
2013-02-28 21:11:57 -05:00
ade27773e6 Add --nosync option to nilmdb-server script 2013-02-28 20:45:08 -05:00
0c1a1d2388 Fix nilmdb-server script 2013-02-28 18:53:06 -05:00
e3f335dfe5 Move time parsing from cmdline into nilmdb.utils.time 2013-02-28 17:09:26 -05:00
7a191c0ebb Fix versioneer to update versions on install 2013-02-28 14:50:53 -05:00
55bf11e393 Fix error when pyximport is too old 2013-02-26 22:21:23 -05:00
e90dcd10f3 Update README and setup.py with python-requests dependency 2013-02-26 22:00:42 -05:00
7d44f4eaa0 Cleanup Makefile; make tests run through setup.py when outside emacs 2013-02-26 22:00:42 -05:00
f541432d44 Merge branch 'requests' 2013-02-26 21:59:15 -05:00
aa4e32f78a Merge branch 'curl-multi' 2013-02-26 21:59:03 -05:00
2bc1416c00 Merge branch 'fixups' 2013-02-26 21:58:55 -05:00
68bbbf757d Remove nilmdb.utils.urllib
python-requests seems to handle UTF-8 just fine.
2013-02-26 19:46:22 -05:00
3df96fdfdd Reorder code 2013-02-26 19:41:55 -05:00
740ab76eaf Re-add persistent connection test for Requests based httpclient 2013-02-26 19:41:27 -05:00
ce13a47fea Save full response object for tests 2013-02-26 17:45:41 -05:00
50a4a60786 Replace pyCurl with Requests
Only tested with v1.1.0.  It's not clear how well older versions will
work.
2013-02-26 17:45:40 -05:00
14afa02db6 Temporarily remove curl-specific keepalive tests 2013-02-26 17:45:40 -05:00
cc990d6ce4 Test persistent connections 2013-02-26 13:41:40 -05:00
0f5162e0c0 Always use the curl multi interface
.. even for non-generator requests
2013-02-26 13:39:33 -05:00
b26cd52f8c Work around curl multi bug 2013-02-26 13:38:42 -05:00
236d925a1d Make sure we use POST when requested, even if the body is empty 2013-02-25 21:05:01 -05:00
a4a4bc61ba Switch to using pycurl.Multi instead of Iteratorizer 2013-02-25 21:05:01 -05:00
3d82888580 Enforce method types, and require POST for actions that change things.
This is a pretty big change that will render existing clients unable
to modify the database, but it's important that we use POST or PUT
instead of GET for anything that may change state, in case this
is ever put behind a cache.
2013-02-25 21:05:01 -05:00
749b878904 Add an explicit lock to httpclient's public methods
This is to prevent possible reentrancy problems.
2013-02-25 18:06:00 -05:00
f396e3934c Remove cherrypy version check
Dependencies should be handled by installation, not at runtime.
2013-02-25 16:50:19 -05:00
dd7594b5fa Fix issue where PUT responses were being dropped
PUTs generate a "HTTP/1.1 100 Continue" response before the
"HTTP/1.1 200 OK" response, and so we were mistakenly picking up
the 100 status code and not returning any data.  Improve the
header callback to correctly process any number of status codes.
2013-02-23 17:51:59 -05:00
4ac1beee6d layout: allow zero and negative timestamps in parser 2013-02-23 16:58:49 -05:00
8c0ce736d8 Disable use of signals in Curl
Various places suggest that this is needed for better thread-safety,
and the only drawback is that some systems cannot timeout properly on
DNS lookups.
2013-02-23 16:15:28 -05:00
8858c9426f Fix error message text in nilmdb.server.Server 2013-02-23 16:13:47 -05:00
9123ccb583 Merge branch 'decorator-work' 2013-02-23 14:38:36 -05:00
5dce851bef Merge branch 'client-insert-context' 2013-02-23 14:37:59 -05:00
5b0441de6b Give serializer and iteratorizer threads names 2013-02-23 14:28:37 -05:00
317c53ab6f Improve serializer_proxy and verify_thread_proxy
These functions can now take an object or a type (class).

If given an object, they will wrap subsequent calls to that object.
If given a type, they will return an object that can be instantiated
to create a new object, and all calls including __init__ will be
covered by the serialization or thread verification.
2013-02-23 14:28:37 -05:00
7db4411462 Cleanup nilmdb.utils.must_close a bit 2013-02-23 11:28:03 -05:00
422317850e Replace threadsafety class decorator version, add explicit proxy version
Like the serializer changes, the class decorator was too fragile.
2013-02-23 11:25:40 -05:00
965537d8cb Implement verify_thread_safety to check for unsafe access patterns
Occasional segfaults may be the result of performing thread-unsafe
operations.  This class decorator verifies that all of its methods
are called in a thread-safe manner.

It can separately warn about:
- two threads calling methods in a function (the kind of thing sqlite
  doesn't like)
- recursion
- concurrency (two different threads functions at the same time)
2013-02-23 11:25:02 -05:00
0dcdec5949 Turn on sqlite thread safety checks -- serializer should fully protect it 2013-02-23 11:25:01 -05:00
7fce305a1d Make server check that the db object has been wrapped in a serializer
It's only the server that calls it in multiple threads.
2013-02-23 11:25:01 -05:00
dfbbe23512 Switch to explicitly wrapping nilmdb objects in a serializer_proxy
This is quite a bit simpler than the class decorator method, so it
may be more reliable.
2013-02-23 11:23:54 -05:00
7761a91242 Remove class decorator version of the serializer; it's too fragile 2013-02-23 11:23:54 -05:00
9b06e46bf1 Add back a proxy version of the Serializer, which is much simpler. 2013-02-23 11:23:54 -05:00
171e6f1871 Replace "serializer" function with a "serialized" decorator
This decorator makes a class always be serialized, including its
instantiation, in a separate thread.  This is an improvement over
the old Serializer() object wrapper, which didn't put the
instantiation into the new thread.
2013-02-23 11:23:54 -05:00
1431e41d16 Allow inserting empty intervals in the database, and add tests for it.
Previously, we could get empty intervals anyway by having a non-empty
interval and removing a smaller interval around each piece of data.
Turns out that empty intervals are OK and needed in some situations,
so explicitly allow and test for it.
2013-02-21 14:07:35 -05:00
a49c655816 Strictly enforce (start < end) for all intervals.
Previously, we allowed start == end, but this doesn't make sense with
half-open intervals.
2013-02-21 14:06:40 -05:00
30e3ffc0e9 Fix check for interval ends to be None, so that zero doesn't confuse it 2013-02-21 12:42:33 -05:00
db7211c3a9 Have server verify that start <= end before creating intervals
Also rename _fill_in_limits to _check_user_times
2013-02-21 12:38:51 -05:00
c6d57cf5c3 Fix errors with calculating limits when start==end==None
This also has the effect of now handling negative timestamps
correctly.
2013-02-19 19:27:06 -05:00
ca5253ddee Fix and test stream_count 2013-02-19 18:26:44 -05:00
e19da84b2e server: always return None instead of sometimes returning "ok"
Previously some functions returned the string "ok".
2013-02-19 18:26:44 -05:00
3e8e3542fd Test for detecting nested HTTP requests 2013-02-19 18:26:44 -05:00
2f7365412d client: detect and give a more clear error when HTTP requests are nested 2013-02-19 17:20:07 -05:00
bba9ad131e Add test for client.stream_insert_context 2013-02-19 17:19:45 -05:00
ee24380d1f Replace duplicated URL in tests with a variable 2013-02-19 15:27:51 -05:00
bfcd91acf8 client tests: renumber 2013-02-19 15:25:34 -05:00
d97291d4d3 client: Use .stream_insert_block from within .stream_insert_context
Avoids duplicating code.
2013-02-19 15:25:01 -05:00
a61fbbcf45 Big rework of client stream_insert_context
Now supports these operations:
  ctx.insert_line()
  ctx.insert_iter()
  ctx.finalize() (end the current contiguous interval, so a new one
                  can be started with a gap)
  ctx.update_end() (update ending timestamp before finalizing interval)
  ctx.update_start() (update starting timestamp for new interval)
2013-02-18 18:06:03 -05:00
5adc8fd0a7 Remove nilmdb.utils.misc.pairwise, as it's no longer used. 2013-02-18 18:06:03 -05:00
251a486c28 client.py: Significant speedup in stream_insert_context
block_data += "string" is fast with local variables, but slow with
variables inside some namespace.  Instead, build a list of strings and
join them once at the end.  This fixes the slowdown that resulted from
the stream_insert_context cleanup.
2013-02-18 18:06:03 -05:00
1edb96a0bd Add client.stream_insert_context, convert everything to use it. Slow.
Not sure why this is so painfully slow.  Need more testing;
might have to scratch the idea.
2013-02-18 18:06:03 -05:00
52e674a192 Fix warning in mustclose decorator 2013-02-18 18:05:45 -05:00
e241c13bf1 Remove must_close decorator from client
It still should be closed, but warning each time was mostly for
debugging and it's kind of annoying when writing one-off programs
where it's OK to just let things get torn down as they're completed.
Not closing is not fatal in terms of data integrity etc.
2013-02-18 18:02:05 -05:00
b53ff31212 client: Add must_close() decorator to nilmdb.Client, and fix tests
Test suite wasn't closing connections correctly.
2013-02-16 18:55:23 -05:00
2045e89f24 client: Add context manager functionality, test closing 2013-02-16 18:55:20 -05:00
841b2dab5c server: Replace /dbpath and /dbsize with a more generic /dbinfo
Update tests accordingly.  This isn't backwards compatible, but
existing clients don't rely on it.
2013-02-14 16:57:33 -05:00
d634f7d3cf bulkdata: Use file writes instead of writing to the mmap.
Extending and then writing to the mmap file has a problem: if the disk
fills up, the mapping becomes invalid, and the Python interpreter will
get a SIGBUS, killing it.  It's difficult to catch this gracefully;
there's no way to do that with existing modules.  Instead, switch to
only using mmap when reading, and normal file writes when writing.
Since we only ever append, it should have similar performance.
2013-02-13 20:30:39 -05:00
1593e181a3 Switch to versioneer-provided versions everywhere 2013-02-05 19:07:38 -05:00
8e781506de Incorporate versioneer for versioning 2013-02-05 18:49:07 -05:00
f6a2c7620a Restructure cherrypy application more correctly
Specifically, switch from using global configuration and several apps,
to using application-specific configuration with a single app.  This
should hopefully make it easier to plug this into another
WSGI-compliant server someday, and also silences some startup warnings
about missing application configs.
2013-02-04 22:38:49 -05:00
6c30e5ab2f Add gitclean target to Makefile 2013-02-04 22:15:12 -05:00
810eac4e61 Flesh out the list of dependencies in setup.py 2013-02-04 22:14:09 -05:00
d9bb3ab7ab Fix iteratorizer coverage issue with thread timing 2013-02-04 22:14:01 -05:00
21d0e90bd9 Rework Cython and external module support.
Now we build Cython modules only if cython >= 0.16 is present.
Tarballs made by "make sdist" include the Cython-generated *.c files,
and so Cython isn't required on the end user machine at all.
2013-02-04 22:12:52 -05:00
f071d749ce Generate a MANIFEST.in from setup.py; more setup.py and Makefile updates 2013-02-04 18:14:44 -05:00
d95c354595 Print a warning in setup.py if basic dependencies aren't present 2013-02-01 17:44:54 -05:00
9bcd8183f6 Add cython dependency 2013-02-01 17:44:27 -05:00
5c531d8273 Convert runserver.py into a generated nilmdb-server script 2013-02-01 17:43:41 -05:00
3fe3e2ca95 Move nilmtool into a dedicated nilmdb.scripts module 2013-02-01 17:42:09 -05:00
f01e781469 Convert nilmtool.py into a setuptools-generated script
At install time, the script "/usr/bin/nilmtool" will be created.
2013-02-01 16:25:12 -05:00
e6180a5a81 Remove all relative imports 2013-02-01 16:02:01 -05:00
a9d31b46ed More files in clean target 2013-02-01 15:48:55 -05:00
b01f23ed99 Move runtests.py script into test directory 2013-02-01 15:47:47 -05:00
842bf21411 Include the full server response if we can't parse errors out of it.
This makes things easier to debug if there's an error in
e.g. json_error_handler(), or if we're trying to poke a server that's
not even ours.
2013-02-01 15:47:47 -05:00
750d9e3c38 Clean up some pylint warnings and potential errors 2013-02-01 15:29:24 -05:00
3b90318f83 Merge remote-tracking branch 'origin/packaging' 2013-01-31 21:54:41 -05:00
1fb37604d3 Rearrange documentation, clean up Makefile, README 2013-01-31 19:06:32 -05:00
018ecab310 Make setup.py executable 2013-01-31 17:26:55 -05:00
6a1d6017e2 Include datetime_tz module 2013-01-31 17:25:14 -05:00
e7406f8147 Add metadata 2013-01-31 17:14:47 -05:00
f316026592 Move datetime_tz package under nilmdb.utils
datetime_tz isn't readily available, so it's a lot easier to just
package it within the nilmdb tree.
2013-01-30 19:03:42 -05:00
a8db747768 More work on setup.py; fixed issues in setup.cfg
Adjusted setup.cfg so "python setup.py nosetests" now works correctly.
Also added a "test" alias so that "python setup.py test" works.
2013-01-30 18:35:12 -05:00
727af94722 Start working on setup.py 2013-01-29 20:21:03 -05:00
6c89659df7 Cleanup cmdline "create" help text 2013-01-28 19:07:48 -05:00
58c7c8f6ff Support "now" as a timestamp argument 2013-01-28 19:07:45 -05:00
225003f412 Huge cleanup of namespaces, modules, packages, imports.
Now nilmdb.client, nilmdb.server, nilmdb.cmdline, and nilmdb.utils
are each their own modules, and there is a little bit more of a
logical separation between them.  Various changes scattered throughout
to fix naming (for example, nilmdb.nilmdb.NilmDBError is now
nilmdb.server.errors.NilmDBError).

Reduced usage of "from __future__ import absolute_import" as much
as possible.  It's still needed for the functions in the nilmdb/server
directory to be able to import the nilmdb module rather than the
nilmdb.py script.

This should hopefully ease future packaging a bit.
2013-01-28 19:04:52 -05:00
40b966aef2 Add pycurl-specific hack to Iteratorizer
Inside the pycurl callback, we can't raise exceptions, because the
pycurl extension module will unconditionally print the exception
itself, and not pass it up to the caller.  Instead, we have the
callback return a value that tells curl to abort.  (-1 would be best,
in case we were given 0 bytes, but the extension doesn't support
that either).

This resolves the 'Exception("should die")' problem when interrupting
a streaming generator like stream_extract.
2013-01-24 19:06:20 -05:00
294ec6988b Rewrite Iteratorizer as a context manager
Relying on __del__ to clean up the thread isn't as reliable.
2013-01-24 19:04:25 -05:00
fad23ebb22 Add --timestamp-raw option to extract and list 2013-01-24 16:03:38 -05:00
b226dc4337 Properly handle test case where server doesn't start 2013-01-24 16:03:38 -05:00
e7af863017 httpclient: make sure we error out quickly if nested calls are made
Curl will give an error if we call .setopt() while a .perform() is
in progress, for example if we try to do a stream_insert() while
in the middle of a stream_extract().  Move the setopt() to the
beginning of the get/put functions to ensure that we hit this
error before we mess with the URLs or anything else.
2013-01-24 15:36:10 -05:00
af6ce5b79c Remove superfluous from iteratorizor callback exception 2013-01-23 15:42:27 -05:00
0a6fc943e2 Add some better documentation of layout parameter to create.py 2013-01-22 18:47:39 -05:00
67c6e178e1 Documentation updates 2013-01-22 18:36:05 -05:00
9bf213707c Properly return an error if two timestamps are equal 2013-01-22 18:35:18 -05:00
5cd7899e98 Send a Access-Control-Allow-Origin (CORS) header with all responses 2013-01-22 14:42:03 -05:00
ceec5fb9b3 Force /stream/interval and /stream/extract responses to be text/plain 2013-01-22 12:47:06 -05:00
85be497edb Fix README 2013-01-21 17:30:01 -05:00
bd1b7107af Update TODO, clean up bulkdata error message 2013-01-21 11:43:28 -05:00
b8275f108d Make error message more helpful 2013-01-18 17:27:57 -05:00
2820ff9758 More fixes to mustclose decorator and argspecs 2013-01-18 17:21:30 -05:00
a015de893d Cleanup 2013-01-18 17:14:26 -05:00
b7f746e66d Fix lrucache decorator argspecs 2013-01-18 17:13:50 -05:00
40cf4941f0 Test that argspecs are maintained in lrucache 2013-01-18 17:01:46 -05:00
8a418ceb3e Fix issue where mustclose decorator doesn't maintain argspec 2013-01-18 16:57:15 -05:00
0312b6eb07 Test for issue where mustclose decorator didn't maintain argspec 2013-01-18 16:55:51 -05:00
077f197d24 Fix server returning 500 for bad HTTP parameters 2013-01-18 16:54:49 -05:00
62354b4dce Add test for bad-parameters-give-500-error 2013-01-17 19:58:48 -05:00
5970cd85cf Disable "ie-friendly" error message padding in CherryPy 2013-01-16 17:57:45 -05:00
4f6a742e6c Fix test failure 2013-01-16 17:31:31 -05:00
87b43e5d04 Command line errors cleaned up and made more consistent 2013-01-16 16:52:43 -05:00
f0c2a64ae3 Update doc formatting, .gitignore 2013-01-09 23:36:23 -05:00
e5d3deb6fe Removal support is complete.
`nrows` may change if you restart the server; documented why this is
the case in the design.md file.  It's not a problem.
2013-01-09 23:26:59 -05:00
d321058b48 Add basic versioning to bulkdata table format file. 2013-01-09 19:26:24 -05:00
cea83140c0 More work towards correctly removing rows. 2013-01-09 19:25:45 -05:00
7807d6caf0 Progress and tests for bulkdata.remove
Passes tests, but doesn't really handle nrows (and removing partially
full files) correctly, when deleting near the end of the data.
2013-01-09 17:39:29 -05:00
3d0fad3c2a Move some helper functions around 2013-01-09 17:39:29 -05:00
fe3b087435 Remove implemented in nilmdb; still needs bulkdata changes. 2013-01-08 21:07:52 -05:00
bcefe52298 nilmdb: Bring out range manipulating SQL so we can reuse it 2013-01-08 18:45:03 -05:00
f88c148ccc Interval removal work in progress. Needs NilmDB and BulkData work. 2013-01-08 18:37:01 -05:00
4a47b1d04a remove support: command line, client 2013-01-06 20:13:57 -05:00
80da937cb7 cmdline: return error when start > end (extract, list, remove) 2013-01-06 20:13:28 -05:00
c81972e66e Minor testsuite and commandline fixes.
Now supports "list /foo/bar" in addition to the older "list --path /foo/bar"
2013-01-06 19:25:07 -05:00
b09362fde1 Full coverage of nilmdb.utils.mustclose 2013-01-05 18:02:53 -05:00
b7688844fa Add a Nosetests plugin that lets me specify a test order within a directory. 2013-01-05 18:02:37 -05:00
3d212e7592 Move test helpers into subdirectory 2013-01-05 15:00:34 -05:00
7aedfdf9c3 Add lower level bulkdata test 2013-01-05 14:55:22 -05:00
ebd4f74959 Remove "pragma: no cover" from things that should get tested 2013-01-05 14:52:06 -05:00
ebe2fbab92 Add wrap_verify option to nilmdb.utils.must_close decorator 2013-01-05 14:51:41 -05:00
4831a0cae1 Small doc updates 2013-01-04 17:27:04 -05:00
07192c6ffb nilmdb.BulkData: Switch to nested subdir/filename layout
Use numbered subdirectories to avoid having too many files in one dir.
Add appropriate tests.

Also fix an issue where the mmap_open LRU cache could inappropriately
open a file twice because it was using the optional "newsize"
parameter as a key -- now lrucache can be given a slice object that
describes which arguments are important.
2013-01-04 16:51:05 -05:00
09d325e8ab Rename format -> _format in data dirs 2013-01-03 20:46:15 -05:00
11b0293d5f Clean up BulkData file size calculations, test more thoroughly
Now the goal is 128 MiB files, rather than a specific length.
2013-01-03 20:19:01 -05:00
493bbed82c More coverage and tests 2013-01-03 19:21:12 -05:00
3bc25daaab Trim urllib to get full coverage of the features in use 2013-01-03 17:10:07 -05:00
40a3bc4bc3 Update README with Python 2.7 requirement 2013-01-03 17:09:51 -05:00
c083d63c96 Tests for Unicode compliance 2013-01-03 17:03:52 -05:00
0221e3ea21 Update commandline test helpers to better handle Unicode
We replace cStringIO with StringIO subclass that forces UTF-8
encoding, and explicitly convert commandlines to UTF-8 before
shlex.  These changes will only affect tests, not normal commandline
operation.
2013-01-03 17:03:52 -05:00
f5fd2b064e Replace urllib.encode() with a version that encodes Unicode as UTF-8 instead 2013-01-03 17:02:38 -05:00
06e91a6a98 Always use function version of print() 2013-01-03 17:02:38 -05:00
41b3f3c018 Always use UTF-8 for filenames in nilmdb.bulkdata 2013-01-03 17:02:38 -05:00
842076fef4 Cleanup server error handling with decorator 2013-01-03 17:02:38 -05:00
10d58f6a47 More test coverage 2013-01-02 00:00:05 -05:00
e2464efc12 Test everything; remove debugging 2013-01-01 23:46:54 -05:00
1beae5024e Bulkdata extract works now. 2013-01-01 23:44:52 -05:00
c7c65b6542 Work around CherryPy bug #1200; related cleanups
Spent way too long trying to track down a cryptic error that turned
out to be a CherryPy bug.  Now we catch this using a decorator in the
'extract' and 'intervals' generators that transforms exceptions that
trigger the bugs into one that does not.  fun!
2013-01-01 23:03:53 -05:00
f41ff0a6e8 Inserting bulk data is essentially done, not tested 2013-01-01 21:04:35 -05:00
389c1d189f Make option to turn off chunked encoding for debugging more clear. 2013-01-01 21:03:33 -05:00
487298986e More work towards bulkdata 2012-12-31 18:44:57 -05:00
d4cd045c48 Fix path stuff, build packer in bulkdata.Table 2012-12-31 17:22:30 -05:00
3816645313 More work on BulkData 2012-12-31 17:22:30 -05:00
83b937c720 More Pytables -> bulkdata conversion 2012-12-31 17:22:30 -05:00
b3e6e8976f More work towards flat bulk data storage.
Cleaned up OS-specific path handling in nilmdb, bulkdata.
2012-12-31 17:22:30 -05:00
c890ea93cb WIP switching away from PyTables 2012-12-31 17:22:29 -05:00
84c68c6913 Better documentation, cache Tables 2012-12-31 17:22:29 -05:00
6f1e6fe232 Isolate all PyTables stuff to a single file.
This will make migrating to my own data storage engine easier.
2012-12-31 17:22:29 -05:00
b0d76312d1 Add must_close() decorator, use it in nilmdb
Warns at runtime if a class's close() method wasn't called before the
object was destroyed.
2012-12-31 17:21:19 -05:00
19c846c71c Remove outdated files 2012-12-31 15:55:43 -05:00
f355c73209 Refactor utility classes into nilmdb.utils subdir/namespace
There's some bug with the testing harness where placing e.g.
  from du import du
in nilmdb/utils/__init__.py doesn't quite work -- sometimes the
module "du" replaces the function "du".  Not exactly sure why;
we work around that by just renaming files so they don't match
the imported names directly.
2012-12-31 15:55:36 -05:00
173014ba19 Use nilmdb.lrucache for caching interval sets 2012-12-31 14:52:46 -05:00
24d4752bc3 Add LRU cache memoizing decorator for functions 2012-12-31 14:39:16 -05:00
a85b273e2e Remove compression.
Messes up extraction, since we random access for the timestamp binary
search.  In the future, maybe switching to multiple tables (one for
timestamp, one for compressed data) would be smart.
2012-12-14 17:19:23 -05:00
7f73b4b304 Use compression in pytables 2012-12-14 17:17:52 -05:00
f3eb6d1b79 Time it! 2012-12-14 16:57:02 -05:00
9082cc9f44 Merging adjacent intervals is working now!
Adjust test expectations accordingly, since the number of intervals
they print out will now be smaller.
2012-12-12 19:25:27 -05:00
bf64a40472 Some misc test additions, interval optimizations. Still need adjacency test 2012-12-11 23:31:55 -05:00
32dbeebc09 More insertion checks. Need to get interval concatenation working. 2012-12-11 18:08:00 -05:00
66ddc79b15 Inserting works again, with proper end/start for paired blocks.
timeit.sh script works too!
2012-12-07 20:30:39 -05:00
7a8bd0bf41 Don't include layout on client side 2012-12-07 16:24:15 -05:00
ee552de740 Start reworking/fixing insert timestamps 2012-12-06 20:25:24 -05:00
6d1fb61573 Use 'repr' instead of 'str' in Interval string representation.
Otherwise timestamps get truncated to 2 decimal places.
2012-12-05 17:47:48 -05:00
f094529e66 TODO update 2012-12-04 22:15:53 -05:00
5fecec2a4c Support deleting streams with new 'destroy' command 2012-12-04 22:15:00 -05:00
85bb46f45c Use pytable's createparents flag to avoid having to create group
structure manually.
2012-12-04 18:57:36 -05:00
17c329fd6d Start to be a little more strict about how intervals are half-open. 2012-11-29 15:35:11 -05:00
437e1b425a More speed tests, some whitespace cleanups 2012-11-29 15:22:47 -05:00
c0f87db3c1 Converted rbtree, interval to Cython. Serious speedups! 2012-11-29 15:13:09 -05:00
a9c5c19e30 Start converting interval.py to Cython. 2012-11-29 12:42:38 -05:00
f39567b2bc Speed updates 2012-11-29 01:35:01 -05:00
99ec0f4946 Converted rbtree.py to Cython
About 3x faster
2012-11-29 01:25:51 -05:00
f5c60f68dc Speed tests.
test_interval_speed is about O(n * log n), which is good -- but the
constants are high and it hits swap on a 4G machine for the 2**21
test.  Hopefully cython helps!
2012-11-29 01:00:54 -05:00
bdef0986d6 rbtree and interval tests fully pass now.
On to benchmarking...
2012-11-29 00:42:50 -05:00
c396c4dac8 rbtree tests complete 2012-11-29 00:07:49 -05:00
0b443f510b Filling out rbtree tests, search routines 2012-11-28 20:57:23 -05:00
66fa6f3824 Add rendering test 2012-11-28 18:34:51 -05:00
875fbe969f Some documentation and other cleanups in rbtree.py 2012-11-28 18:30:21 -05:00
e35e85886e add .gitignore 2012-11-28 17:21:51 -05:00
7211217f40 Working on getting the RBTree working. Intersections are busted.
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11380 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-15 18:55:56 +00:00
d34b980516 RBTree seems generally OK now
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11379 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-14 20:10:43 +00:00
6aee52d980 Deletion is still broken. F.
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11378 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-14 04:23:53 +00:00
090c8d5315 More progress
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11377 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-14 04:12:15 +00:00
1042ff9f4b add RBtree C++ example that I based this on; update tests
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11376 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-14 03:55:37 +00:00
bc687969c1 Work in progress switching to my own RBTree. Currently creates loops
somewhere, need to figure out what's going on.


git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11375 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-14 03:48:04 +00:00
de27bd3f41 Attempt at using a sentinel instead of class instances for the leaf node.. doesnt quite work for deletion
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11361 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-10 02:12:01 +00:00
4dcf713d0e Attempts at speeding up the RbTree implementation
with cython.  Still quite a bit slower than the bxinterval
implementation, though.


git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11360 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-09 21:06:04 +00:00
f9dea53c24 Randomize order for the insertion test
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11358 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-08 23:50:23 +00:00
6cedd7c327 fix
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11357 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-08 23:44:21 +00:00
6278d32f7d Passes tests, but is slow
git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11356 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-08 23:08:01 +00:00
991039903c Partial implementation of Interval and IntervalSet with a red-black
tree.

This is currently hitting an issue where it's considering the
intersection of [0,1] and [1,2] to be [1,1].  It matches the 
fully-closed definition of intervals, unlike before -- but might
cause issues.  Need to consider whether test case is correct.


git-svn-id: https://bucket.mit.edu/svn/nilm/nilmdb@11355 ddd99763-3ecb-0310-9145-efcb8ce7c51f
2012-11-08 22:56:05 +00:00
119 changed files with 26413 additions and 18732 deletions

View File

@@ -7,3 +7,4 @@
exclude_lines =
pragma: no cover
if 0:
omit = nilmdb/utils/datetime_tz*,nilmdb/scripts,nilmdb/_version.py,nilmdb/fsck

1
.gitattributes vendored Normal file
View File

@@ -0,0 +1 @@
nilmdb/_version.py export-subst

25
.gitignore vendored Normal file
View File

@@ -0,0 +1,25 @@
# Tests
tests/*testdb/
.coverage
db/
# Compiled / cythonized files
docs/*.html
build/
*.pyc
nilmdb/server/interval.c
nilmdb/server/layout.c
nilmdb/server/rbtree.c
*.so
# Setup junk
dist/
nilmdb.egg-info/
# This gets generated as needed by setup.py
MANIFEST.in
MANIFEST
# Misc
timeit*out

250
.pylintrc Normal file
View File

@@ -0,0 +1,250 @@
# -*- conf -*-
[MASTER]
# Specify a configuration file.
#rcfile=
# Python code to execute, usually for sys.path manipulation such as
# pygtk.require().
#init-hook=
# Profiled execution.
profile=no
# Add files or directories to the blacklist. They should be base names, not
# paths.
ignore=datetime_tz
# Pickle collected data for later comparisons.
persistent=no
# List of plugins (as comma separated values of python modules names) to load,
# usually to register additional checkers.
load-plugins=
[MESSAGES CONTROL]
# Enable the message, report, category or checker with the given id(s). You can
# either give multiple identifier separated by comma (,) or put this option
# multiple time.
#enable=
# Disable the message, report, category or checker with the given id(s). You
# can either give multiple identifier separated by comma (,) or put this option
# multiple time (only on the command line, not in the configuration file where
# it should appear only once).
disable=C0111,R0903,R0201,R0914,R0912,W0142,W0703,W0702
[REPORTS]
# Set the output format. Available formats are text, parseable, colorized, msvs
# (visual studio) and html
output-format=parseable
# Include message's id in output
include-ids=yes
# Put messages in a separate file for each module / package specified on the
# command line instead of printing them on stdout. Reports (if any) will be
# written in a file name "pylint_global.[txt|html]".
files-output=no
# Tells whether to display a full report or only the messages
reports=yes
# Python expression which should return a note less than 10 (10 is the highest
# note). You have access to the variables errors warning, statement which
# respectively contain the number of errors / warnings messages and the total
# number of statements analyzed. This is used by the global evaluation report
# (RP0004).
evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)
# Add a comment according to your evaluation note. This is used by the global
# evaluation report (RP0004).
comment=no
[SIMILARITIES]
# Minimum lines number of a similarity.
min-similarity-lines=4
# Ignore comments when computing similarities.
ignore-comments=yes
# Ignore docstrings when computing similarities.
ignore-docstrings=yes
[TYPECHECK]
# Tells whether missing members accessed in mixin class should be ignored. A
# mixin class is detected if its name ends with "mixin" (case insensitive).
ignore-mixin-members=yes
# List of classes names for which member attributes should not be checked
# (useful for classes with attributes dynamically set).
ignored-classes=SQLObject
# When zope mode is activated, add a predefined set of Zope acquired attributes
# to generated-members.
zope=no
# List of members which are set dynamically and missed by pylint inference
# system, and so shouldn't trigger E0201 when accessed. Python regular
# expressions are accepted.
generated-members=REQUEST,acl_users,aq_parent
[FORMAT]
# Maximum number of characters on a single line.
max-line-length=80
# Maximum number of lines in a module
max-module-lines=1000
# String used as indentation unit. This is usually " " (4 spaces) or "\t" (1
# tab).
indent-string=' '
[MISCELLANEOUS]
# List of note tags to take in consideration, separated by a comma.
notes=FIXME,XXX,TODO
[VARIABLES]
# Tells whether we should check for unused import in __init__ files.
init-import=no
# A regular expression matching the beginning of the name of dummy variables
# (i.e. not used).
dummy-variables-rgx=_|dummy
# List of additional names supposed to be defined in builtins. Remember that
# you should avoid to define new builtins when possible.
additional-builtins=
[BASIC]
# Required attributes for module, separated by a comma
required-attributes=
# List of builtins function names that should not be used, separated by a comma
bad-functions=apply,input
# Regular expression which should only match correct module names
module-rgx=(([a-z_][a-z0-9_]*)|([A-Z][a-zA-Z0-9]+))$
# Regular expression which should only match correct module level names
const-rgx=(([A-Z_][A-Z0-9_]*)|(__.*__)|version)$
# Regular expression which should only match correct class names
class-rgx=[A-Z_][a-zA-Z0-9]+$
# Regular expression which should only match correct function names
function-rgx=[a-z_][a-z0-9_]{0,30}$
# Regular expression which should only match correct method names
method-rgx=[a-z_][a-z0-9_]{0,30}$
# Regular expression which should only match correct instance attribute names
attr-rgx=[a-z_][a-z0-9_]{0,30}$
# Regular expression which should only match correct argument names
argument-rgx=[a-z_][a-z0-9_]{0,30}$
# Regular expression which should only match correct variable names
variable-rgx=[a-z_][a-z0-9_]{0,30}$
# Regular expression which should only match correct list comprehension /
# generator expression variable names
inlinevar-rgx=[A-Za-z_][A-Za-z0-9_]*$
# Good variable names which should always be accepted, separated by a comma
good-names=i,j,k,ex,Run,_
# Bad variable names which should always be refused, separated by a comma
bad-names=foo,bar,baz,toto,tutu,tata
# Regular expression which should only match functions or classes name which do
# not require a docstring
no-docstring-rgx=__.*__
[CLASSES]
# List of interface methods to ignore, separated by a comma. This is used for
# instance to not check methods defines in Zope's Interface base class.
ignore-iface-methods=isImplementedBy,deferred,extends,names,namesAndDescriptions,queryDescriptionFor,getBases,getDescriptionFor,getDoc,getName,getTaggedValue,getTaggedValueTags,isEqualOrExtendedBy,setTaggedValue,isImplementedByInstancesOf,adaptWith,is_implemented_by
# List of method names used to declare (i.e. assign) instance attributes.
defining-attr-methods=__init__,__new__,setUp
# List of valid names for the first argument in a class method.
valid-classmethod-first-arg=cls
[DESIGN]
# Maximum number of arguments for function / method
max-args=5
# Argument names that match this expression will be ignored. Default to name
# with leading underscore
ignored-argument-names=_.*
# Maximum number of locals for function / method body
max-locals=15
# Maximum number of return / yield for function / method body
max-returns=6
# Maximum number of branch for function / method body
max-branchs=12
# Maximum number of statements in function / method body
max-statements=50
# Maximum number of parents for a class (see R0901).
max-parents=7
# Maximum number of attributes for a class (see R0902).
max-attributes=7
# Minimum number of public methods for a class (see R0903).
min-public-methods=2
# Maximum number of public methods for a class (see R0904).
max-public-methods=20
[IMPORTS]
# Deprecated modules which should not be used, separated by a comma
deprecated-modules=regsub,string,TERMIOS,Bastion,rexec
# Create a graph of every (i.e. internal and external) dependencies in the
# given file (report RP0402 must not be disabled)
import-graph=
# Create a graph of external dependencies in the given file (report RP0402 must
# not be disabled)
ext-import-graph=
# Create a graph of internal dependencies in the given file (report RP0402 must
# not be disabled)
int-import-graph=
[EXCEPTIONS]
# Exceptions that will emit a warning when being caught. Defaults to
# "Exception"
overgeneral-exceptions=Exception

View File

@@ -1,20 +1,50 @@
all: test
# By default, run the tests.
all: fscktest
tool:
python nilmtool.py --help
python nilmtool.py list --help
python nilmtool.py -u asfdadsf list
version:
python setup.py version
build:
python setup.py build_ext --inplace
dist: sdist
sdist:
python setup.py sdist
install:
python setup.py install
develop:
python setup.py develop
docs:
make -C docs
lint:
pylint -f parseable nilmdb
pylint --rcfile=.pylintrc nilmdb
fscktest:
python -c "import nilmdb.fsck; nilmdb.fsck.Fsck('/home/jim/wsgi/db').check()"
# python -c "import nilmdb.fsck; nilmdb.fsck.Fsck('/home/jim/mnt/bucket/mnt/sharon/data/db', True).check()"
test:
nosetests
profile:
nosetests --with-profile
ifeq ($(INSIDE_EMACS), t)
# Use the slightly more flexible script
python setup.py build_ext --inplace
python tests/runtests.py
else
# Let setup.py check dependencies, build stuff, and run the test
python setup.py nosetests
endif
clean::
find . -name '*pyc' | xargs rm -f
rm -f .coverage
rm -rf tests/*testdb*
rm -rf nilmdb.egg-info/ build/ nilmdb/server/*.so MANIFEST.in
make -C docs clean
gitclean::
git clean -dXf
.PHONY: all version build dist sdist install docs lint test clean gitclean

View File

@@ -1,2 +1,33 @@
sudo apt-get install python-nose python-coverage
sudo apt-get install python-tables cython python-cherrypy3
nilmdb: Non-Intrusive Load Monitor Database
by Jim Paris <jim@jtan.com>
Prerequisites:
# Runtime and build environments
sudo apt-get install python2.7 python2.7-dev python-setuptools cython
# Base NilmDB dependencies
sudo apt-get install python-cherrypy3 python-decorator python-simplejson
sudo apt-get install python-requests python-dateutil python-tz
sudo apt-get install python-progressbar python-psutil
# Other dependencies (required by some modules)
sudo apt-get install python-numpy
# Tools for running tests
sudo apt-get install python-nose python-coverage
Test:
python setup.py nosetests
Install:
python setup.py install
Usage:
nilmdb-server --help
nilmdb-fsck --help
nilmtool --help
See docs/wsgi.md for info on setting up a WSGI application in Apache.

5
TODO
View File

@@ -1,5 +0,0 @@
- Merge adjacent intervals on insert (maybe with client help?)
- Better testing:
- see about getting coverage on layout.pyx
- layout.pyx performance tests, before and after generalization

181
design.md
View File

@@ -1,181 +0,0 @@
Structure
---------
nilmdb.nilmdb is the NILM database interface. It tracks a PyTables
database holds actual rows of data, and a SQL database tracks metadata
and ranges.
Access to the nilmdb must be single-threaded. This is handled with
the nilmdb.serializer class.
nilmdb.server is a HTTP server that provides an interface to talk,
thorugh the serialization layer, to the nilmdb object.
nilmdb.client is a HTTP client that connects to this.
Sqlite performance
------------------
Committing a transaction in the default sync mode (PRAGMA synchronous=FULL)
takes about 125msec. sqlite3 will commit transactions at 3 times:
1: explicit con.commit()
2: between a series of DML commands and non-DML commands, e.g.
after a series of INSERT, SELECT, but before a CREATE TABLE or
PRAGMA.
3: at the end of an explicit transaction, e.g. "with self.con as con:"
To speed up testing, or if this transaction speed becomes an issue,
the sync=False option to NilmDB will set PRAGMA synchronous=OFF.
Inserting streams
-----------------
We need to send the contents of "data" as POST. Do we need chunked
transfer?
- Don't know the size in advance, so we would need to use chunked if
we send the entire thing in one request.
- But we shouldn't send one chunk per line, so we need to buffer some
anyway; why not just make new requests?
- Consider the infinite-streaming case, we might want to send it
immediately? Not really -- server still should do explicit inserts
of fixed-size chunks.
- Even chunked encoding needs the size of each chunk beforehand, so
everything still gets buffered. Just a tradeoff of buffer size.
Before timestamps are added:
- Raw data is about 440 kB/s (9 channels)
- Prep data is about 12.5 kB/s (1 phase)
- How do we know how much data to send?
- Remember that we can only do maybe 8-50 transactions per second on
the sqlite database. So if one block of inserted data is one
transaction, we'd need the raw case to be around 64kB per request,
ideally more.
- Maybe use a range, based on how long it's taking to read the data
- If no more data, send it
- If data > 1 MB, send it
- If more than 10 seconds have elapsed, send it
- Should those numbers come from the server?
Converting from ASCII to PyTables:
- For each row getting added, we need to set attributes on a PyTables
Row object and call table.append(). This means that there isn't a
particularly efficient way of converting from ascii.
- Could create a function like nilmdb.layout.Layout("foo".fillRow(asciiline)
- But this means we're doing parsing on the serialized side
- Let's keep parsing on the threaded server side so we can detect
errors better, and not block the serialized nilmdb for a slow
parsing process.
- Client sends ASCII data
- Server converts this ACSII data to a list of values
- Maybe:
# threaded side creates this object
parser = nilmdb.layout.Parser("layout_name")
# threaded side parses and fills it with data
parser.parse(textdata)
# serialized side pulls out rows
for n in xrange(parser.nrows):
parser.fill_row(rowinstance, n)
table.append()
Inserting streams, inside nilmdb
--------------------------------
- First check that the new stream doesn't overlap.
- Get minimum timestamp, maximum timestamp from data parser.
- (extend parser to verify monotonicity and track extents)
- Get all intervals for this stream in the database
- See if new interval overlaps any existing ones
- If so, bail
- Question: should we cache intervals inside NilmDB?
- Assume database is fast for now, and always rebuild fom DB.
- Can add a caching layer later if we need to.
- `stream_get_ranges(path)` -> return IntervalSet?
Speed
-----
- First approach was quadratic. Adding four hours of data:
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-110000 /bpnilm/1/raw
real 24m31.093s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-120001 /bpnilm/1/raw
real 43m44.528s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-130002 /bpnilm/1/raw
real 93m29.713s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-140003 /bpnilm/1/raw
real 166m53.007s
- Disabling pytables indexing didn't help:
real 31m21.492s
real 52m51.963s
real 102m8.151s
real 176m12.469s
- Server RAM usage is constant.
- Speed problems were due to IntervalSet speed, of parsing intervals
from the database and adding the new one each time.
- First optimization is to cache result of `nilmdb:_get_intervals`,
which gives the best speedup.
- Also switched to internally using bxInterval from bx-python package.
Speed of `tests/test_interval:TestIntervalSpeed` is pretty decent
and seems to be growing logarithmically now. About 85μs per insertion
for inserting 131k entries.
- Storing the interval data in SQL might be better, with a scheme like:
http://www.logarithmic.net/pfh/blog/01235197474
- Next slowdown target is nilmdb.layout.Parser.parse().
- Rewrote parsers using cython and sscanf
- Stats (rev 10831), with _add_interval disabled
layout.pyx.Parser.parse:128 6303 sec, 262k calls
layout.pyx.parse:63 13913 sec, 5.1g calls
numpy:records.py.fromrecords:569 7410 sec, 262k calls
- Probably OK for now.
IntervalSet speed
-----------------
- Initial implementation was pretty slow, even with binary search in
sorted list
- Replaced with bxInterval; now takes about log n time for an insertion
- TestIntervalSpeed with range(17,18) and profiling
- 85 μs each
- 131072 calls to `__iadd__`
- 131072 to bx.insert_interval
- 131072 to bx.insert:395
- 2355835 to bx.insert:106 (18x as many?)
- Tried blist too, worse than bxinterval.
- Might be algorithmic improvements to be made in Interval.py,
like in `__and__`
Layouts
-------
Current/old design has specific layouts: RawData, PrepData, RawNotchedData.
Let's get rid of this entirely and switch to simpler data types that are
just collections and counts of a single type. We'll still use strings
to describe them, with format:
type_count
where type is "uint16", "float32", or "float64", and count is an integer.
nilmdb.layout.named() will parse these strings into the appropriate
handlers. For compatibility:
"RawData" == "uint16_6"
"RawNotchedData" == "uint16_9"
"PrepData" == "float32_8"

9
docs/Makefile Normal file
View File

@@ -0,0 +1,9 @@
ALL_DOCS = $(wildcard *.md)
all: $(ALL_DOCS:.md=.html)
%.html: %.md
pandoc -s $< > $@
clean:
rm -f *.html

5
docs/TODO.md Normal file
View File

@@ -0,0 +1,5 @@
- Documentation
- Machine-readable information in OverflowError, parser errors.
Maybe subclass `cherrypy.HTTPError` and override `set_response`
to add another JSON field?

440
docs/design.md Normal file
View File

@@ -0,0 +1,440 @@
Structure
---------
nilmdb.nilmdb is the NILM database interface. A nilmdb.BulkData
interface stores data in flat files, and a SQL database tracks
metadata and ranges.
Access to the nilmdb must be single-threaded. This is handled with
the nilmdb.serializer class. In the future this could probably
be turned into a per-path serialization.
nilmdb.server is a HTTP server that provides an interface to talk,
thorugh the serialization layer, to the nilmdb object.
nilmdb.client is a HTTP client that connects to this.
Sqlite performance
------------------
Committing a transaction in the default sync mode (PRAGMA synchronous=FULL)
takes about 125msec. sqlite3 will commit transactions at 3 times:
1. explicit con.commit()
2. between a series of DML commands and non-DML commands, e.g.
after a series of INSERT, SELECT, but before a CREATE TABLE or
PRAGMA.
3. at the end of an explicit transaction, e.g. "with self.con as con:"
To speed up testing, or if this transaction speed becomes an issue,
the sync=False option to NilmDB will set PRAGMA synchronous=OFF.
Inserting streams
-----------------
We need to send the contents of "data" as POST. Do we need chunked
transfer?
- Don't know the size in advance, so we would need to use chunked if
we send the entire thing in one request.
- But we shouldn't send one chunk per line, so we need to buffer some
anyway; why not just make new requests?
- Consider the infinite-streaming case, we might want to send it
immediately? Not really -- server still should do explicit inserts
of fixed-size chunks.
- Even chunked encoding needs the size of each chunk beforehand, so
everything still gets buffered. Just a tradeoff of buffer size.
Before timestamps are added:
- Raw data is about 440 kB/s (9 channels)
- Prep data is about 12.5 kB/s (1 phase)
- How do we know how much data to send?
- Remember that we can only do maybe 8-50 transactions per second on
the sqlite database. So if one block of inserted data is one
transaction, we'd need the raw case to be around 64kB per request,
ideally more.
- Maybe use a range, based on how long it's taking to read the data
- If no more data, send it
- If data > 1 MB, send it
- If more than 10 seconds have elapsed, send it
- Should those numbers come from the server?
Converting from ASCII to PyTables:
- For each row getting added, we need to set attributes on a PyTables
Row object and call table.append(). This means that there isn't a
particularly efficient way of converting from ascii.
- Could create a function like nilmdb.layout.Layout("foo".fillRow(asciiline)
- But this means we're doing parsing on the serialized side
- Let's keep parsing on the threaded server side so we can detect
errors better, and not block the serialized nilmdb for a slow
parsing process.
- Client sends ASCII data
- Server converts this ACSII data to a list of values
- Maybe:
# threaded side creates this object
parser = nilmdb.layout.Parser("layout_name")
# threaded side parses and fills it with data
parser.parse(textdata)
# serialized side pulls out rows
for n in xrange(parser.nrows):
parser.fill_row(rowinstance, n)
table.append()
Inserting streams, inside nilmdb
--------------------------------
- First check that the new stream doesn't overlap.
- Get minimum timestamp, maximum timestamp from data parser.
- (extend parser to verify monotonicity and track extents)
- Get all intervals for this stream in the database
- See if new interval overlaps any existing ones
- If so, bail
- Question: should we cache intervals inside NilmDB?
- Assume database is fast for now, and always rebuild fom DB.
- Can add a caching layer later if we need to.
- `stream_get_ranges(path)` -> return IntervalSet?
Speed
-----
- First approach was quadratic. Adding four hours of data:
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-110000 /bpnilm/1/raw
real 24m31.093s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-120001 /bpnilm/1/raw
real 43m44.528s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-130002 /bpnilm/1/raw
real 93m29.713s
$ time zcat /home/jim/bpnilm-data/snapshot-1-20110513-110002.raw.gz | ./nilmtool.py insert -s 20110513-140003 /bpnilm/1/raw
real 166m53.007s
- Disabling pytables indexing didn't help:
real 31m21.492s
real 52m51.963s
real 102m8.151s
real 176m12.469s
- Server RAM usage is constant.
- Speed problems were due to IntervalSet speed, of parsing intervals
from the database and adding the new one each time.
- First optimization is to cache result of `nilmdb:_get_intervals`,
which gives the best speedup.
- Also switched to internally using bxInterval from bx-python package.
Speed of `tests/test_interval:TestIntervalSpeed` is pretty decent
and seems to be growing logarithmically now. About 85μs per insertion
for inserting 131k entries.
- Storing the interval data in SQL might be better, with a scheme like:
http://www.logarithmic.net/pfh/blog/01235197474
- Next slowdown target is nilmdb.layout.Parser.parse().
- Rewrote parsers using cython and sscanf
- Stats (rev 10831), with `_add_interval` disabled
layout.pyx.Parser.parse:128 6303 sec, 262k calls
layout.pyx.parse:63 13913 sec, 5.1g calls
numpy:records.py.fromrecords:569 7410 sec, 262k calls
- Probably OK for now.
- After all updates, now takes about 8.5 minutes to insert an hour of
data, constant after adding 171 hours (4.9 billion data points)
- Data set size: 98 gigs = 20 bytes per data point.
6 uint16 data + 1 uint32 timestamp = 16 bytes per point
So compression must be off -- will retry with compression forced on.
IntervalSet speed
-----------------
- Initial implementation was pretty slow, even with binary search in
sorted list
- Replaced with bxInterval; now takes about log n time for an insertion
- TestIntervalSpeed with range(17,18) and profiling
- 85 μs each
- 131072 calls to `__iadd__`
- 131072 to bx.insert_interval
- 131072 to bx.insert:395
- 2355835 to bx.insert:106 (18x as many?)
- Tried blist too, worse than bxinterval.
- Might be algorithmic improvements to be made in Interval.py,
like in `__and__`
- Replaced again with rbtree. Seems decent. Numbers are time per
insert for 2**17 insertions, followed by total wall time and RAM
usage for running "make test" with `test_rbtree` and `test_interval`
with range(5,20):
- old values with bxinterval:
20.2 μS, total 20 s, 177 MB RAM
- rbtree, plain python:
97 μS, total 105 s, 846 MB RAM
- rbtree converted to cython:
26 μS, total 29 s, 320 MB RAM
- rbtree and interval converted to cython:
8.4 μS, total 12 s, 134 MB RAM
- Would like to move Interval itself back to Python so other
non-cythonized code like client code can use it more easily.
Testing speed with just `test_interval` being tested, with
`range(5,22)`, using `/usr/bin/time -v python tests/runtests.py`,
times recorded for 2097152:
- 52ae397 (Interval in cython):
12.6133 μs each, ratio 0.866533, total 47 sec, 399 MB RAM
- 9759dcf (Interval in python):
21.2937 μs each, ratio 1.462870, total 83 sec, 1107 MB RAM
That's a huge difference! Instead, will keep Interval and DBInterval
cythonized inside nilmdb, and just have an additional copy in
nilmdb.utils for clients to use.
Layouts
-------
Current/old design has specific layouts: RawData, PrepData, RawNotchedData.
Let's get rid of this entirely and switch to simpler data types that are
just collections and counts of a single type. We'll still use strings
to describe them, with format:
type_count
where type is "uint16", "float32", or "float64", and count is an integer.
nilmdb.layout.named() will parse these strings into the appropriate
handlers. For compatibility:
"RawData" == "uint16_6"
"RawNotchedData" == "uint16_9"
"PrepData" == "float32_8"
BulkData design
---------------
BulkData is a custom bulk data storage system that was written to
replace PyTables. The general structure is a `data` subdirectory in
the main NilmDB directory. Within `data`, paths are created for each
created stream. These locations are called tables. For example,
tables might be located at
nilmdb/data/newton/raw/
nilmdb/data/newton/prep/
nilmdb/data/cottage/raw/
Each table contains:
- An unchanging `_format` file (Python pickle format) that describes
parameters of how the data is broken up, like files per directory,
rows per file, and the binary data format
- Hex named subdirectories `("%04x", although more than 65536 can exist)`
- Hex named files within those subdirectories, like:
/nilmdb/data/newton/raw/000b/010a
The data format of these files is raw binary, interpreted by the
Python `struct` module according to the format string in the
`_format` file.
- Same as above, with `.removed` suffix, is an optional file (Python
pickle format) containing a list of row numbers that have been
logically removed from the file. If this range covers the entire
file, the entire file will be removed.
- Note that the `bulkdata.nrows` variable is calculated once in
`BulkData.__init__()`, and only ever incremented during use. Thus,
even if all data is removed, `nrows` can remain high. However, if
the server is restarted, the newly calculated `nrows` may be lower
than in a previous run due to deleted data. To be specific, this
sequence of events:
- insert data
- remove all data
- insert data
will result in having different row numbers in the database, and
differently numbered files on the filesystem, than the sequence:
- insert data
- remove all data
- restart server
- insert data
This is okay! Everything should remain consistent both in the
`BulkData` and `NilmDB`. Not attempting to readjust `nrows` during
deletion makes the code quite a bit simpler.
- Similarly, data files are never truncated shorter. Removing data
from the end of the file will not shorten it; it will only be
deleted when it has been fully filled and all of the data has been
subsequently removed.
Rocket
------
Original design had the nilmdb.nilmdb thread (through bulkdata)
convert from on-disk layout to a Python list, and then the
nilmdb.server thread (from cherrypy) converts to ASCII. For at least
the extraction side of things, it's easy to pass the bulkdata a layout
name instead, and have it convert directly from on-disk to ASCII
format, because this conversion can then be shoved into a C module.
This module, which provides a means for converting directly from
on-disk format to ASCII or Python lists, is the "rocket" interface.
Python is still used to manage the files and figure out where the
data should go; rocket just puts binary data directly in or out of
those files at specified locations.
Before rocket, testing speed with uint16_6 data, with an end-to-end
test (extracting data with nilmtool):
- insert: 65 klines/sec
- extract: 120 klines/sec
After switching to the rocket design, but using the Python version
(pyrocket):
- insert: 57 klines/sec
- extract: 120 klines/sec
After switching to a C extension module (rocket.c)
- insert: 74 klines/sec through insert.py; 99.6 klines/sec through nilmtool
- extract: 335 klines/sec
After client block updates (described below):
- insert: 180 klines/sec through nilmtool (pre-timestamped)
- extract: 390 klines/sec through nilmtool
Using "insert --timestamp" or "extract --bare" cuts the speed in half.
Blocks versus lines
-------------------
Generally want to avoid parsing the bulk of the data as lines if
possible, and transfer things in bigger blocks at once.
Current places where we use lines:
- All data returned by `client.stream_extract`, since it comes from
`httpclient.get_gen`, which iterates over lines. Not sure if this
should be changed, because a `nilmtool extract` is just about the
same speed as `curl -q .../stream/extract`!
- `client.StreamInserter.insert_iter` and
`client.StreamInserter.insert_line`, which should probably get
replaced with block versions. There's no real need to keep
updating the timestamp every time we get a new line of data.
- Finished. Just a single insert() that takes any length string and
does very little processing until it's time to send it to the
server.
Timestamps
----------
Timestamps are currently double-precision floats (64 bit). Since the
mantissa is 53-bit, this can only represent about 15-17 significant
figures, and microsecond Unix timestamps like 1222333444.000111 are
already 16 significant figures. Rounding is therefore an issue;
it's hard to sure that converting from ASCII, then back to ASCII,
will always give the same result.
Also, if the client provides a floating point value like 1.9999999999,
we need to be careful that we don't store it as 1.9999999999 but later
print it as 2.000000, because then round-trips change the data.
Possible solutions:
- When the client provides a floating point value to the server,
always round to the 6th decimal digit before verifying & storing.
Good for compatibility and simplicity. But still might have rounding
issues, and clients will also need to round when doing their own
verification. Having every piece of code need to know which digit
to round at is not ideal.
- Always store int64 timestamps on the server, representing
microseconds since epoch. int64 timestamps are used in all HTTP
parameters, in insert/extract ASCII strings, client API, commandline
raw timestamps, etc. Pretty big change.
This is what we'll go with...
- Client programs that interpret the timestamps as doubles instead
of ints will remain accurate until 2^53 microseconds, or year
2255.
- On insert, maybe it's OK to send floating point microsecond values
(1234567890123456.0), just to cope with clients that want to print
everything as a double. Server could try parsing as int64, and if
that fails, parse as double and truncate to int64. However, this
wouldn't catch imprecise inputs like "1.23456789012e+15". But
maybe that can just be ignored; it's likely to cause a
non-monotonic error at the client.
- Timestamps like 1234567890.123456 never show up anywhere, except
for interfacing to datetime_tz etc. Command line "raw timestamps"
are always printed as int64 values, and a new format
"@1234567890123456" is added to the parser for specifying them
exactly.
Binary interface
----------------
The ASCII interface is too slow for high-bandwidth processing, like
sinefits, prep, etc. A binary interface was added so that you can
extract the raw binary out of the bulkdata storage. This binary is
a little-endian format, e.g. in C a uint16_6 stream would be:
#include <endian.h>
#include <stdint.h>
struct {
int64_t timestamp_le;
uint16_t data_le[6];
} __attribute__((packed));
Remember to byteswap (with e.g. `letoh` in C)!
This interface is used by the new `nilmdb.client.numpyclient.NumpyClient`
class, which is a subclass of the normal `nilmcb.client.client.Client`
and has all of the same functions. It adds three new functions:
- `stream_extract_numpy` to extract data as a Numpy array
- `stream_insert_numpy` to insert data as a Numpy array
- `stream_insert_numpy_context` is the context manager for
incrementally inserting data
It is significantly faster! It is about 20 times faster to decimate a
stream with `nilm-decimate` when the filter code is using the new
binary/numpy interface.
WSGI interface & chunked requests
---------------------------------
mod_wsgi requires "WSGIChunkedRequest On" to handle
"Transfer-encoding: Chunked" requests. However, `/stream/insert`
doesn't handle this correctly right now, because:
- The `cherrpy.request.body.read()` call needs to be fixed for chunked requests
- We don't want to just buffer endlessly in the server, and it will
require some thought on how to handle data in chunks (what to do about
interval endpoints).
It is probably better to just keep the endpoint management on the client
side, so leave "WSGIChunkedRequest off" for now.

32
docs/wsgi.md Normal file
View File

@@ -0,0 +1,32 @@
WSGI Application in Apache
--------------------------
Install `apache2` and `libapache2-mod-wsgi`
We'll set up the database server at URL `http://myhost.com/nilmdb`.
The database will be stored in `/home/nilm/db`, and the process will
run as user `nilm`, group `nilm`.
First, create a WSGI script `/home/nilm/nilmdb.wsgi` containing:
import nilmdb.server
application = nilmdb.server.wsgi_application("/home/nilm/db", "/nilmdb")
The first parameter is the local filesystem path, and the second
parameter is the path part of the URL.
Then, set up Apache with a configuration like:
<VirtualHost>
WSGIScriptAlias /nilmdb /home/nilm/nilmdb.wsgi
WSGIDaemonProcess nilmdb-procgroup threads=32 user=nilm group=nilm
<Location /nilmdb>
WSGIProcessGroup nilmdb-procgroup
WSGIApplicationGroup nilmdb-appgroup
# Access control example:
Order deny,allow
Deny from all
Allow from 1.2.3.4
</Location>
</VirtualHost>

View File

@@ -0,0 +1,50 @@
#!/usr/bin/python
import os
import sys
import cPickle as pickle
import argparse
import fcntl
import re
from nilmdb.client.numpyclient import layout_to_dtype
parser = argparse.ArgumentParser(
description = """
Fix database corruption where binary writes caused too much data to be
written to the file. Truncates files to the correct length. This was
fixed by b98ff1331a515ad47fd3203615e835b529b039f9.
""")
parser.add_argument("path", action="store", help='Database root path')
parser.add_argument("-y", "--yes", action="store_true", help='Fix them')
args = parser.parse_args()
lock = os.path.join(args.path, "data.lock")
with open(lock, "w") as f:
fcntl.flock(f.fileno(), fcntl.LOCK_EX | fcntl.LOCK_NB)
fix = {}
for (path, dirs, files) in os.walk(args.path):
if "_format" in files:
with open(os.path.join(path, "_format")) as format:
fmt = pickle.load(format)
rowsize = layout_to_dtype(fmt["layout"]).itemsize
maxsize = rowsize * fmt["rows_per_file"]
fix[path] = maxsize
if maxsize < 128000000: # sanity check
raise Exception("bad maxsize " + str(maxsize))
for fixpath in fix:
for (path, dirs, files) in os.walk(fixpath):
for fn in files:
if not re.match("^[0-9a-f]{4,}$", fn):
continue
fn = os.path.join(path, fn)
size = os.path.getsize(fn)
maxsize = fix[fixpath]
if size > maxsize:
diff = size - maxsize
print diff, "too big:", fn
if args.yes:
with open(fn, "a+") as dbfile:
dbfile.truncate(maxsize)

View File

@@ -0,0 +1,20 @@
# To enable bash completion:
#
# 1. Ensure python-argcomplete is installed:
# pip install argcomplete
# 2. Source this file:
# . nilmtool-bash-completion.sh
_nilmtool_argcomplete() {
local IFS=$(printf "\013")
COMPREPLY=( $(IFS="$IFS" \
COMP_LINE="$COMP_LINE" \
COMP_WORDBREAKS="$COMP_WORDBREAKS" \
COMP_POINT="$COMP_POINT" \
_ARGCOMPLETE=1 \
"$1" 8>&1 9>&2 1>/dev/null 2>/dev/null) )
if [[ $? != 0 ]]; then
unset COMPREPLY
fi
}
complete -o nospace -F _nilmtool_argcomplete nilmtool

View File

@@ -1,16 +1,10 @@
"""Main NilmDB import"""
from .nilmdb import NilmDB
from .server import Server
from .client import Client
from .timer import Timer
# These aren't imported automatically, because loading the server
# stuff isn't always necessary.
#from nilmdb.server import NilmDB, Server
#from nilmdb.client import Client
import cmdline
import pyximport; pyximport.install()
import layout
import serializer
import timestamper
import interval
import du
from nilmdb._version import get_versions
__version__ = get_versions()['version']
del get_versions

197
nilmdb/_version.py Normal file
View File

@@ -0,0 +1,197 @@
IN_LONG_VERSION_PY = True
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (build by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains the computed version number.
# This file is released into the public domain. Generated by
# versioneer-0.7+ (https://github.com/warner/python-versioneer)
# these strings will be replaced by git during git-archive
git_refnames = "$Format:%d$"
git_full = "$Format:%H$"
import subprocess
import sys
def run_command(args, cwd=None, verbose=False):
try:
# remember shell=False, so use git.cmd on windows, not just git
p = subprocess.Popen(args, stdout=subprocess.PIPE, cwd=cwd)
except EnvironmentError:
e = sys.exc_info()[1]
if verbose:
print("unable to run %s" % args[0])
print(e)
return None
stdout = p.communicate()[0].strip()
if sys.version >= '3':
stdout = stdout.decode()
if p.returncode != 0:
if verbose:
print("unable to run %s (error)" % args[0])
return None
return stdout
import sys
import re
import os.path
def get_expanded_variables(versionfile_source):
# the code embedded in _version.py can just fetch the value of these
# variables. When used from setup.py, we don't want to import
# _version.py, so we do it with a regexp instead. This function is not
# used from _version.py.
variables = {}
try:
for line in open(versionfile_source,"r").readlines():
if line.strip().startswith("git_refnames ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
variables["refnames"] = mo.group(1)
if line.strip().startswith("git_full ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
variables["full"] = mo.group(1)
except EnvironmentError:
pass
return variables
def versions_from_expanded_variables(variables, tag_prefix, verbose=False):
refnames = variables["refnames"].strip()
if refnames.startswith("$Format"):
if verbose:
print("variables are unexpanded, not using")
return {} # unexpanded, so not in an unpacked git-archive tarball
refs = set([r.strip() for r in refnames.strip("()").split(",")])
for ref in list(refs):
if not re.search(r'\d', ref):
if verbose:
print("discarding '%s', no digits" % ref)
refs.discard(ref)
# Assume all version tags have a digit. git's %d expansion
# behaves like git log --decorate=short and strips out the
# refs/heads/ and refs/tags/ prefixes that would let us
# distinguish between branches and tags. By ignoring refnames
# without digits, we filter out many common branch names like
# "release" and "stabilization", as well as "HEAD" and "master".
if verbose:
print("remaining refs: %s" % ",".join(sorted(refs)))
for ref in sorted(refs):
# sorting will prefer e.g. "2.0" over "2.0rc1"
if ref.startswith(tag_prefix):
r = ref[len(tag_prefix):]
if verbose:
print("picking %s" % r)
return { "version": r,
"full": variables["full"].strip() }
# no suitable tags, so we use the full revision id
if verbose:
print("no suitable tags, using full revision id")
return { "version": variables["full"].strip(),
"full": variables["full"].strip() }
def versions_from_vcs(tag_prefix, versionfile_source, verbose=False):
# this runs 'git' from the root of the source tree. That either means
# someone ran a setup.py command (and this code is in versioneer.py, so
# IN_LONG_VERSION_PY=False, thus the containing directory is the root of
# the source tree), or someone ran a project-specific entry point (and
# this code is in _version.py, so IN_LONG_VERSION_PY=True, thus the
# containing directory is somewhere deeper in the source tree). This only
# gets called if the git-archive 'subst' variables were *not* expanded,
# and _version.py hasn't already been rewritten with a short version
# string, meaning we're inside a checked out source tree.
try:
here = os.path.abspath(__file__)
except NameError:
# some py2exe/bbfreeze/non-CPython implementations don't do __file__
return {} # not always correct
# versionfile_source is the relative path from the top of the source tree
# (where the .git directory might live) to this file. Invert this to find
# the root from __file__.
root = here
if IN_LONG_VERSION_PY:
for i in range(len(versionfile_source.split("/"))):
root = os.path.dirname(root)
else:
root = os.path.dirname(here)
if not os.path.exists(os.path.join(root, ".git")):
if verbose:
print("no .git in %s" % root)
return {}
GIT = "git"
if sys.platform == "win32":
GIT = "git.cmd"
stdout = run_command([GIT, "describe", "--tags", "--dirty", "--always"],
cwd=root)
if stdout is None:
return {}
if not stdout.startswith(tag_prefix):
if verbose:
print("tag '%s' doesn't start with prefix '%s'" % (stdout, tag_prefix))
return {}
tag = stdout[len(tag_prefix):]
stdout = run_command([GIT, "rev-parse", "HEAD"], cwd=root)
if stdout is None:
return {}
full = stdout.strip()
if tag.endswith("-dirty"):
full += "-dirty"
return {"version": tag, "full": full}
def versions_from_parentdir(parentdir_prefix, versionfile_source, verbose=False):
if IN_LONG_VERSION_PY:
# We're running from _version.py. If it's from a source tree
# (execute-in-place), we can work upwards to find the root of the
# tree, and then check the parent directory for a version string. If
# it's in an installed application, there's no hope.
try:
here = os.path.abspath(__file__)
except NameError:
# py2exe/bbfreeze/non-CPython don't have __file__
return {} # without __file__, we have no hope
# versionfile_source is the relative path from the top of the source
# tree to _version.py. Invert this to find the root from __file__.
root = here
for i in range(len(versionfile_source.split("/"))):
root = os.path.dirname(root)
else:
# we're running from versioneer.py, which means we're running from
# the setup.py in a source tree. sys.argv[0] is setup.py in the root.
here = os.path.abspath(sys.argv[0])
root = os.path.dirname(here)
# Source tarballs conventionally unpack into a directory that includes
# both the project name and a version string.
dirname = os.path.basename(root)
if not dirname.startswith(parentdir_prefix):
if verbose:
print("guessing rootdir is '%s', but '%s' doesn't start with prefix '%s'" %
(root, dirname, parentdir_prefix))
return None
return {"version": dirname[len(parentdir_prefix):], "full": ""}
tag_prefix = "nilmdb-"
parentdir_prefix = "nilmdb-"
versionfile_source = "nilmdb/_version.py"
def get_versions(default={"version": "unknown", "full": ""}, verbose=False):
variables = { "refnames": git_refnames, "full": git_full }
ver = versions_from_expanded_variables(variables, tag_prefix, verbose)
if not ver:
ver = versions_from_vcs(tag_prefix, versionfile_source, verbose)
if not ver:
ver = versions_from_parentdir(parentdir_prefix, versionfile_source,
verbose)
if not ver:
ver = default
return ver

View File

@@ -1,495 +0,0 @@
# cython: profile=False
# This is from bx-python 554:07aca5a9f6fc (BSD licensed), modified to
# store interval ranges as doubles rather than 32-bit integers.
"""
Data structure for performing intersect queries on a set of intervals which
preserves all information about the intervals (unlike bitset projection methods).
:Authors: James Taylor (james@jamestaylor.org),
Ian Schenk (ian.schenck@gmail.com),
Brent Pedersen (bpederse@gmail.com)
"""
# Historical note:
# This module original contained an implementation based on sorted endpoints
# and a binary search, using an idea from Scott Schwartz and Piotr Berman.
# Later an interval tree implementation was implemented by Ian for Galaxy's
# join tool (see `bx.intervals.operations.quicksect.py`). This was then
# converted to Cython by Brent, who also added support for
# upstream/downstream/neighbor queries. This was modified by James to
# handle half-open intervals strictly, to maintain sort order, and to
# implement the same interface as the original Intersecter.
#cython: cdivision=True
import operator
cdef extern from "stdlib.h":
int ceil(float f)
float log(float f)
int RAND_MAX
int rand()
int strlen(char *)
int iabs(int)
cdef inline double dmax2(double a, double b):
if b > a: return b
return a
cdef inline double dmax3(double a, double b, double c):
if b > a:
if c > b:
return c
return b
if a > c:
return a
return c
cdef inline double dmin3(double a, double b, double c):
if b < a:
if c < b:
return c
return b
if a < c:
return a
return c
cdef inline double dmin2(double a, double b):
if b < a: return b
return a
cdef float nlog = -1.0 / log(0.5)
cdef class IntervalNode:
"""
A single node of an `IntervalTree`.
NOTE: Unless you really know what you are doing, you probably should us
`IntervalTree` rather than using this directly.
"""
cdef float priority
cdef public object interval
cdef public double start, end
cdef double minend, maxend, minstart
cdef IntervalNode cleft, cright, croot
property left_node:
def __get__(self):
return self.cleft if self.cleft is not EmptyNode else None
property right_node:
def __get__(self):
return self.cright if self.cright is not EmptyNode else None
property root_node:
def __get__(self):
return self.croot if self.croot is not EmptyNode else None
def __repr__(self):
return "IntervalNode(%g, %g)" % (self.start, self.end)
def __cinit__(IntervalNode self, double start, double end, object interval):
# Python lacks the binomial distribution, so we convert a
# uniform into a binomial because it naturally scales with
# tree size. Also, python's uniform is perfect since the
# upper limit is not inclusive, which gives us undefined here.
self.priority = ceil(nlog * log(-1.0/(1.0 * rand()/RAND_MAX - 1)))
self.start = start
self.end = end
self.interval = interval
self.maxend = end
self.minstart = start
self.minend = end
self.cleft = EmptyNode
self.cright = EmptyNode
self.croot = EmptyNode
cpdef IntervalNode insert(IntervalNode self, double start, double end, object interval):
"""
Insert a new IntervalNode into the tree of which this node is
currently the root. The return value is the new root of the tree (which
may or may not be this node!)
"""
cdef IntervalNode croot = self
# If starts are the same, decide which to add interval to based on
# end, thus maintaining sortedness relative to start/end
cdef double decision_endpoint = start
if start == self.start:
decision_endpoint = end
if decision_endpoint > self.start:
# insert to cright tree
if self.cright is not EmptyNode:
self.cright = self.cright.insert( start, end, interval )
else:
self.cright = IntervalNode( start, end, interval )
# rebalance tree
if self.priority < self.cright.priority:
croot = self.rotate_left()
else:
# insert to cleft tree
if self.cleft is not EmptyNode:
self.cleft = self.cleft.insert( start, end, interval)
else:
self.cleft = IntervalNode( start, end, interval)
# rebalance tree
if self.priority < self.cleft.priority:
croot = self.rotate_right()
croot.set_ends()
self.cleft.croot = croot
self.cright.croot = croot
return croot
cdef IntervalNode rotate_right(IntervalNode self):
cdef IntervalNode croot = self.cleft
self.cleft = self.cleft.cright
croot.cright = self
self.set_ends()
return croot
cdef IntervalNode rotate_left(IntervalNode self):
cdef IntervalNode croot = self.cright
self.cright = self.cright.cleft
croot.cleft = self
self.set_ends()
return croot
cdef inline void set_ends(IntervalNode self):
if self.cright is not EmptyNode and self.cleft is not EmptyNode:
self.maxend = dmax3(self.end, self.cright.maxend, self.cleft.maxend)
self.minend = dmin3(self.end, self.cright.minend, self.cleft.minend)
self.minstart = dmin3(self.start, self.cright.minstart, self.cleft.minstart)
elif self.cright is not EmptyNode:
self.maxend = dmax2(self.end, self.cright.maxend)
self.minend = dmin2(self.end, self.cright.minend)
self.minstart = dmin2(self.start, self.cright.minstart)
elif self.cleft is not EmptyNode:
self.maxend = dmax2(self.end, self.cleft.maxend)
self.minend = dmin2(self.end, self.cleft.minend)
self.minstart = dmin2(self.start, self.cleft.minstart)
def intersect( self, double start, double end, sort=True ):
"""
given a start and a end, return a list of features
falling within that range
"""
cdef list results = []
self._intersect( start, end, results )
if sort:
results = sorted(results)
return results
find = intersect
cdef void _intersect( IntervalNode self, double start, double end, list results):
# Left subtree
if self.cleft is not EmptyNode and self.cleft.maxend > start:
self.cleft._intersect( start, end, results )
# This interval
if ( self.end > start ) and ( self.start < end ):
results.append( self.interval )
# Right subtree
if self.cright is not EmptyNode and self.start < end:
self.cright._intersect( start, end, results )
cdef void _seek_left(IntervalNode self, double position, list results, int n, double max_dist):
# we know we can bail in these 2 cases.
if self.maxend + max_dist < position:
return
if self.minstart > position:
return
# the ordering of these 3 blocks makes it so the results are
# ordered nearest to farest from the query position
if self.cright is not EmptyNode:
self.cright._seek_left(position, results, n, max_dist)
if -1 < position - self.end < max_dist:
results.append(self.interval)
# TODO: can these conditionals be more stringent?
if self.cleft is not EmptyNode:
self.cleft._seek_left(position, results, n, max_dist)
cdef void _seek_right(IntervalNode self, double position, list results, int n, double max_dist):
# we know we can bail in these 2 cases.
if self.maxend < position: return
if self.minstart - max_dist > position: return
#print "SEEK_RIGHT:",self, self.cleft, self.maxend, self.minstart, position
# the ordering of these 3 blocks makes it so the results are
# ordered nearest to farest from the query position
if self.cleft is not EmptyNode:
self.cleft._seek_right(position, results, n, max_dist)
if -1 < self.start - position < max_dist:
results.append(self.interval)
if self.cright is not EmptyNode:
self.cright._seek_right(position, results, n, max_dist)
cpdef left(self, position, int n=1, double max_dist=2500):
"""
find n features with a start > than `position`
f: a Interval object (or anything with an `end` attribute)
n: the number of features to return
max_dist: the maximum distance to look before giving up.
"""
cdef list results = []
# use start - 1 becuase .left() assumes strictly left-of
self._seek_left( position - 1, results, n, max_dist )
if len(results) == n: return results
r = results
r.sort(key=operator.attrgetter('end'), reverse=True)
return r[:n]
cpdef right(self, position, int n=1, double max_dist=2500):
"""
find n features with a end < than position
f: a Interval object (or anything with a `start` attribute)
n: the number of features to return
max_dist: the maximum distance to look before giving up.
"""
cdef list results = []
# use end + 1 becuase .right() assumes strictly right-of
self._seek_right(position + 1, results, n, max_dist)
if len(results) == n: return results
r = results
r.sort(key=operator.attrgetter('start'))
return r[:n]
def traverse(self):
if self.cleft is not EmptyNode:
for node in self.cleft.traverse():
yield node
yield self.interval
if self.cright is not EmptyNode:
for node in self.cright.traverse():
yield node
cdef IntervalNode EmptyNode = IntervalNode( 0, 0, Interval(0, 0))
## ---- Wrappers that retain the old interface -------------------------------
cdef class Interval:
"""
Basic feature, with required integer start and end properties.
Also accepts optional strand as +1 or -1 (used for up/downstream queries),
a name, and any arbitrary data is sent in on the info keyword argument
>>> from bx.intervals.intersection import Interval
>>> f1 = Interval(23, 36)
>>> f2 = Interval(34, 48, value={'chr':12, 'anno':'transposon'})
>>> f2
Interval(34, 48, value={'anno': 'transposon', 'chr': 12})
"""
cdef public double start, end
cdef public object value, chrom, strand
def __init__(self, double start, double end, object value=None, object chrom=None, object strand=None ):
assert start <= end, "start must be less than end"
self.start = start
self.end = end
self.value = value
self.chrom = chrom
self.strand = strand
def __repr__(self):
fstr = "Interval(%g, %g" % (self.start, self.end)
if not self.value is None:
fstr += ", value=" + str(self.value)
fstr += ")"
return fstr
def __richcmp__(self, other, op):
if op == 0:
# <
return self.start < other.start or self.end < other.end
elif op == 1:
# <=
return self == other or self < other
elif op == 2:
# ==
return self.start == other.start and self.end == other.end
elif op == 3:
# !=
return self.start != other.start or self.end != other.end
elif op == 4:
# >
return self.start > other.start or self.end > other.end
elif op == 5:
# >=
return self == other or self > other
cdef class IntervalTree:
"""
Data structure for performing window intersect queries on a set of
of possibly overlapping 1d intervals.
Usage
=====
Create an empty IntervalTree
>>> from bx.intervals.intersection import Interval, IntervalTree
>>> intersecter = IntervalTree()
An interval is a start and end position and a value (possibly None).
You can add any object as an interval:
>>> intersecter.insert( 0, 10, "food" )
>>> intersecter.insert( 3, 7, dict(foo='bar') )
>>> intersecter.find( 2, 5 )
['food', {'foo': 'bar'}]
If the object has start and end attributes (like the Interval class) there
is are some shortcuts:
>>> intersecter = IntervalTree()
>>> intersecter.insert_interval( Interval( 0, 10 ) )
>>> intersecter.insert_interval( Interval( 3, 7 ) )
>>> intersecter.insert_interval( Interval( 3, 40 ) )
>>> intersecter.insert_interval( Interval( 13, 50 ) )
>>> intersecter.find( 30, 50 )
[Interval(3, 40), Interval(13, 50)]
>>> intersecter.find( 100, 200 )
[]
Before/after for intervals
>>> intersecter.before_interval( Interval( 10, 20 ) )
[Interval(3, 7)]
>>> intersecter.before_interval( Interval( 5, 20 ) )
[]
Upstream/downstream
>>> intersecter.upstream_of_interval(Interval(11, 12))
[Interval(0, 10)]
>>> intersecter.upstream_of_interval(Interval(11, 12, strand="-"))
[Interval(13, 50)]
>>> intersecter.upstream_of_interval(Interval(1, 2, strand="-"), num_intervals=3)
[Interval(3, 7), Interval(3, 40), Interval(13, 50)]
"""
cdef IntervalNode root
def __cinit__( self ):
root = None
# ---- Position based interfaces -----------------------------------------
def insert( self, double start, double end, object value=None ):
"""
Insert the interval [start,end) associated with value `value`.
"""
if self.root is None:
self.root = IntervalNode( start, end, value )
else:
self.root = self.root.insert( start, end, value )
add = insert
def find( self, start, end ):
"""
Return a sorted list of all intervals overlapping [start,end).
"""
if self.root is None:
return []
return self.root.find( start, end )
def before( self, position, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie before `position` and are no
further than `max_dist` positions away
"""
if self.root is None:
return []
return self.root.left( position, num_intervals, max_dist )
def after( self, position, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie after `position` and are no
further than `max_dist` positions away
"""
if self.root is None:
return []
return self.root.right( position, num_intervals, max_dist )
# ---- Interval-like object based interfaces -----------------------------
def insert_interval( self, interval ):
"""
Insert an "interval" like object (one with at least start and end
attributes)
"""
self.insert( interval.start, interval.end, interval )
add_interval = insert_interval
def before_interval( self, interval, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie completely before `interval`
and are no further than `max_dist` positions away
"""
if self.root is None:
return []
return self.root.left( interval.start, num_intervals, max_dist )
def after_interval( self, interval, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie completely after `interval` and
are no further than `max_dist` positions away
"""
if self.root is None:
return []
return self.root.right( interval.end, num_intervals, max_dist )
def upstream_of_interval( self, interval, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie completely upstream of
`interval` and are no further than `max_dist` positions away
"""
if self.root is None:
return []
if interval.strand == -1 or interval.strand == "-":
return self.root.right( interval.end, num_intervals, max_dist )
else:
return self.root.left( interval.start, num_intervals, max_dist )
def downstream_of_interval( self, interval, num_intervals=1, max_dist=2500 ):
"""
Find `num_intervals` intervals that lie completely downstream of
`interval` and are no further than `max_dist` positions away
"""
if self.root is None:
return []
if interval.strand == -1 or interval.strand == "-":
return self.root.left( interval.start, num_intervals, max_dist )
else:
return self.root.right( interval.end, num_intervals, max_dist )
def traverse(self):
"""
iterator that traverses the tree
"""
if self.root is None:
return iter([])
return self.root.traverse()
# For backward compatibility
Intersecter = IntervalTree

View File

@@ -1,152 +0,0 @@
"""Class for performing HTTP client requests via libcurl"""
from __future__ import absolute_import
from nilmdb.printf import *
import time
import sys
import re
import os
import simplejson as json
import nilmdb.httpclient
# Other functions expect to see these in the nilmdb.client namespace
from nilmdb.httpclient import ClientError, ServerError, Error
version = "1.0"
class Client(object):
"""Main client interface to the Nilm database."""
client_version = version
def __init__(self, url):
self.http = nilmdb.httpclient.HTTPClient(url)
def _json_param(self, data):
"""Return compact json-encoded version of parameter"""
return json.dumps(data, separators=(',',':'))
def close(self):
self.http.close()
def geturl(self):
"""Return the URL we're using"""
return self.http.baseurl
def version(self):
"""Return server version"""
return self.http.get("version")
def dbpath(self):
"""Return server database path"""
return self.http.get("dbpath")
def dbsize(self):
"""Return server database size as human readable string"""
return self.http.get("dbsize")
def stream_list(self, path = None, layout = None):
params = {}
if path is not None:
params["path"] = path
if layout is not None:
params["layout"] = layout
return self.http.get("stream/list", params)
def stream_get_metadata(self, path, keys = None):
params = { "path": path }
if keys is not None:
params["key"] = keys
return self.http.get("stream/get_metadata", params)
def stream_set_metadata(self, path, data):
"""Set stream metadata from a dictionary, replacing all existing
metadata."""
params = {
"path": path,
"data": self._json_param(data)
}
return self.http.get("stream/set_metadata", params)
def stream_update_metadata(self, path, data):
"""Update stream metadata from a dictionary"""
params = {
"path": path,
"data": self._json_param(data)
}
return self.http.get("stream/update_metadata", params)
def stream_create(self, path, layout):
"""Create a new stream"""
params = { "path": path,
"layout" : layout }
return self.http.get("stream/create", params)
def stream_insert(self, path, data):
"""Insert data into a stream. data should be a file-like object
that provides ASCII data that matches the database layout for path."""
params = { "path": path }
# See design.md for a discussion of how much data to send.
# These are soft limits -- actual data might be rounded up.
max_data = 1048576
max_time = 30
def sendit():
result = self.http.put("stream/insert", send_data, params)
params["old_timestamp"] = result[1]
return result
result = None
start = time.time()
send_data = ""
for line in data:
elapsed = time.time() - start
send_data += line
if (len(send_data) > max_data) or (elapsed > max_time):
result = sendit()
send_data = ""
start = time.time()
if len(send_data):
result = sendit()
# Return the most recent JSON result we got back, or None if
# we didn't make any requests.
return result
def stream_intervals(self, path, start = None, end = None):
"""
Return a generator that yields each stream interval.
"""
params = {
"path": path
}
if start is not None:
params["start"] = repr(start) # use repr to keep precision
if end is not None:
params["end"] = repr(end)
return self.http.get_gen("stream/intervals", params, retjson = True)
def stream_extract(self, path, start = None, end = None, count = False):
"""
Extract data from a stream. Returns a generator that yields
lines of ASCII-formatted data that matches the database
layout for the given path.
Specify count=True to just get a count of values rather than
the actual data.
"""
params = {
"path": path,
}
if start is not None:
params["start"] = repr(start) # use repr to keep precision
if end is not None:
params["end"] = repr(end)
if count:
params["count"] = 1
return self.http.get_gen("stream/extract", params, retjson = False)

View File

@@ -0,0 +1,4 @@
"""nilmdb.client"""
from nilmdb.client.client import Client
from nilmdb.client.errors import ClientError, ServerError, Error

470
nilmdb/client/client.py Normal file
View File

@@ -0,0 +1,470 @@
# -*- coding: utf-8 -*-
"""Class for performing HTTP client requests via libcurl"""
import nilmdb.utils
import nilmdb.client.httpclient
from nilmdb.client.errors import ClientError
import time
import simplejson as json
import contextlib
from nilmdb.utils.time import timestamp_to_string, string_to_timestamp
def extract_timestamp(line):
"""Extract just the timestamp from a line of data text"""
return string_to_timestamp(line.split()[0])
class Client(object):
"""Main client interface to the Nilm database."""
def __init__(self, url, post_json = False):
"""Initialize client with given URL. If post_json is true,
POST requests are sent with Content-Type 'application/json'
instead of the default 'x-www-form-urlencoded'."""
self.http = nilmdb.client.httpclient.HTTPClient(url, post_json)
self.post_json = post_json
# __enter__/__exit__ allow this class to be a context manager
def __enter__(self):
return self
def __exit__(self, exc_type, exc_value, traceback):
self.close()
def _json_post_param(self, data):
"""Return compact json-encoded version of parameter"""
if self.post_json:
# If we're posting as JSON, we don't need to encode it further here
return data
return json.dumps(data, separators=(',',':'))
def close(self):
"""Close the connection; safe to call multiple times"""
self.http.close()
def geturl(self):
"""Return the URL we're using"""
return self.http.baseurl
def version(self):
"""Return server version"""
return self.http.get("version")
def dbinfo(self):
"""Return server database info (path, size, free space)
as a dictionary."""
return self.http.get("dbinfo")
def stream_list(self, path = None, layout = None, extended = False):
"""Return a sorted list of [path, layout] lists. If 'path' or
'layout' are specified, only return streams that match those
exact values. If 'extended' is True, the returned lists have
extended info, e.g.: [path, layout, extent_min, extent_max,
total_rows, total_seconds."""
params = {}
if path is not None:
params["path"] = path
if layout is not None:
params["layout"] = layout
if extended:
params["extended"] = 1
streams = self.http.get("stream/list", params)
return nilmdb.utils.sort.sort_human(streams, key = lambda s: s[0])
def stream_get_metadata(self, path, keys = None):
"""Get stream metadata"""
params = { "path": path }
if keys is not None:
params["key"] = keys
return self.http.get("stream/get_metadata", params)
def stream_set_metadata(self, path, data):
"""Set stream metadata from a dictionary, replacing all existing
metadata."""
params = {
"path": path,
"data": self._json_post_param(data)
}
return self.http.post("stream/set_metadata", params)
def stream_update_metadata(self, path, data):
"""Update stream metadata from a dictionary"""
params = {
"path": path,
"data": self._json_post_param(data)
}
return self.http.post("stream/update_metadata", params)
def stream_create(self, path, layout):
"""Create a new stream"""
params = { "path": path,
"layout" : layout }
return self.http.post("stream/create", params)
def stream_destroy(self, path):
"""Delete stream. Fails if any data is still present."""
params = { "path": path }
return self.http.post("stream/destroy", params)
def stream_rename(self, oldpath, newpath):
"""Rename a stream."""
params = { "oldpath": oldpath,
"newpath": newpath }
return self.http.post("stream/rename", params)
def stream_remove(self, path, start = None, end = None):
"""Remove data from the specified time range"""
params = {
"path": path
}
if start is not None:
params["start"] = timestamp_to_string(start)
if end is not None:
params["end"] = timestamp_to_string(end)
total = 0
for count in self.http.post_gen("stream/remove", params):
total += int(count)
return total
@contextlib.contextmanager
def stream_insert_context(self, path, start = None, end = None):
"""Return a context manager that allows data to be efficiently
inserted into a stream in a piecewise manner. Data is
provided as ASCII lines, and is aggregated and sent to the
server in larger or smaller chunks as necessary. Data lines
must match the database layout for the given path, and end
with a newline.
Example:
with client.stream_insert_context('/path', start, end) as ctx:
ctx.insert('1234567890.0 1 2 3 4\\n')
ctx.insert('1234567891.0 1 2 3 4\\n')
For more details, see help for nilmdb.client.client.StreamInserter
This may make multiple requests to the server, if the data is
large enough or enough time has passed between insertions.
"""
ctx = StreamInserter(self, path, start, end)
yield ctx
ctx.finalize()
ctx.destroy()
def stream_insert(self, path, data, start = None, end = None):
"""Insert rows of data into a stream. data should be a string
or iterable that provides ASCII data that matches the database
layout for path. Data is passed through stream_insert_context,
so it will be broken into reasonably-sized chunks and
start/end will be deduced if missing."""
with self.stream_insert_context(path, start, end) as ctx:
if isinstance(data, basestring):
ctx.insert(data)
else:
for chunk in data:
ctx.insert(chunk)
return ctx.last_response
def stream_insert_block(self, path, data, start, end, binary = False):
"""Insert a single fixed block of data into the stream. It is
sent directly to the server in one block with no further
processing.
If 'binary' is True, provide raw binary data in little-endian
format matching the path layout, including an int64 timestamp.
Otherwise, provide ASCII data matching the layout."""
params = {
"path": path,
"start": timestamp_to_string(start),
"end": timestamp_to_string(end),
}
if binary:
params["binary"] = 1
return self.http.put("stream/insert", data, params, binary = binary)
def stream_intervals(self, path, start = None, end = None, diffpath = None):
"""
Return a generator that yields each stream interval.
If 'diffpath' is not None, yields only interval ranges that are
present in 'path' but not in 'diffpath'.
"""
params = {
"path": path
}
if diffpath is not None:
params["diffpath"] = diffpath
if start is not None:
params["start"] = timestamp_to_string(start)
if end is not None:
params["end"] = timestamp_to_string(end)
return self.http.get_gen("stream/intervals", params)
def stream_extract(self, path, start = None, end = None,
count = False, markup = False, binary = False):
"""
Extract data from a stream. Returns a generator that yields
lines of ASCII-formatted data that matches the database
layout for the given path.
If 'count' is True, return a count of matching data points
rather than the actual data. The output format is unchanged.
If 'markup' is True, include comments in the returned data
that indicate interval starts and ends.
If 'binary' is True, return chunks of raw binary data, rather
than lines of ASCII-formatted data. Raw binary data is
little-endian and matches the database types (including an
int64 timestamp).
"""
params = {
"path": path,
}
if start is not None:
params["start"] = timestamp_to_string(start)
if end is not None:
params["end"] = timestamp_to_string(end)
if count:
params["count"] = 1
if markup:
params["markup"] = 1
if binary:
params["binary"] = 1
return self.http.get_gen("stream/extract", params, binary = binary)
def stream_count(self, path, start = None, end = None):
"""
Return the number of rows of data in the stream that satisfy
the given timestamps.
"""
counts = list(self.stream_extract(path, start, end, count = True))
return int(counts[0])
class StreamInserter(object):
"""Object returned by stream_insert_context() that manages
the insertion of rows of data into a particular path.
The basic data flow is that we are filling a contiguous interval
on the server, with no gaps, that extends from timestamp 'start'
to timestamp 'end'. Data timestamps satisfy 'start <= t < end'.
Data is provided to .insert() as ASCII formatted data separated by
newlines. The chunks of data passed to .insert() do not need to
match up with the newlines; less or more than one line can be passed.
1. The first inserted line begins a new interval that starts at
'start'. If 'start' is not given, it is deduced from the first
line's timestamp.
2. Subsequent lines go into the same contiguous interval. As lines
are inserted, this routine may make multiple insertion requests to
the server, but will structure the timestamps to leave no gaps.
3. The current contiguous interval can be completed by manually
calling .finalize(), which the context manager will also do
automatically. This will send any remaining data to the server,
using the 'end' timestamp to end the interval. If no 'end'
was provided, it is deduced from the last timestamp seen,
plus a small delta.
After a .finalize(), inserting new data goes back to step 1.
.update_start() can be called before step 1 to change the start
time for the interval. .update_end() can be called before step 3
to change the end time for the interval.
"""
# See design.md for a discussion of how much data to send. This
# is a soft limit -- we might send up to twice as much or so
_max_data = 2 * 1024 * 1024
_max_data_after_send = 64 * 1024
def __init__(self, client, path, start, end):
"""'client' is the client object. 'path' is the database
path to insert to. 'start' and 'end' are used for the first
contiguous interval and may be None."""
self.last_response = None
self._client = client
self._path = path
# Start and end for the overall contiguous interval we're
# filling
self._interval_start = start
self._interval_end = end
# Current data we're building up to send. Each string
# goes into the array, and gets joined all at once.
self._block_data = []
self._block_len = 0
self.destroyed = False
def destroy(self):
"""Ensure this object can't be used again without raising
an error"""
def error(*args, **kwargs):
raise Exception("don't reuse this context object")
self._send_block = self.insert = self.finalize = self.send = error
def insert(self, data):
"""Insert a chunk of ASCII formatted data in string form. The
overall data must consist of lines terminated by '\\n'."""
length = len(data)
maxdata = self._max_data
if length > maxdata:
# This could make our buffer more than twice what we
# wanted to send, so split it up. This is a bit
# inefficient, but the user really shouldn't be providing
# this much data at once.
for cut in range(0, length, maxdata):
self.insert(data[cut:(cut + maxdata)])
return
# Append this string to our list
self._block_data.append(data)
self._block_len += length
# Send the block once we have enough data
if self._block_len >= maxdata:
self._send_block(final = False)
if self._block_len >= self._max_data_after_send: # pragma: no cover
raise ValueError("too much data left over after trying"
" to send intermediate block; is it"
" missing newlines or malformed?")
def update_start(self, start):
"""Update the start time for the next contiguous interval.
Call this before starting to insert data for a new interval,
for example, after .finalize()"""
self._interval_start = start
def update_end(self, end):
"""Update the end time for the current contiguous interval.
Call this before .finalize()"""
self._interval_end = end
def finalize(self):
"""Stop filling the current contiguous interval.
All outstanding data will be sent, and the interval end
time of the interval will be taken from the 'end' argument
used when initializing this class, or the most recent
value passed to update_end(), or the last timestamp plus
a small epsilon value if no other endpoint was provided.
If more data is inserted after a finalize(), it will become
part of a new interval and there may be a gap left in-between."""
self._send_block(final = True)
def send(self):
"""Send any data that we might have buffered up. Does not affect
any other treatment of timestamps or endpoints."""
self._send_block(final = False)
def _get_first_noncomment(self, block):
"""Return the (start, end) indices of the first full line in
block that isn't a comment, or raise IndexError if
there isn't one."""
start = 0
while True:
end = block.find('\n', start)
if end < 0:
raise IndexError
if block[start] != '#':
return (start, (end + 1))
start = end + 1
def _get_last_noncomment(self, block):
"""Return the (start, end) indices of the last full line in
block[:length] that isn't a comment, or raise IndexError if
there isn't one."""
end = block.rfind('\n')
if end <= 0:
raise IndexError
while True:
start = block.rfind('\n', 0, end)
if block[start + 1] != '#':
return ((start + 1), end)
if start == -1:
raise IndexError
end = start
def _send_block(self, final = False):
"""Send data currently in the block. The data sent will
consist of full lines only, so some might be left over."""
# Build the full string to send
block = "".join(self._block_data)
start_ts = self._interval_start
if start_ts is None:
# Pull start from the first line
try:
(spos, epos) = self._get_first_noncomment(block)
start_ts = extract_timestamp(block[spos:epos])
except (ValueError, IndexError):
pass # no timestamp is OK, if we have no data
if final:
# For a final block, it must end in a newline, and the
# ending timestamp is either the user-provided end,
# or the timestamp of the last line plus epsilon.
end_ts = self._interval_end
try:
if block[-1] != '\n':
raise ValueError("final block didn't end with a newline")
if end_ts is None:
(spos, epos) = self._get_last_noncomment(block)
end_ts = extract_timestamp(block[spos:epos])
end_ts += nilmdb.utils.time.epsilon
except (ValueError, IndexError):
pass # no timestamp is OK, if we have no data
self._block_data = []
self._block_len = 0
# Next block is completely fresh
self._interval_start = None
self._interval_end = None
else:
# An intermediate block, e.g. "line1\nline2\nline3\nline4"
# We need to save "line3\nline4" for the next block, and
# use the timestamp from "line3" as the ending timestamp
# for this one.
try:
(spos, epos) = self._get_last_noncomment(block)
end_ts = extract_timestamp(block[spos:epos])
except (ValueError, IndexError):
# If we found no timestamp, give up; we could send this
# block later when we have more data.
return
if spos == 0:
# Not enough data to send an intermediate block
return
if self._interval_end is not None and end_ts > self._interval_end:
# User gave us bad endpoints; send it anyway, and let
# the server complain so that the error is the same
# as if we hadn't done this chunking.
end_ts = self._interval_end
self._block_data = [ block[spos:] ]
self._block_len = (epos - spos)
block = block[:spos]
# Next block continues where this one ended
self._interval_start = end_ts
# Double check endpoints
if (start_ts is None or end_ts is None) or (start_ts == end_ts):
# If the block has no non-comment lines, it's OK
try:
self._get_first_noncomment(block)
except IndexError:
return
raise ClientError("have data to send, but no start/end times")
# Send it
self.last_response = self._client.stream_insert_block(
self._path, block, start_ts, end_ts, binary = False)
return

33
nilmdb/client/errors.py Normal file
View File

@@ -0,0 +1,33 @@
"""HTTP client errors"""
from nilmdb.utils.printf import *
class Error(Exception):
"""Base exception for both ClientError and ServerError responses"""
def __init__(self,
status = "Unspecified error",
message = None,
url = None,
traceback = None):
Exception.__init__(self, status)
self.status = status # e.g. "400 Bad Request"
self.message = message # textual message from the server
self.url = url # URL we were requesting
self.traceback = traceback # server traceback, if available
def _format_error(self, show_url):
s = sprintf("[%s]", self.status)
if self.message:
s += sprintf(" %s", self.message)
if show_url and self.url: # pragma: no cover
s += sprintf(" (%s)", self.url)
if self.traceback: # pragma: no cover
s += sprintf("\nServer traceback:\n%s", self.traceback)
return s
def __str__(self):
return self._format_error(show_url = False)
def __repr__(self): # pragma: no cover
return self._format_error(show_url = True)
class ClientError(Error):
pass
class ServerError(Error):
pass

172
nilmdb/client/httpclient.py Normal file
View File

@@ -0,0 +1,172 @@
"""HTTP client library"""
import nilmdb.utils
from nilmdb.client.errors import ClientError, ServerError, Error
import simplejson as json
import urlparse
import requests
class HTTPClient(object):
"""Class to manage and perform HTTP requests from the client"""
def __init__(self, baseurl = "", post_json = False):
"""If baseurl is supplied, all other functions that take
a URL can be given a relative URL instead."""
# Verify / clean up URL
reparsed = urlparse.urlparse(baseurl).geturl()
if '://' not in reparsed:
reparsed = urlparse.urlparse("http://" + baseurl).geturl()
self.baseurl = reparsed.rstrip('/') + '/'
# Build Requests session object, enable SSL verification
self.session = requests.Session()
self.session.verify = True
# Saved response, so that tests can verify a few things.
self._last_response = {}
# Whether to send application/json POST bodies (versus
# x-www-form-urlencoded)
self.post_json = post_json
def _handle_error(self, url, code, body):
# Default variables for exception. We use the entire body as
# the default message, in case we can't extract it from a JSON
# response.
args = { "url" : url,
"status" : str(code),
"message" : body,
"traceback" : None }
try:
# Fill with server-provided data if we can
jsonerror = json.loads(body)
args["status"] = jsonerror["status"]
args["message"] = jsonerror["message"]
args["traceback"] = jsonerror["traceback"]
except Exception: # pragma: no cover
pass
if code >= 400 and code <= 499:
raise ClientError(**args)
else: # pragma: no cover
if code >= 500 and code <= 599:
if args["message"] is None:
args["message"] = ("(no message; try disabling " +
"response.stream option in " +
"nilmdb.server for better debugging)")
raise ServerError(**args)
else:
raise Error(**args)
def close(self):
self.session.close()
def _do_req(self, method, url, query_data, body_data, stream, headers):
url = urlparse.urljoin(self.baseurl, url)
try:
response = self.session.request(method, url,
params = query_data,
data = body_data,
stream = stream,
headers = headers)
except requests.RequestException as e:
raise ServerError(status = "502 Error", url = url,
message = str(e.message))
if response.status_code != 200:
self._handle_error(url, response.status_code, response.content)
self._last_response = response
if response.headers["content-type"] in ("application/json",
"application/x-json-stream"):
return (response, True)
else:
return (response, False)
# Normal versions that return data directly
def _req(self, method, url, query = None, body = None, headers = None):
"""
Make a request and return the body data as a string or parsed
JSON object, or raise an error if it contained an error.
"""
(response, isjson) = self._do_req(method, url, query, body,
stream = False, headers = headers)
if isjson:
return json.loads(response.content)
return response.content
def get(self, url, params = None):
"""Simple GET (parameters in URL)"""
return self._req("GET", url, params, None)
def post(self, url, params = None):
"""Simple POST (parameters in body)"""
if self.post_json:
return self._req("POST", url, None,
json.dumps(params),
{ 'Content-type': 'application/json' })
else:
return self._req("POST", url, None, params)
def put(self, url, data, params = None, binary = False):
"""Simple PUT (parameters in URL, data in body)"""
if binary:
h = { 'Content-type': 'application/octet-stream' }
else:
h = { 'Content-type': 'text/plain; charset=utf-8' }
return self._req("PUT", url, query = params, body = data, headers = h)
# Generator versions that return data one line at a time.
def _req_gen(self, method, url, query = None, body = None,
headers = None, binary = False):
"""
Make a request and return a generator that gives back strings
or JSON decoded lines of the body data, or raise an error if
it contained an eror.
"""
(response, isjson) = self._do_req(method, url, query, body,
stream = True, headers = headers)
# Like the iter_lines function in Requests, but only splits on
# the specified line ending.
def lines(source, ending):
pending = None
for chunk in source:
if pending is not None:
chunk = pending + chunk
tmp = chunk.split(ending)
lines = tmp[:-1]
if chunk.endswith(ending):
pending = None
else:
pending = tmp[-1]
for line in lines:
yield line
if pending is not None: # pragma: no cover (missing newline)
yield pending
# Yield the chunks or lines as requested
if binary:
for chunk in response.iter_content(chunk_size = 65536):
yield chunk
elif isjson:
for line in lines(response.iter_content(chunk_size = 1),
ending = '\r\n'):
yield json.loads(line)
else:
for line in lines(response.iter_content(chunk_size = 65536),
ending = '\n'):
yield line
def get_gen(self, url, params = None, binary = False):
"""Simple GET (parameters in URL) returning a generator"""
return self._req_gen("GET", url, params, binary = binary)
def post_gen(self, url, params = None):
"""Simple POST (parameters in body) returning a generator"""
if self.post_json:
return self._req_gen("POST", url, None,
json.dumps(params),
{ 'Content-type': 'application/json' })
else:
return self._req_gen("POST", url, None, params)
# Not much use for a POST or PUT generator, since they don't
# return much data.

View File

@@ -0,0 +1,258 @@
# -*- coding: utf-8 -*-
"""Provide a NumpyClient class that is based on normal Client, but has
additional methods for extracting and inserting data via Numpy arrays."""
import nilmdb.utils
import nilmdb.client.client
import nilmdb.client.httpclient
from nilmdb.client.errors import ClientError
import contextlib
from nilmdb.utils.time import timestamp_to_string, string_to_timestamp
import numpy
import cStringIO
def layout_to_dtype(layout):
ltype = layout.split('_')[0]
lcount = int(layout.split('_')[1])
if ltype.startswith('int'):
atype = '<i' + str(int(ltype[3:]) / 8)
elif ltype.startswith('uint'):
atype = '<u' + str(int(ltype[4:]) / 8)
elif ltype.startswith('float'):
atype = '<f' + str(int(ltype[5:]) / 8)
else:
raise ValueError("bad layout")
return numpy.dtype([('timestamp', '<i8'), ('data', atype, lcount)])
class NumpyClient(nilmdb.client.client.Client):
"""Subclass of nilmdb.client.Client that adds additional methods for
extracting and inserting data via Numpy arrays."""
def _get_dtype(self, path, layout):
if layout is None:
streams = self.stream_list(path)
if len(streams) != 1:
raise ClientError("can't get layout for path: " + path)
layout = streams[0][1]
return layout_to_dtype(layout)
def stream_extract_numpy(self, path, start = None, end = None,
layout = None, maxrows = 100000,
structured = False):
"""
Extract data from a stream. Returns a generator that yields
Numpy arrays of up to 'maxrows' of data each.
If 'layout' is None, it is read using stream_info.
If 'structured' is False, all data is converted to float64
and returned in a flat 2D array. Otherwise, data is returned
as a structured dtype in a 1D array.
"""
dtype = self._get_dtype(path, layout)
def to_numpy(data):
a = numpy.fromstring(data, dtype)
if structured:
return a
return numpy.c_[a['timestamp'], a['data']]
chunks = []
total_len = 0
maxsize = dtype.itemsize * maxrows
for data in self.stream_extract(path, start, end, binary = True):
# Add this block of binary data
chunks.append(data)
total_len += len(data)
# See if we have enough to make the requested Numpy array
while total_len >= maxsize:
assembled = "".join(chunks)
total_len -= maxsize
chunks = [ assembled[maxsize:] ]
block = assembled[:maxsize]
yield to_numpy(block)
if total_len:
yield to_numpy("".join(chunks))
@contextlib.contextmanager
def stream_insert_numpy_context(self, path, start = None, end = None,
layout = None):
"""Return a context manager that allows data to be efficiently
inserted into a stream in a piecewise manner. Data is
provided as Numpy arrays, and is aggregated and sent to the
server in larger or smaller chunks as necessary. Data format
must match the database layout for the given path.
For more details, see help for
nilmdb.client.numpyclient.StreamInserterNumpy
If 'layout' is not None, use it as the layout rather than
querying the database.
"""
dtype = self._get_dtype(path, layout)
ctx = StreamInserterNumpy(self, path, start, end, dtype)
yield ctx
ctx.finalize()
ctx.destroy()
def stream_insert_numpy(self, path, data, start = None, end = None,
layout = None):
"""Insert data into a stream. data should be a Numpy array
which will be passed through stream_insert_numpy_context to
break it into chunks etc. See the help for that function
for details."""
with self.stream_insert_numpy_context(path, start, end, layout) as ctx:
if isinstance(data, numpy.ndarray):
ctx.insert(data)
else:
for chunk in data:
ctx.insert(chunk)
return ctx.last_response
class StreamInserterNumpy(nilmdb.client.client.StreamInserter):
"""Object returned by stream_insert_numpy_context() that manages
the insertion of rows of data into a particular path.
See help for nilmdb.client.client.StreamInserter for details.
The only difference is that, instead of ASCII formatted data,
this context manager can take Numpy arrays, which are either
structured (1D with complex dtype) or flat (2D with simple dtype).
"""
# Soft limit of how many bytes to send per HTTP request.
_max_data = 2 * 1024 * 1024
def __init__(self, client, path, start, end, dtype):
"""
'client' is the client object. 'path' is the database path
to insert to. 'start' and 'end' are used for the first
contiguous interval and may be None. 'dtype' is the Numpy
dtype for this stream.
"""
super(StreamInserterNumpy, self).__init__(client, path, start, end)
self._dtype = dtype
# Max rows to send at once
self._max_rows = self._max_data // self._dtype.itemsize
# List of the current arrays we're building up to send
self._block_arrays = []
self._block_rows = 0
def insert(self, array):
"""Insert Numpy data, which must match the layout type."""
if type(array) != numpy.ndarray:
array = numpy.array(array)
if array.ndim == 1:
# Already a structured array; just verify the type
if array.dtype != self._dtype:
raise ValueError("wrong dtype for 1D (structured) array")
elif array.ndim == 2:
# Convert to structured array
sarray = numpy.zeros(array.shape[0], dtype=self._dtype)
try:
sarray['timestamp'] = array[:,0]
# Need the squeeze in case sarray['data'] is 1 dimensional
sarray['data'] = numpy.squeeze(array[:,1:])
except (IndexError, ValueError):
raise ValueError("wrong number of fields for this data type")
array = sarray
else:
raise ValueError("wrong number of dimensions in array")
length = len(array)
maxrows = self._max_rows
if length == 0:
return
if length > maxrows:
# This is more than twice what we wanted to send, so split
# it up. This is a bit inefficient, but the user really
# shouldn't be providing this much data at once.
for cut in range(0, length, maxrows):
self.insert(array[cut:(cut + maxrows)])
return
# Add this array to our list
self._block_arrays.append(array)
self._block_rows += length
# Send if it's too long
if self._block_rows >= maxrows:
self._send_block(final = False)
def _send_block(self, final = False):
"""Send the data current stored up. One row might be left
over if we need its timestamp saved."""
# Build the full array to send
if self._block_rows == 0:
array = numpy.zeros(0, dtype = self._dtype)
else:
array = numpy.hstack(self._block_arrays)
# Get starting timestamp
start_ts = self._interval_start
if start_ts is None:
# Pull start from the first row
try:
start_ts = array['timestamp'][0]
except IndexError:
pass # no timestamp is OK, if we have no data
# Get ending timestamp
if final:
# For a final block, the timestamp is either the
# user-provided end, or the timestamp of the last line
# plus epsilon.
end_ts = self._interval_end
if end_ts is None:
try:
end_ts = array['timestamp'][-1]
end_ts += nilmdb.utils.time.epsilon
except IndexError:
pass # no timestamp is OK, if we have no data
self._block_arrays = []
self._block_rows = 0
# Next block is completely fresh
self._interval_start = None
self._interval_end = None
else:
# An intermediate block. We need to save the last row
# for the next block, and use its timestamp as the ending
# timestamp for this one.
if len(array) < 2:
# Not enough data to send an intermediate block
return
end_ts = array['timestamp'][-1]
if self._interval_end is not None and end_ts > self._interval_end:
# User gave us bad endpoints; send it anyway, and let
# the server complain so that the error is the same
# as if we hadn't done this chunking.
end_ts = self._interval_end
self._block_arrays = [ array[-1:] ]
self._block_rows = 1
array = array[:-1]
# Next block continues where this one ended
self._interval_start = end_ts
# If we have no endpoints, or equal endpoints, it's OK as long
# as there's no data to send
if (start_ts is None or end_ts is None) or (start_ts == end_ts):
if len(array) == 0:
return
raise ClientError("have data to send, but invalid start/end times")
# Send it
data = array.tostring()
self.last_response = self._client.stream_insert_block(
self._path, data, start_ts, end_ts, binary = True)
return

View File

@@ -1 +1,3 @@
from .cmdline import Cmdline
"""nilmdb.cmdline"""
from nilmdb.cmdline.cmdline import Cmdline

View File

@@ -1,142 +1,182 @@
"""Command line client functionality"""
from __future__ import absolute_import
from nilmdb.printf import *
import nilmdb.client
import datetime_tz
import dateutil.parser
from nilmdb.utils.printf import *
from nilmdb.utils import datetime_tz
import nilmdb.utils.time
import sys
import re
import os
import argparse
from argparse import ArgumentDefaultsHelpFormatter as def_form
import signal
version = "0.1"
try: # pragma: no cover
import argcomplete
except ImportError: # pragma: no cover
argcomplete = None
# Valid subcommands. Defined in separate files just to break
# things up -- they're still called with Cmdline as self.
subcommands = [ "info", "create", "list", "metadata", "insert", "extract" ]
subcommands = [ "help", "info", "create", "list", "metadata",
"insert", "extract", "remove", "destroy",
"intervals", "rename" ]
# Import the subcommand modules. Equivalent way of doing this would be
# from . import info as cmd_info
# Import the subcommand modules
subcmd_mods = {}
for cmd in subcommands:
subcmd_mods[cmd] = __import__("nilmdb.cmdline." + cmd, fromlist = [ cmd ])
class JimArgumentParser(argparse.ArgumentParser):
def parse_args(self, args=None, namespace=None):
# Look for --version anywhere and change it to just "nilmtool
# --version". This makes "nilmtool cmd --version" work, which
# is needed by help2man.
if "--version" in (args or sys.argv[1:]):
args = [ "--version" ]
return argparse.ArgumentParser.parse_args(self, args, namespace)
def error(self, message):
self.print_usage(sys.stderr)
self.exit(2, sprintf("error: %s\n", message))
class Complete(object): # pragma: no cover
# Completion helpers, for using argcomplete (see
# extras/nilmtool-bash-completion.sh)
def escape(self, s):
quote_chars = [ "\\", "\"", "'", " " ]
for char in quote_chars:
s = s.replace(char, "\\" + char)
return s
def none(self, prefix, parsed_args, **kwargs):
return []
rate = none
time = none
url = none
def path(self, prefix, parsed_args, **kwargs):
client = nilmdb.client.Client(parsed_args.url)
return ( self.escape(s[0])
for s in client.stream_list()
if s[0].startswith(prefix) )
def layout(self, prefix, parsed_args, **kwargs):
types = [ "int8", "int16", "int32", "int64",
"uint8", "uint16", "uint32", "uint64",
"float32", "float64" ]
layouts = []
for i in range(1,10):
layouts.extend([(t + "_" + str(i)) for t in types])
return ( l for l in layouts if l.startswith(prefix) )
def meta_key(self, prefix, parsed_args, **kwargs):
return (kv.split('=')[0] for kv
in self.meta_keyval(prefix, parsed_args, **kwargs))
def meta_keyval(self, prefix, parsed_args, **kwargs):
client = nilmdb.client.Client(parsed_args.url)
path = parsed_args.path
if not path:
return []
results = []
# prefix comes in as UTF-8, but results need to be Unicode,
# weird. Still doesn't work in all cases, but that's bugs in
# argcomplete.
prefix = nilmdb.utils.unicode.decode(prefix)
for (k,v) in client.stream_get_metadata(path).iteritems():
kv = self.escape(k + '=' + v)
if kv.startswith(prefix):
results.append(kv)
return results
class Cmdline(object):
def __init__(self, argv):
self.argv = argv
def __init__(self, argv = None):
self.argv = argv or sys.argv[1:]
try:
# Assume command line arguments are encoded with stdin's encoding,
# and reverse it. Won't be needed in Python 3, but for now..
self.argv = [ x.decode(sys.stdin.encoding) for x in self.argv ]
except Exception: # pragma: no cover
pass
self.client = None
self.def_url = os.environ.get("NILMDB_URL", "http://localhost/nilmdb/")
self.subcmd = {}
self.complete = Complete()
def arg_time(self, toparse):
"""Parse a time string argument"""
try:
return self.parse_time(toparse).totimestamp()
return nilmdb.utils.time.parse_time(toparse)
except ValueError as e:
raise argparse.ArgumentTypeError(sprintf("%s \"%s\"",
str(e), toparse))
def parse_time(self, toparse):
"""
Parse a free-form time string and return a datetime_tz object.
If the string doesn't contain a timestamp, the current local
timezone is assumed (e.g. from the TZ env var).
"""
# If string doesn't contain at least 6 digits, consider it
# invalid. smartparse might otherwise accept empty strings
# and strings with just separators.
if len(re.findall(r"\d", toparse)) < 6:
raise ValueError("not enough digits for a timestamp")
# Try to just parse the time as given
try:
return datetime_tz.datetime_tz.smartparse(toparse)
except ValueError:
pass
# Try to extract a substring in a condensed format that we expect
# to see in a filename or header comment
res = re.search(r"(^|[^\d])(" # non-numeric or SOL
r"(199\d|2\d\d\d)" # year
r"[-/]?" # separator
r"(0[1-9]|1[012])" # month
r"[-/]?" # separator
r"([012]\d|3[01])" # day
r"[-T ]?" # separator
r"([01]\d|2[0-3])" # hour
r"[:]?" # separator
r"([0-5]\d)" # minute
r"[:]?" # separator
r"([0-5]\d)?" # second
r"([-+]\d\d\d\d)?" # timezone
r")", toparse)
if res is not None:
try:
return datetime_tz.datetime_tz.smartparse(res.group(2))
except ValueError:
pass
# Could also try to successively parse substrings, but let's
# just give up for now.
raise ValueError("unable to parse timestamp")
def time_string(self, timestamp):
"""
Convert a Unix timestamp to a string for printing, using the
local timezone for display (e.g. from the TZ env var).
"""
dt = datetime_tz.datetime_tz.fromtimestamp(timestamp)
return dt.strftime("%a, %d %b %Y %H:%M:%S.%f %z")
# Set up the parser
def parser_setup(self):
version_string = sprintf("nilmtool %s, client library %s",
version, nilmdb.Client.client_version)
self.parser = argparse.ArgumentParser(add_help = False,
formatter_class = def_form)
self.parser = JimArgumentParser(add_help = False,
formatter_class = def_form)
group = self.parser.add_argument_group("General options")
group.add_argument("-h", "--help", action='help',
help='show this help message and exit')
group.add_argument("-V", "--version", action="version",
version=version_string)
version = nilmdb.__version__)
group = self.parser.add_argument_group("Server")
group.add_argument("-u", "--url", action="store",
default="http://localhost:12380/",
help="NilmDB server URL (default: %(default)s)")
default=self.def_url,
help="NilmDB server URL (default: %(default)s)"
).completer = self.complete.url
sub = self.parser.add_subparsers(title="Commands",
dest="command",
description="Specify --help after "
"the command for command-specific "
"options.")
sub = self.parser.add_subparsers(
title="Commands", dest="command",
description="Use 'help command' or 'command --help' for more "
"details on a particular command.")
# Set up subcommands (defined in separate files)
for cmd in subcommands:
subcmd_mods[cmd].setup(self, sub)
self.subcmd[cmd] = subcmd_mods[cmd].setup(self, sub)
def die(self, formatstr, *args):
fprintf(sys.stderr, formatstr + "\n", *args)
self.client.close()
if self.client:
self.client.close()
sys.exit(-1)
def run(self):
# Set SIGPIPE to its default handler -- we don't need Python
# to catch it for us.
try:
signal.signal(signal.SIGPIPE, signal.SIG_DFL)
except ValueError: # pragma: no cover
pass
# Clear cached timezone, so that we can pick up timezone changes
# while running this from the test suite.
datetime_tz._localtz = None
# Run parser
self.parser_setup()
if argcomplete: # pragma: no cover
argcomplete.autocomplete(self.parser)
self.args = self.parser.parse_args(self.argv)
self.client = nilmdb.Client(self.args.url)
# Run arg verify handler if there is one
if "verify" in self.args:
self.args.verify(self)
# Make a test connection to make sure things work
try:
server_version = self.client.version()
except nilmdb.client.Error as e:
self.die("Error connecting to server: %s", str(e))
self.client = nilmdb.client.Client(self.args.url)
# Make a test connection to make sure things work,
# unless the particular command requests that we don't.
if "no_test_connect" not in self.args:
try:
server_version = self.client.version()
except nilmdb.client.Error as e:
self.die("error connecting to server: %s", str(e))
# Now dispatch client request to appropriate function. Parser
# should have ensured that we don't have any unknown commands

View File

@@ -1,27 +1,37 @@
from __future__ import absolute_import
from nilmdb.printf import *
from nilmdb.utils.printf import *
import nilmdb.client
from argparse import ArgumentDefaultsHelpFormatter as def_form
from argparse import RawDescriptionHelpFormatter as raw_form
def setup(self, sub):
cmd = sub.add_parser("create", help="Create a new stream",
formatter_class = def_form,
formatter_class = raw_form,
description="""
Create a new empty stream at the
specified path and with the specifed
layout type.
""")
Create a new empty stream at the specified path and with the specified
layout type.
Layout types are of the format: type_count
'type' is a data type like 'float32', 'float64', 'uint16', 'int32', etc.
'count' is the number of columns of this type.
For example, 'float32_8' means the data for this stream has 8 columns of
32-bit floating point values.
""")
cmd.set_defaults(handler = cmd_create)
group = cmd.add_argument_group("Required arguments")
group.add_argument("path",
help="Path (in database) of new stream, e.g. /foo/bar")
help="Path (in database) of new stream, e.g. /foo/bar",
).completer = self.complete.path
group.add_argument("layout",
help="Layout type for new stream, e.g. float32_8")
help="Layout type for new stream, e.g. float32_8",
).completer = self.complete.layout
return cmd
def cmd_create(self):
"""Create new stream"""
try:
self.client.stream_create(self.args.path, self.args.layout)
except nilmdb.client.ClientError as e:
self.die("Error creating stream: %s", str(e))
self.die("error creating stream: %s", str(e))

49
nilmdb/cmdline/destroy.py Normal file
View File

@@ -0,0 +1,49 @@
from nilmdb.utils.printf import *
import nilmdb.client
import fnmatch
from argparse import ArgumentDefaultsHelpFormatter as def_form
def setup(self, sub):
cmd = sub.add_parser("destroy", help="Delete a stream and all data",
formatter_class = def_form,
description="""
Destroy the stream at the specified path.
The stream must be empty. All metadata
related to the stream is permanently deleted.
Wildcards and multiple paths are supported.
""")
cmd.set_defaults(handler = cmd_destroy)
group = cmd.add_argument_group("Options")
group.add_argument("-R", "--remove", action="store_true",
help="Remove all data before destroying stream")
group.add_argument("-q", "--quiet", action="store_true",
help="Don't display names when destroying "
"multiple paths")
group = cmd.add_argument_group("Required arguments")
group.add_argument("path", nargs='+',
help="Path of the stream to delete, e.g. /foo/bar/*",
).completer = self.complete.path
return cmd
def cmd_destroy(self):
"""Destroy stream"""
streams = [ s[0] for s in self.client.stream_list() ]
paths = []
for path in self.args.path:
new = fnmatch.filter(streams, path)
if not new:
self.die("error: no stream matched path: %s", path)
paths.extend(new)
for path in paths:
if not self.args.quiet and len(paths) > 1:
printf("Destroying %s\n", path)
try:
if self.args.remove:
count = self.client.stream_remove(path)
self.client.stream_destroy(path)
except nilmdb.client.ClientError as e:
self.die("error destroying stream: %s", str(e))

View File

@@ -1,7 +1,6 @@
from __future__ import absolute_import
from nilmdb.printf import *
from __future__ import print_function
from nilmdb.utils.printf import *
import nilmdb.client
import nilmdb.layout
import sys
def setup(self, sub):
@@ -9,49 +8,83 @@ def setup(self, sub):
description="""
Extract data from a stream.
""")
cmd.set_defaults(handler = cmd_extract)
cmd.set_defaults(verify = cmd_extract_verify,
handler = cmd_extract)
group = cmd.add_argument_group("Data selection")
group.add_argument("path",
help="Path of stream, e.g. /foo/bar")
help="Path of stream, e.g. /foo/bar",
).completer = self.complete.path
group.add_argument("-s", "--start", required=True,
metavar="TIME", type=self.arg_time,
help="Starting timestamp (free-form)")
help="Starting timestamp (free-form, inclusive)",
).completer = self.complete.time
group.add_argument("-e", "--end", required=True,
metavar="TIME", type=self.arg_time,
help="Ending timestamp (free-form)")
help="Ending timestamp (free-form, noninclusive)",
).completer = self.complete.time
group = cmd.add_argument_group("Output format")
group.add_argument("-B", "--binary", action="store_true",
help="Raw binary output")
group.add_argument("-b", "--bare", action="store_true",
help="Exclude timestamps from output lines")
group.add_argument("-a", "--annotate", action="store_true",
help="Include comments with some information "
"about the stream")
group.add_argument("-m", "--markup", action="store_true",
help="Include comments with interval starts and ends")
group.add_argument("-T", "--timestamp-raw", action="store_true",
help="Show raw timestamps in annotated information")
group.add_argument("-c", "--count", action="store_true",
help="Just output a count of matched data points")
return cmd
def cmd_extract_verify(self):
if self.args.start is not None and self.args.end is not None:
if self.args.start > self.args.end:
self.parser.error("start is after end")
if self.args.binary:
if (self.args.bare or self.args.annotate or self.args.markup or
self.args.timestamp_raw or self.args.count):
self.parser.error("--binary cannot be combined with other options")
def cmd_extract(self):
streams = self.client.stream_list(self.args.path)
if len(streams) != 1:
self.die("Error getting stream info for path %s", self.args.path)
self.die("error getting stream info for path %s", self.args.path)
layout = streams[0][1]
if self.args.timestamp_raw:
time_string = nilmdb.utils.time.timestamp_to_string
else:
time_string = nilmdb.utils.time.timestamp_to_human
if self.args.annotate:
printf("# path: %s\n", self.args.path)
printf("# layout: %s\n", layout)
printf("# start: %s\n", self.time_string(self.args.start))
printf("# end: %s\n", self.time_string(self.args.end))
printf("# start: %s\n", time_string(self.args.start))
printf("# end: %s\n", time_string(self.args.end))
printed = False
if self.args.binary:
printer = sys.stdout.write
else:
printer = print
bare = self.args.bare
count = self.args.count
for dataline in self.client.stream_extract(self.args.path,
self.args.start,
self.args.end,
self.args.count):
if self.args.bare and not self.args.count:
self.args.count,
self.args.markup,
self.args.binary):
if bare and not count:
# Strip timestamp (first element). Doesn't make sense
# if we are only returning a count.
dataline = ' '.join(dataline.split(' ')[1:])
print dataline
printer(dataline)
printed = True
if not printed:
if self.args.annotate:

26
nilmdb/cmdline/help.py Normal file
View File

@@ -0,0 +1,26 @@
from nilmdb.utils.printf import *
import argparse
import sys
def setup(self, sub):
cmd = sub.add_parser("help", help="Show detailed help for a command",
description="""
Show help for a command. 'help command' is
the same as 'command --help'.
""")
cmd.set_defaults(handler = cmd_help)
cmd.set_defaults(no_test_connect = True)
cmd.add_argument("command", nargs="?",
help="Command to get help about")
cmd.add_argument("rest", nargs=argparse.REMAINDER,
help=argparse.SUPPRESS)
return cmd
def cmd_help(self):
if self.args.command in self.subcmd:
self.subcmd[self.args.command].print_help()
else:
self.parser.print_help()
return

View File

@@ -1,5 +1,6 @@
from __future__ import absolute_import
from nilmdb.printf import *
import nilmdb.client
from nilmdb.utils.printf import *
from nilmdb.utils import human_size
from argparse import ArgumentDefaultsHelpFormatter as def_form
@@ -11,11 +12,17 @@ def setup(self, sub):
version.
""")
cmd.set_defaults(handler = cmd_info)
return cmd
def cmd_info(self):
"""Print info about the server"""
printf("Client library version: %s\n", self.client.client_version)
printf("Client version: %s\n", nilmdb.__version__)
printf("Server version: %s\n", self.client.version())
printf("Server URL: %s\n", self.client.geturl())
printf("Server database path: %s\n", self.client.dbpath())
printf("Server database size: %s\n", self.client.dbsize())
dbinfo = self.client.dbinfo()
printf("Server database path: %s\n", dbinfo["path"])
for (desc, field) in [("used by NilmDB", "size"),
("used by other", "other"),
("reserved", "reserved"),
("free", "free")]:
printf("Server disk space %s: %s\n", desc, human_size(dbinfo[field]))

View File

@@ -1,8 +1,7 @@
from __future__ import absolute_import
from nilmdb.printf import *
from nilmdb.utils.printf import *
import nilmdb.client
import nilmdb.layout
import nilmdb.timestamper
import nilmdb.utils.timestamper as timestamper
import nilmdb.utils.time
import sys
@@ -11,96 +10,122 @@ def setup(self, sub):
description="""
Insert data into a stream.
""")
cmd.set_defaults(handler = cmd_insert)
cmd.set_defaults(verify = cmd_insert_verify,
handler = cmd_insert)
cmd.add_argument("-q", "--quiet", action='store_true',
help='suppress unnecessary messages')
group = cmd.add_argument_group("Timestamping",
description="""
If timestamps are already provided in the
input date, use --none. Otherwise,
provide --start, or use --filename to
try to deduce timestamps from the file.
Set the TZ environment variable to change
the default timezone.
To add timestamps, specify the
arguments --timestamp and --rate,
and provide a starting time.
""")
group.add_argument("-t", "--timestamp", action="store_true",
help="Add timestamps to each line")
group.add_argument("-r", "--rate", type=float,
help="""
If needed, rate in Hz (required when using --start)
""")
help="Data rate, in Hz",
).completer = self.complete.rate
group = cmd.add_argument_group("Start time",
description="""
Start time may be manually
specified with --start, or guessed
from the filenames using
--filename. Set the TZ environment
variable to change the default
timezone.""")
exc = group.add_mutually_exclusive_group()
exc.add_argument("-s", "--start",
metavar="TIME", type=self.arg_time,
help="Starting timestamp (free-form)")
help="Starting timestamp (free-form)",
).completer = self.complete.time
exc.add_argument("-f", "--filename", action="store_true",
help="""
Use filenames to determine start time
(default, if filenames are provided)
""")
exc.add_argument("-n", "--none", action="store_true",
help="Timestamp is already present, don't add one")
help="Use filename to determine start time")
group = cmd.add_argument_group("End time",
description="""
End time for the overall stream.
(required when not using --timestamp).
Set the TZ environment
variable to change the default
timezone.""")
group.add_argument("-e", "--end",
metavar="TIME", type=self.arg_time,
help="Ending timestamp (free-form)",
).completer = self.complete.time
group = cmd.add_argument_group("Required parameters")
group.add_argument("path",
help="Path of stream, e.g. /foo/bar")
group.add_argument("file", nargs="*", default=['-'],
help="File(s) to insert (default: - (stdin))")
help="Path of stream, e.g. /foo/bar",
).completer = self.complete.path
group.add_argument("file", nargs = '?', default='-',
help="File to insert (default: - (stdin))")
return cmd
def cmd_insert_verify(self):
if self.args.timestamp:
if not self.args.rate:
self.die("error: --rate is needed, but was not specified")
if not self.args.filename and self.args.start is None:
self.die("error: need --start or --filename when adding timestamps")
else:
if self.args.start is None or self.args.end is None:
self.die("error: when not adding timestamps, --start and "
"--end are required")
def cmd_insert(self):
# Find requested stream
streams = self.client.stream_list(self.args.path)
if len(streams) != 1:
self.die("Error getting stream info for path %s", self.args.path)
self.die("error getting stream info for path %s", self.args.path)
layout = streams[0][1]
arg = self.args
if self.args.start and len(self.args.file) != 1:
self.die("--start can only be used with one input file, for now")
for filename in self.args.file:
try:
filename = arg.file
if filename == '-':
infile = sys.stdin
else:
try:
infile = open(filename, "r")
infile = open(filename, "rb")
except IOError:
self.die("Error opening input file %s", filename)
self.die("error opening input file %s", filename)
# Build a timestamper for this file
if self.args.none:
ts = nilmdb.timestamper.TimestamperNull(infile)
if arg.start is None:
try:
arg.start = nilmdb.utils.time.parse_time(filename)
except ValueError:
self.die("error extracting start time from filename '%s'",
filename)
if arg.timestamp:
data = timestamper.TimestamperRate(infile, arg.start, arg.rate)
else:
if self.args.start:
start = self.args.start
else:
try:
start = self.parse_time(filename)
except ValueError:
self.die("Error extracting time from filename '%s'",
filename)
if not self.args.rate:
self.die("Need to specify --rate")
rate = self.args.rate
ts = nilmdb.timestamper.TimestamperRate(infile, start, rate)
data = iter(lambda: infile.read(1048576), '')
# Print info
if not self.args.quiet:
printf("Input file: %s\n", filename)
printf("Timestamper: %s\n", str(ts))
if not arg.quiet:
printf(" Input file: %s\n", filename)
printf(" Start time: %s\n",
nilmdb.utils.time.timestamp_to_human(arg.start))
if arg.end:
printf(" End time: %s\n",
nilmdb.utils.time.timestamp_to_human(arg.end))
if arg.timestamp:
printf("Timestamper: %s\n", str(data))
# Insert the data
try:
result = self.client.stream_insert(self.args.path, ts)
except nilmdb.client.Error as e:
# TODO: It would be nice to be able to offer better errors
# here, particularly in the case of overlap, which just shows
# ugly bracketed ranges of 16-digit numbers and a mangled URL.
# Need to consider adding something like e.prettyprint()
# that is smarter about the contents of the error.
self.die("Error inserting data: %s", str(e))
self.client.stream_insert(arg.path, data, arg.start, arg.end)
except nilmdb.client.Error as e:
# TODO: It would be nice to be able to offer better errors
# here, particularly in the case of overlap, which just shows
# ugly bracketed ranges of 16-digit numbers and a mangled URL.
# Need to consider adding something like e.prettyprint()
# that is smarter about the contents of the error.
self.die("error inserting data: %s", str(e))
return

View File

@@ -0,0 +1,76 @@
from nilmdb.utils.printf import *
import nilmdb.utils.time
from nilmdb.utils.interval import Interval
import fnmatch
import argparse
from argparse import ArgumentDefaultsHelpFormatter as def_form
def setup(self, sub):
cmd = sub.add_parser("intervals", help="List intervals",
formatter_class = def_form,
description="""
List intervals in a stream, similar to
'list --detail path'.
If '--diff diffpath' is provided, only
interval ranges that are present in 'path'
and not present in 'diffpath' are printed.
""")
cmd.set_defaults(verify = cmd_intervals_verify,
handler = cmd_intervals)
group = cmd.add_argument_group("Stream selection")
group.add_argument("path", metavar="PATH",
help="List intervals for this path",
).completer = self.complete.path
group.add_argument("-d", "--diff", metavar="PATH",
help="Subtract intervals from this path",
).completer = self.complete.path
group = cmd.add_argument_group("Interval details")
group.add_argument("-s", "--start",
metavar="TIME", type=self.arg_time,
help="Starting timestamp for intervals "
"(free-form, inclusive)",
).completer = self.complete.time
group.add_argument("-e", "--end",
metavar="TIME", type=self.arg_time,
help="Ending timestamp for intervals "
"(free-form, noninclusive)",
).completer = self.complete.time
group = cmd.add_argument_group("Misc options")
group.add_argument("-T", "--timestamp-raw", action="store_true",
help="Show raw timestamps when printing times")
group.add_argument("-o", "--optimize", action="store_true",
help="Optimize (merge adjacent) intervals")
return cmd
def cmd_intervals_verify(self):
if self.args.start is not None and self.args.end is not None:
if self.args.start >= self.args.end:
self.parser.error("start must precede end")
def cmd_intervals(self):
"""List intervals in a stream"""
if self.args.timestamp_raw:
time_string = nilmdb.utils.time.timestamp_to_string
else:
time_string = nilmdb.utils.time.timestamp_to_human
try:
intervals = ( Interval(start, end) for (start, end) in
self.client.stream_intervals(self.args.path,
self.args.start,
self.args.end,
self.args.diff) )
if self.args.optimize:
intervals = nilmdb.utils.interval.optimize(intervals)
for i in intervals:
printf("[ %s -> %s ]\n", time_string(i.start), time_string(i.end))
except nilmdb.client.ClientError as e:
self.die("error listing intervals: %s", str(e))

View File

@@ -1,8 +1,8 @@
from __future__ import absolute_import
from nilmdb.printf import *
import nilmdb.client
from nilmdb.utils.printf import *
import nilmdb.utils.time
import fnmatch
import argparse
from argparse import ArgumentDefaultsHelpFormatter as def_form
def setup(self, sub):
@@ -10,45 +10,89 @@ def setup(self, sub):
formatter_class = def_form,
description="""
List streams available in the database,
optionally filtering by layout or path. Wildcards
are accepted.
optionally filtering by path. Wildcards
are accepted; non-matching paths or wildcards
are ignored.
""")
cmd.set_defaults(handler = cmd_list)
cmd.set_defaults(verify = cmd_list_verify,
handler = cmd_list)
group = cmd.add_argument_group("Stream filtering")
group.add_argument("-l", "--layout", default="*",
help="Match only this stream layout")
group.add_argument("-p", "--path", default="*",
help="Match only this path")
group.add_argument("path", metavar="PATH", default=["*"], nargs='*',
).completer = self.complete.path
group = cmd.add_argument_group("Interval info")
group.add_argument("-E", "--ext", action="store_true",
help="Show extended stream info, like interval "
"extents and row count")
group = cmd.add_argument_group("Interval details")
group.add_argument("-d", "--detail", action="store_true",
help="Show available data time intervals")
group.add_argument("-s", "--start",
metavar="TIME", type=self.arg_time,
help="Starting timestamp (free-form)")
help="Starting timestamp for intervals "
"(free-form, inclusive)",
).completer = self.complete.time
group.add_argument("-e", "--end",
metavar="TIME", type=self.arg_time,
help="Ending timestamp (free-form)")
help="Ending timestamp for intervals "
"(free-form, noninclusive)",
).completer = self.complete.time
group = cmd.add_argument_group("Misc options")
group.add_argument("-T", "--timestamp-raw", action="store_true",
help="Show raw timestamps when printing times")
group.add_argument("-l", "--layout", action="store_true",
help="Show layout type next to path name")
return cmd
def cmd_list_verify(self):
if self.args.start is not None and self.args.end is not None:
if self.args.start >= self.args.end:
self.parser.error("start must precede end")
if self.args.start is not None or self.args.end is not None:
if not self.args.detail:
self.parser.error("--start and --end only make sense with --detail")
def cmd_list(self):
"""List available streams"""
streams = self.client.stream_list()
for (path, layout) in streams:
if not (fnmatch.fnmatch(path, self.args.path) and
fnmatch.fnmatch(layout, self.args.layout)):
continue
streams = self.client.stream_list(extended = True)
printf("%s %s\n", path, layout)
if not self.args.detail:
continue
if self.args.timestamp_raw:
time_string = nilmdb.utils.time.timestamp_to_string
else:
time_string = nilmdb.utils.time.timestamp_to_human
printed = False
for (start, end) in self.client.stream_intervals(path, self.args.start,
self.args.end):
printf(" [ %s -> %s ]\n",
self.time_string(start),
self.time_string(end))
printed = True
if not printed:
printf(" (no intervals)\n")
for argpath in self.args.path:
for stream in streams:
(path, layout, int_min, int_max, rows, time) = stream[:6]
if not fnmatch.fnmatch(path, argpath):
continue
if self.args.layout:
printf("%s %s\n", path, layout)
else:
printf("%s\n", path)
if self.args.ext:
if int_min is None or int_max is None:
printf(" interval extents: (no data)\n")
else:
printf(" interval extents: %s -> %s\n",
time_string(int_min), time_string(int_max))
printf(" total data: %d rows, %.6f seconds\n",
rows or 0,
nilmdb.utils.time.timestamp_to_seconds(time or 0))
if self.args.detail:
printed = False
for (start, end) in self.client.stream_intervals(
path, self.args.start, self.args.end):
printf(" [ %s -> %s ]\n",
time_string(start), time_string(end))
printed = True
if not printed:
printf(" (no intervals)\n")

View File

@@ -1,5 +1,5 @@
from __future__ import absolute_import
from nilmdb.printf import *
from nilmdb.utils.printf import *
import nilmdb
import nilmdb.client
def setup(self, sub):
@@ -9,33 +9,42 @@ def setup(self, sub):
a stream.
""",
usage="%(prog)s path [-g [key ...] | "
"-s key=value [...] | -u key=value [...]]")
"-s key=value [...] | -u key=value [...]] | "
"-d [key ...]")
cmd.set_defaults(handler = cmd_metadata)
group = cmd.add_argument_group("Required arguments")
group.add_argument("path",
help="Path of stream, e.g. /foo/bar")
help="Path of stream, e.g. /foo/bar",
).completer = self.complete.path
group = cmd.add_argument_group("Actions")
exc = group.add_mutually_exclusive_group()
exc.add_argument("-g", "--get", nargs="*", metavar="key",
help="Get metadata for specified keys (default all)")
help="Get metadata for specified keys (default all)",
).completer = self.complete.meta_key
exc.add_argument("-s", "--set", nargs="+", metavar="key=value",
help="Replace all metadata with provided "
"key=value pairs")
"key=value pairs",
).completer = self.complete.meta_keyval
exc.add_argument("-u", "--update", nargs="+", metavar="key=value",
help="Update metadata using provided "
"key=value pairs")
"key=value pairs",
).completer = self.complete.meta_keyval
exc.add_argument("-d", "--delete", nargs="*", metavar="key",
help="Delete metadata for specified keys (default all)",
).completer = self.complete.meta_key
return cmd
def cmd_metadata(self):
"""Manipulate metadata"""
if self.args.set is not None or self.args.update is not None:
# Either set, or update
if self.args.set is not None:
keyvals = self.args.set
keyvals = map(nilmdb.utils.unicode.decode, self.args.set)
handler = self.client.stream_set_metadata
else:
keyvals = self.args.update
keyvals = map(nilmdb.utils.unicode.decode, self.args.update)
handler = self.client.stream_update_metadata
# Extract key=value pairs
@@ -43,23 +52,39 @@ def cmd_metadata(self):
for keyval in keyvals:
kv = keyval.split('=')
if len(kv) != 2 or kv[0] == "":
self.die("Error parsing key=value argument '%s'", keyval)
self.die("error parsing key=value argument '%s'", keyval)
data[kv[0]] = kv[1]
# Make the call
try:
handler(self.args.path, data)
except nilmdb.client.ClientError as e:
self.die("Error setting/updating metadata: %s", str(e))
self.die("error setting/updating metadata: %s", str(e))
elif self.args.delete is not None:
# Delete (by setting values to empty strings)
keys = None
if self.args.delete:
keys = map(nilmdb.utils.unicode.decode, self.args.delete)
try:
data = self.client.stream_get_metadata(self.args.path, keys)
for key in data:
data[key] = ""
self.client.stream_update_metadata(self.args.path, data)
except nilmdb.client.ClientError as e:
self.die("error deleting metadata: %s", str(e))
else:
# Get (or unspecified)
keys = self.args.get or None
keys = None
if self.args.get:
keys = map(nilmdb.utils.unicode.decode, self.args.get)
try:
data = self.client.stream_get_metadata(self.args.path, keys)
except nilmdb.client.ClientError as e:
self.die("Error getting metadata: %s", str(e))
self.die("error getting metadata: %s", str(e))
for key, value in sorted(data.items()):
# Omit nonexistant keys
# Print nonexistant keys as having empty value
if value is None:
value = ""
printf("%s=%s\n", key, value)
printf("%s=%s\n",
nilmdb.utils.unicode.encode(key),
nilmdb.utils.unicode.encode(value))

55
nilmdb/cmdline/remove.py Normal file
View File

@@ -0,0 +1,55 @@
from nilmdb.utils.printf import *
import nilmdb.client
import fnmatch
def setup(self, sub):
cmd = sub.add_parser("remove", help="Remove data",
description="""
Remove all data from a specified time range within a
stream. If multiple streams or wildcards are provided,
the same time range is removed from all streams.
""")
cmd.set_defaults(handler = cmd_remove)
group = cmd.add_argument_group("Data selection")
group.add_argument("path", nargs='+',
help="Path of stream, e.g. /foo/bar/*",
).completer = self.complete.path
group.add_argument("-s", "--start", required=True,
metavar="TIME", type=self.arg_time,
help="Starting timestamp (free-form, inclusive)",
).completer = self.complete.time
group.add_argument("-e", "--end", required=True,
metavar="TIME", type=self.arg_time,
help="Ending timestamp (free-form, noninclusive)",
).completer = self.complete.time
group = cmd.add_argument_group("Output format")
group.add_argument("-q", "--quiet", action="store_true",
help="Don't display names when removing "
"from multiple paths")
group.add_argument("-c", "--count", action="store_true",
help="Output number of data points removed")
return cmd
def cmd_remove(self):
streams = [ s[0] for s in self.client.stream_list() ]
paths = []
for path in self.args.path:
new = fnmatch.filter(streams, path)
if not new:
self.die("error: no stream matched path: %s", path)
paths.extend(new)
try:
for path in paths:
if not self.args.quiet and len(paths) > 1:
printf("Removing from %s\n", path)
count = self.client.stream_remove(path,
self.args.start, self.args.end)
if self.args.count:
printf("%d\n", count);
except nilmdb.client.ClientError as e:
self.die("error removing data: %s", str(e))
return 0

31
nilmdb/cmdline/rename.py Normal file
View File

@@ -0,0 +1,31 @@
from nilmdb.utils.printf import *
import nilmdb.client
from argparse import ArgumentDefaultsHelpFormatter as def_form
def setup(self, sub):
cmd = sub.add_parser("rename", help="Rename a stream",
formatter_class = def_form,
description="""
Rename a stream.
Only the stream's path is renamed; no
metadata is changed.
""")
cmd.set_defaults(handler = cmd_rename)
group = cmd.add_argument_group("Required arguments")
group.add_argument("oldpath",
help="Old path, e.g. /foo/old",
).completer = self.complete.path
group.add_argument("newpath",
help="New path, e.g. /foo/bar/new",
).completer = self.complete.path
return cmd
def cmd_rename(self):
"""Rename a stream"""
try:
self.client.stream_rename(self.args.oldpath, self.args.newpath)
except nilmdb.client.ClientError as e:
self.die("error renaming stream: %s", str(e))

5
nilmdb/fsck/__init__.py Normal file
View File

@@ -0,0 +1,5 @@
"""nilmdb.fsck"""
from __future__ import absolute_import
from nilmdb.fsck.fsck import Fsck

450
nilmdb/fsck/fsck.py Normal file
View File

@@ -0,0 +1,450 @@
# -*- coding: utf-8 -*-
"""Check database consistency, with some ability to fix problems.
This should be able to fix cases where a database gets corrupted due
to unexpected system shutdown, and detect other cases that may cause
NilmDB to return errors when trying to manipulate the database."""
import nilmdb.utils
import nilmdb.server
import nilmdb.client.numpyclient
from nilmdb.utils.interval import IntervalError
from nilmdb.server.interval import Interval, IntervalSet
from nilmdb.utils.printf import *
from nilmdb.utils.time import timestamp_to_string
from collections import defaultdict
import sqlite3
import os
import sys
import progressbar
import re
import time
import shutil
import cPickle as pickle
import numpy
class FsckError(Exception):
def __init__(self, msg = "", *args):
if args:
msg = sprintf(msg, *args)
Exception.__init__(self, msg)
class FixableFsckError(FsckError):
def __init__(self, msg = "", *args):
if args:
msg = sprintf(msg, *args)
FsckError.__init__(self, "%s\nThis may be fixable with \"--fix\".", msg)
class RetryFsck(FsckError):
pass
def log(format, *args):
printf(format, *args)
def err(format, *args):
fprintf(sys.stderr, format, *args)
# Decorator that retries a function if it returns a specific value
def retry_if_raised(exc, message = None):
def f1(func):
def f2(*args, **kwargs):
while True:
try:
return func(*args, **kwargs)
except exc as e:
if message:
log("%s\n\n", message)
return f2
return f1
class Progress(object):
def __init__(self, maxval):
self.bar = progressbar.ProgressBar(
maxval = maxval,
widgets = [ progressbar.Percentage(), ' ',
progressbar.Bar(), ' ',
progressbar.ETA() ])
if self.bar.term_width == 0:
self.bar.term_width = 75
def __enter__(self):
self.bar.start()
self.last_update = 0
return self
def __exit__(self, exc_type, exc_value, traceback):
if exc_type is None:
self.bar.finish()
else:
printf("\n")
def update(self, val):
self.bar.update(val)
class Fsck(object):
def __init__(self, path, fix = False):
self.basepath = path
self.sqlpath = os.path.join(path, "data.sql")
self.bulkpath = os.path.join(path, "data")
self.bulklock = os.path.join(path, "data.lock")
self.fix = fix
### Main checks
@retry_if_raised(RetryFsck, "Something was fixed: restarting fsck")
def check(self):
self.bulk = None
self.sql = None
try:
self.check_paths()
self.check_sql()
self.check_streams()
self.check_intervals()
self.check_data()
finally:
if self.bulk:
self.bulk.close()
if self.sql:
self.sql.commit()
self.sql.close()
log("ok\n")
### Check basic path structure
def check_paths(self):
log("checking paths\n")
if self.bulk:
self.bulk.close()
if not os.path.isfile(self.sqlpath):
raise FsckError("SQL database missing (%s)", self.sqlpath)
if not os.path.isdir(self.bulkpath):
raise FsckError("Bulk data directory missing (%s)", self.bulkpath)
with open(self.bulklock, "w") as lockfile:
if not nilmdb.utils.lock.exclusive_lock(lockfile):
raise FsckError('database already locked by another process')
# unlocked immediately
self.bulk = nilmdb.server.bulkdata.BulkData(self.basepath)
### Check SQL database health
def check_sql(self):
log("checking sqlite database\n")
self.sql = sqlite3.connect(self.sqlpath)
with self.sql:
cur = self.sql.cursor()
ver = cur.execute("PRAGMA user_version").fetchone()[0]
good = max(nilmdb.server.nilmdb._sql_schema_updates.keys())
if ver != good:
raise FsckError("database version %d too old, should be %d",
ver, good)
self.stream_path = {}
self.stream_layout = {}
log(" loading paths\n")
result = cur.execute("SELECT id, path, layout FROM streams")
for r in result:
if r[0] in self.stream_path:
raise FsckError("duplicated ID %d in stream IDs", r[0])
self.stream_path[r[0]] = r[1]
self.stream_layout[r[0]] = r[2]
log(" loading intervals\n")
self.stream_interval = defaultdict(list)
result = cur.execute("SELECT stream_id, start_time, end_time, "
"start_pos, end_pos FROM ranges "
"ORDER BY start_time")
for r in result:
if r[0] not in self.stream_path:
raise FsckError("interval ID %d not in streams", k)
self.stream_interval[r[0]].append((r[1], r[2], r[3], r[4]))
log(" loading metadata\n")
self.stream_meta = defaultdict(dict)
result = cur.execute("SELECT stream_id, key, value FROM metadata")
for r in result:
if r[0] not in self.stream_path:
raise FsckError("metadata ID %d not in streams", k)
if r[1] in self.stream_meta[r[0]]:
raise FsckError("duplicate metadata key '%s' for stream %d",
r[1], r[0])
self.stream_meta[r[0]][r[1]] = r[2]
### Check streams and basic interval overlap
def check_streams(self):
ids = self.stream_path.keys()
log("checking %d streams\n", len(ids))
with Progress(len(ids)) as pbar:
for i, sid in enumerate(ids):
pbar.update(i)
path = self.stream_path[sid]
# unique path, valid layout
if self.stream_path.values().count(path) != 1:
raise FsckError("duplicated path %s", path)
layout = self.stream_layout[sid].split('_')[0]
if layout not in ('int8', 'int16', 'int32', 'int64',
'uint8', 'uint16', 'uint32', 'uint64',
'float32', 'float64'):
raise FsckError("bad layout %s for %s", layout, path)
count = int(self.stream_layout[sid].split('_')[1])
if count < 1 or count > 1024:
raise FsckError("bad count %d for %s", count, path)
# must exist in bulkdata
bulk = self.bulkpath + path
if not os.path.isdir(bulk):
raise FsckError("%s: missing bulkdata dir", path)
if not nilmdb.server.bulkdata.Table.exists(bulk):
raise FsckError("%s: bad bulkdata table", path)
# intervals don't overlap. Abuse IntervalSet to check
# for intervals in file positions, too.
timeiset = IntervalSet()
posiset = IntervalSet()
for (stime, etime, spos, epos) in self.stream_interval[sid]:
new = Interval(stime, etime)
try:
timeiset += new
except IntervalError:
raise FsckError("%s: overlap in intervals:\n"
"set: %s\nnew: %s",
path, str(timeiset), str(new))
if spos != epos:
new = Interval(spos, epos)
try:
posiset += new
except IntervalError:
raise FsckError("%s: overlap in file offsets:\n"
"set: %s\nnew: %s",
path, str(posiset), str(new))
# check bulkdata
self.check_bulkdata(sid, path, bulk)
# Check that we can open bulkdata
try:
tab = None
try:
tab = nilmdb.server.bulkdata.Table(bulk)
except Exception as e:
raise FsckError("%s: can't open bulkdata: %s",
path, str(e))
finally:
if tab:
tab.close()
### Check that bulkdata is good enough to be opened
@retry_if_raised(RetryFsck)
def check_bulkdata(self, sid, path, bulk):
with open(os.path.join(bulk, "_format"), "rb") as f:
fmt = pickle.load(f)
if fmt["version"] != 3:
raise FsckError("%s: bad or unsupported bulkdata version %d",
path, fmt["version"])
row_per_file = int(fmt["rows_per_file"])
files_per_dir = int(fmt["files_per_dir"])
layout = fmt["layout"]
if layout != self.stream_layout[sid]:
raise FsckError("%s: layout mismatch %s != %s", path,
layout, self.stream_layout[sid])
# Every file should have a size that's the multiple of the row size
rkt = nilmdb.server.rocket.Rocket(layout, None)
row_size = rkt.binary_size
rkt.close()
# Find all directories
regex = re.compile("^[0-9a-f]{4,}$")
subdirs = sorted(filter(regex.search, os.listdir(bulk)),
key = lambda x: int(x, 16), reverse = True)
for subdir in subdirs:
# Find all files in that dir
subpath = os.path.join(bulk, subdir)
files = filter(regex.search, os.listdir(subpath))
if not files:
self.fix_empty_subdir(subpath)
raise RetryFsck
# Verify that their size is a multiple of the row size
for filename in files:
filepath = os.path.join(subpath, filename)
offset = os.path.getsize(filepath)
if offset % row_size:
self.fix_bad_filesize(path, filepath, offset, row_size)
def fix_empty_subdir(self, subpath):
msg = sprintf("bulkdata path %s is missing data files", subpath)
if not self.fix:
raise FixableFsckError(msg)
# Try to fix it by just deleting whatever is present,
# as long as it's only ".removed" files.
err("\n%s\n", msg)
for fn in os.listdir(subpath):
if not fn.endswith(".removed"):
raise FsckError("can't fix automatically: please manually "
"remove the file %s and try again",
os.path.join(subpath, fn))
# Remove the whole thing
err("Removing empty subpath\n")
shutil.rmtree(subpath)
raise RetryFsck
def fix_bad_filesize(self, path, filepath, offset, row_size):
extra = offset % row_size
msg = sprintf("%s: size of file %s (%d) is not a multiple" +
" of row size (%d): %d extra bytes present",
path, filepath, offset, row_size, extra)
if not self.fix:
raise FixableFsckError(msg)
# Try to fix it by just truncating the file
err("\n%s\n", msg)
newsize = offset - extra
err("Truncating file to %d bytes and retrying\n", newsize)
with open(filepath, "r+b") as f:
f.truncate(newsize)
raise RetryFsck
### Check interval endpoints
def check_intervals(self):
total_ints = sum(len(x) for x in self.stream_interval.values())
log("checking %d intervals\n", total_ints)
done = 0
with Progress(total_ints) as pbar:
for sid in self.stream_interval:
try:
bulk = self.bulkpath + self.stream_path[sid]
tab = nilmdb.server.bulkdata.Table(bulk)
def update(x):
pbar.update(done + x)
ints = self.stream_interval[sid]
done += self.check_table_intervals(sid, ints, tab, update)
finally:
tab.close()
def check_table_intervals(self, sid, ints, tab, update):
# look in the table to make sure we can pick out the interval's
# endpoints
path = self.stream_path[sid]
tab.file_open.cache_remove_all()
for (i, intv) in enumerate(ints):
update(i)
(stime, etime, spos, epos) = intv
if spos == epos and spos >= 0 and spos <= tab.nrows:
continue
try:
srow = tab[spos]
erow = tab[epos-1]
except Exception as e:
self.fix_bad_interval(sid, intv, tab, str(e))
raise RetryFsck
return len(ints)
def fix_bad_interval(self, sid, intv, tab, msg):
path = self.stream_path[sid]
msg = sprintf("%s: interval %s error accessing rows: %s",
path, str(intv), str(msg))
if not self.fix:
raise FixableFsckError(msg)
err("\n%s\n", msg)
(stime, etime, spos, epos) = intv
# If it's just that the end pos is more than the number of rows
# in the table, lower end pos and truncate interval time too.
if spos < tab.nrows and epos >= tab.nrows:
err("end position is past endrows, but it can be truncated\n")
err("old end: time %d, pos %d\n", etime, epos)
new_epos = tab.nrows
new_etime = tab[new_epos-1] + 1
err("new end: time %d, pos %d\n", new_etime, new_epos)
if stime < new_etime:
# Change it in SQL
with self.sql:
cur = self.sql.cursor()
cur.execute("UPDATE ranges SET end_time=?, end_pos=? "
"WHERE stream_id=? AND start_time=? AND "
"end_time=? AND start_pos=? AND end_pos=?",
(new_etime, new_epos, sid, stime, etime,
spos, epos))
if cur.rowcount != 1:
raise FsckError("failed to fix SQL database")
raise RetryFsck
err("actually it can't be truncated; times are bad too")
# Otherwise, the only hope is to delete the interval entirely.
err("*** Deleting the entire interval from SQL.\n")
err("This may leave stale data on disk. To fix that, copy all\n")
err("data from this stream to a new stream, then remove all data\n")
err("from and destroy %s.\n")
with self.sql:
cur = self.sql.cursor()
cur.execute("DELETE FROM ranges WHERE "
"stream_id=? AND start_time=? AND "
"end_time=? AND start_pos=? AND end_pos=?",
(sid, stime, etime, spos, epos))
if cur.rowcount != 1:
raise FsckError("failed to remove interval")
raise RetryFsck
### Check data in each interval
def check_data(self):
total_rows = sum(sum((y[3] - y[2]) for y in x)
for x in self.stream_interval.values())
log("checking %d rows of data\n", total_rows)
done = 0
with Progress(total_rows) as pbar:
for sid in self.stream_interval:
try:
bulk = self.bulkpath + self.stream_path[sid]
tab = nilmdb.server.bulkdata.Table(bulk)
def update(x):
pbar.update(done + x)
ints = self.stream_interval[sid]
done += self.check_table_data(sid, ints, tab, update)
finally:
tab.close()
def check_table_data(self, sid, ints, tab, update):
# Pull out all of the interval's data and verify that it's
# monotonic.
maxrows = 100000
path = self.stream_path[sid]
layout = self.stream_layout[sid]
dtype = nilmdb.client.numpyclient.layout_to_dtype(layout)
tab.file_open.cache_remove_all()
done = 0
for intv in ints:
last_ts = None
(stime, etime, spos, epos) = intv
if spos == epos:
continue
for start in xrange(*slice(spos, epos, maxrows).indices(epos)):
stop = min(start + maxrows, epos)
count = stop - start
# Get raw data, convert to NumPy arary
try:
raw = tab.get_data(start, stop, binary = True)
data = numpy.fromstring(raw, dtype)
except Exception as e:
raise FsckError("%s: failed to grab rows %d through %d: %s",
path, start, stop, repr(e))
# Verify that timestamps are monotonic
if (numpy.diff(data['timestamp']) <= 0).any():
raise FsckError("%s: non-monotonic timestamp(s) in rows "
"%d through %d", path, start, stop)
first_ts = data['timestamp'][0]
if last_ts is not None and first_ts <= last_ts:
raise FsckError("%s: first interval timestamp %d is not "
"greater than the previous last interval "
"timestamp %d, at row %d",
path, first_ts, last_ts, start)
last_ts = data['timestamp'][-1]
# These are probably fixable, by removing the offending
# intervals. But I'm not going to bother implementing
# that yet.
# Done
done += count
update(done)
return done

View File

@@ -1,220 +0,0 @@
"""HTTP client library"""
from __future__ import absolute_import
from nilmdb.printf import *
import time
import sys
import re
import os
import simplejson as json
import urlparse
import urllib
import pycurl
import cStringIO
import nilmdb.iteratorizer
class Error(Exception):
"""Base exception for both ClientError and ServerError responses"""
def __init__(self,
status = "Unspecified error",
message = None,
url = None,
traceback = None):
Exception.__init__(self, status)
self.status = status # e.g. "400 Bad Request"
self.message = message # textual message from the server
self.url = url # URL we were requesting
self.traceback = traceback # server traceback, if available
def __str__(self):
s = sprintf("[%s]", self.status)
if self.message:
s += sprintf(" %s", self.message)
if self.url:
s += sprintf(" (%s)", self.url)
if self.traceback: # pragma: no cover
s += sprintf("\nServer traceback:\n%s", self.traceback)
return s
class ClientError(Error):
pass
class ServerError(Error):
pass
class HTTPClient(object):
"""Class to manage and perform HTTP requests from the client"""
def __init__(self, baseurl = ""):
"""If baseurl is supplied, all other functions that take
a URL can be given a relative URL instead."""
# Verify / clean up URL
reparsed = urlparse.urlparse(baseurl).geturl()
if '://' not in reparsed:
reparsed = urlparse.urlparse("http://" + baseurl).geturl()
self.baseurl = reparsed
self.curl = pycurl.Curl()
self.curl.setopt(pycurl.SSL_VERIFYHOST, 2)
self.curl.setopt(pycurl.FOLLOWLOCATION, 1)
self.curl.setopt(pycurl.MAXREDIRS, 5)
self._setup_url()
def _setup_url(self, url = "", params = ""):
url = urlparse.urljoin(self.baseurl, url)
if params:
url = urlparse.urljoin(url, "?" + urllib.urlencode(params, True))
self.curl.setopt(pycurl.URL, url)
self.url = url
def _check_error(self, body = None):
code = self.curl.getinfo(pycurl.RESPONSE_CODE)
if code == 200:
return
# Default variables for exception
args = { "url" : self.url,
"status" : str(code),
"message" : None,
"traceback" : None }
try:
# Fill with server-provided data if we can
jsonerror = json.loads(body)
args["status"] = jsonerror["status"]
args["message"] = jsonerror["message"]
args["traceback"] = jsonerror["traceback"]
except Exception: # pragma: no cover
pass
if code >= 400 and code <= 499:
raise ClientError(**args)
else: # pragma: no cover
if code >= 500 and code <= 599:
raise ServerError(**args)
else:
raise Error(**args)
def _req_generator(self, url, params):
"""
Like self._req(), but runs the perform in a separate thread.
It returns a generator that spits out arbitrary-sized chunks
of the resulting data, instead of using the WRITEFUNCTION
callback.
"""
self._setup_url(url, params)
self._status = None
error_body = ""
self._headers = ""
def header_callback(data):
if self._status is None:
self._status = int(data.split(" ")[1])
self._headers += data
self.curl.setopt(pycurl.HEADERFUNCTION, header_callback)
def func(callback):
self.curl.setopt(pycurl.WRITEFUNCTION, callback)
self.curl.perform()
try:
for i in nilmdb.iteratorizer.Iteratorizer(func):
if self._status == 200:
# If we had a 200 response, yield the data to the caller.
yield i
else:
# Otherwise, collect it into an error string.
error_body += i
except pycurl.error as e:
raise ServerError(status = "502 Error",
url = self.url,
message = e[1])
# Raise an exception if there was an error
self._check_error(error_body)
def _req(self, url, params):
"""
GET or POST that returns raw data. Returns the body
data as a string, or raises an error if it contained an error.
"""
self._setup_url(url, params)
body = cStringIO.StringIO()
self.curl.setopt(pycurl.WRITEFUNCTION, body.write)
self._headers = ""
def header_callback(data):
self._headers += data
self.curl.setopt(pycurl.HEADERFUNCTION, header_callback)
try:
self.curl.perform()
except pycurl.error as e:
raise ServerError(status = "502 Error",
url = self.url,
message = e[1])
body_str = body.getvalue()
# Raise an exception if there was an error
self._check_error(body_str)
return body_str
def close(self):
self.curl.close()
def _iterate_lines(self, it):
"""
Given an iterator that returns arbitrarily-sized chunks
of data, return '\n'-delimited lines of text
"""
partial = ""
for chunk in it:
partial += chunk
lines = partial.split("\n")
for line in lines[0:-1]:
yield line
partial = lines[-1]
if partial != "":
yield partial
# Non-generator versions
def _doreq(self, url, params, retjson):
"""
Perform a request, and return the body.
url: URL to request (relative to baseurl)
params: dictionary of query parameters
retjson: expect JSON and return python objects instead of string
"""
out = self._req(url, params)
if retjson:
return json.loads(out)
return out
def get(self, url, params = None, retjson = True):
"""Simple GET"""
self.curl.setopt(pycurl.UPLOAD, 0)
return self._doreq(url, params, retjson)
def put(self, url, postdata, params = None, retjson = True):
"""Simple PUT"""
self._setup_url(url, params)
data = cStringIO.StringIO(postdata)
self.curl.setopt(pycurl.UPLOAD, 1)
self.curl.setopt(pycurl.READFUNCTION, data.read)
return self._doreq(url, params, retjson)
# Generator versions
def _doreq_gen(self, url, params, retjson):
"""
Perform a request, and return lines of the body in a generator.
url: URL to request (relative to baseurl)
params: dictionary of query parameters
retjson: expect JSON and yield python objects instead of strings
"""
for line in self._iterate_lines(self._req_generator(url, params)):
if retjson:
yield json.loads(line)
else:
yield line
def get_gen(self, url, params = None, retjson = True):
"""Simple GET, returning a generator"""
self.curl.setopt(pycurl.UPLOAD, 0)
return self._doreq_gen(url, params, retjson)
def put_gen(self, url, postdata, params = None, retjson = True):
"""Simple PUT, returning a generator"""
self._setup_url(url, params)
data = cStringIO.StringIO(postdata)
self.curl.setopt(pycurl.UPLOAD, 1)
self.curl.setopt(pycurl.READFUNCTION, data.read)
return self._doreq_gen(url, params, retjson)

View File

@@ -1,72 +0,0 @@
import Queue
import threading
import sys
# This file provides a class that will convert a function that
# takes a callback into a generator that returns an iterator.
# Based partially on http://stackoverflow.com/questions/9968592/
class IteratorizerThread(threading.Thread):
def __init__(self, queue, function):
"""
function: function to execute, which takes the
callback (provided by this class) as an argument
"""
threading.Thread.__init__(self)
self.function = function
self.queue = queue
self.die = False
def callback(self, data):
if self.die:
raise Exception("should die")
self.queue.put((1, data))
def run(self):
try:
result = self.function(self.callback)
except:
if sys is not None: # can be None during unclean shutdown
self.queue.put((2, sys.exc_info()))
else:
self.queue.put((0, result))
class Iteratorizer(object):
def __init__(self, function):
"""
function: function to execute, which takes the
callback (provided by this class) as an argument
"""
self.function = function
self.queue = Queue.Queue(maxsize = 1)
self.thread = IteratorizerThread(self.queue, self.function)
self.thread.daemon = True
self.thread.start()
def __del__(self):
# If we get garbage collected, try to get rid of the
# thread too by asking it to raise an exception, then
# draining the queue until it's gone.
self.thread.die = True
while self.thread.isAlive():
try:
self.queue.get(True, 0.01)
except: # pragma: no cover
pass
def __iter__(self):
return self
def next(self):
(typ, data) = self.queue.get()
if typ == 0:
# function returned
self.retval = data
raise StopIteration
elif typ == 1:
# data available
return data
else:
# exception
raise data[0], data[1], data[2]

View File

@@ -1,219 +0,0 @@
# cython: profile=False
import tables
import time
import sys
import inspect
import cStringIO
import numpy as np
cdef enum:
max_value_count = 64
cimport cython
cimport libc.stdlib
cimport libc.stdio
cimport libc.string
class ParserError(Exception):
def __init__(self, line, message):
self.message = "line " + str(line) + ": " + message
Exception.__init__(self, self.message)
class FormatterError(Exception):
pass
class Layout:
"""Represents a NILM database layout"""
def __init__(self, typestring):
"""Initialize this Layout object to handle the specified
type string"""
try:
[ datatype, count ] = typestring.split("_")
except:
raise KeyError("invalid layout string")
try:
self.count = int(count)
except ValueError:
raise KeyError("invalid count")
if self.count < 1 or self.count > max_value_count:
raise KeyError("invalid count")
if datatype == 'uint16':
self.parse = self.parse_uint16
self.format = self.format_uint16
elif datatype == 'float32' or datatype == 'float64':
self.parse = self.parse_float64
self.format = self.format_float64
else:
raise KeyError("invalid type")
self.datatype = datatype
# Parsers
def parse_float64(self, char *text):
cdef int n
cdef double ts
# Return doubles even in float32 case, since they're going into
# a Python array which would upconvert to double anyway.
result = []
cdef char *end
ts = libc.stdlib.strtod(text, &end)
if end == text:
raise ValueError("bad timestamp")
result.append(ts)
for n in range(self.count):
text = end
result.append(libc.stdlib.strtod(text, &end))
if end == text:
raise ValueError("wrong number of values")
n = 0
while end[n] == ' ':
n += 1
if end[n] != '\n' and end[n] != '#' and end[n] != '\0':
raise ValueError("extra data on line")
return (ts, result)
def parse_uint16(self, char *text):
cdef int n
cdef double ts
cdef int v
result = []
cdef char *end
ts = libc.stdlib.strtod(text, &end)
if end == text:
raise ValueError("bad timestamp")
result.append(ts)
for n in range(self.count):
text = end
v = libc.stdlib.strtol(text, &end, 10)
if v < 0 or v > 65535:
raise ValueError("value out of range")
result.append(v)
if end == text:
raise ValueError("wrong number of values")
n = 0
while end[n] == ' ':
n += 1
if end[n] != '\n' and end[n] != '#' and end[n] != '\0':
raise ValueError("extra data on line")
return (ts, result)
# Formatters
def format_float64(self, d):
n = len(d) - 1
if n != self.count:
raise ValueError("wrong number of values for layout type: "
"got %d, wanted %d" % (n, self.count))
s = "%.6f" % d[0]
for i in range(n):
s += " %f" % d[i+1]
return s + "\n"
def format_uint16(self, d):
n = len(d) - 1
if n != self.count:
raise ValueError("wrong number of values for layout type: "
"got %d, wanted %d" % (n, self.count))
s = "%.6f" % d[0]
for i in range(n):
s += " %d" % d[i+1]
return s + "\n"
# PyTables description
def description(self):
"""Return the PyTables description of this layout"""
desc = {}
desc['timestamp'] = tables.Col.from_type('float64', pos=0)
for n in range(self.count):
desc['c' + str(n+1)] = tables.Col.from_type(self.datatype, pos=n+1)
return tables.Description(desc)
# Get a layout by name
def get_named(typestring):
try:
return Layout(typestring)
except KeyError:
compat = { "PrepData": "float32_8",
"RawData": "uint16_6",
"RawNotchedData": "uint16_9" }
return Layout(compat[typestring])
class Parser(object):
"""Object that parses and stores ASCII data for inclusion into the
database"""
def __init__(self, layout):
if issubclass(layout.__class__, Layout):
self.layout = layout
else:
try:
self.layout = get_named(layout)
except KeyError:
raise TypeError("unknown layout")
self.data = []
self.min_timestamp = None
self.max_timestamp = None
def parse(self, textdata):
"""
Parse the data, provided as lines of text, using the current
layout, into an internal data structure suitable for a
pytables 'table.append(parser.data)'.
"""
cdef double last_ts = 0, ts
cdef int n = 0, i
cdef char *line
indata = cStringIO.StringIO(textdata)
# Assume any parsing error is a real error.
# In the future we might want to skip completely empty lines,
# or partial lines right before EOF?
try:
self.data = []
for pyline in indata:
line = pyline
n += 1
if line[0] == '\#':
continue
(ts, row) = self.layout.parse(line)
if ts < last_ts:
raise ValueError("timestamp is not "
"monotonically increasing")
last_ts = ts
self.data.append(row)
except (ValueError, IndexError, TypeError) as e:
raise ParserError(n, "error: " + e.message)
# Mark timestamp ranges
if len(self.data):
self.min_timestamp = self.data[0][0]
self.max_timestamp = self.data[-1][0]
class Formatter(object):
"""Object that formats database data into ASCII"""
def __init__(self, layout):
if issubclass(layout.__class__, Layout):
self.layout = layout
else:
try:
self.layout = get_named(layout)
except KeyError:
raise TypeError("unknown layout")
def format(self, data):
"""
Format raw data from the database, using the current layout,
as lines of ACSII text.
"""
text = cStringIO.StringIO()
try:
for row in data:
text.write(self.layout.format(row))
except (ValueError, IndexError, TypeError) as e:
raise FormatterError("formatting error: " + e.message)
return text.getvalue()

View File

@@ -1,496 +0,0 @@
# -*- coding: utf-8 -*-
"""NilmDB
Object that represents a NILM database file.
Manages both the SQL database and the PyTables storage backend.
"""
# Need absolute_import so that "import nilmdb" won't pull in nilmdb.py,
# but will pull the nilmdb module instead.
from __future__ import absolute_import
import nilmdb
from nilmdb.printf import *
import sqlite3
import tables
import time
import sys
import os
import errno
import bisect
import pyximport
pyximport.install()
from nilmdb.interval import Interval, DBInterval, IntervalSet, IntervalError
# Note about performance and transactions:
#
# Committing a transaction in the default sync mode (PRAGMA synchronous=FULL)
# takes about 125msec. sqlite3 will commit transactions at 3 times:
# 1: explicit con.commit()
# 2: between a series of DML commands and non-DML commands, e.g.
# after a series of INSERT, SELECT, but before a CREATE TABLE or PRAGMA.
# 3: at the end of an explicit transaction, e.g. "with self.con as con:"
#
# To speed up testing, or if this transaction speed becomes an issue,
# the sync=False option to NilmDB.__init__ will set PRAGMA synchronous=OFF.
# Don't touch old entries -- just add new ones.
_sql_schema_updates = {
0: """
-- All streams
CREATE TABLE streams(
id INTEGER PRIMARY KEY, -- stream ID
path TEXT UNIQUE NOT NULL, -- path, e.g. '/newton/prep'
layout TEXT NOT NULL -- layout name, e.g. float32_8
);
-- Individual timestamped ranges in those streams.
-- For a given start_time and end_time, this tells us that the
-- data is stored between start_pos and end_pos.
-- Times are stored as μs since Unix epoch
-- Positions are opaque: PyTables rows, file offsets, etc.
--
-- Note: end_pos points to the row _after_ end_time, so end_pos-1
-- is the last valid row.
CREATE TABLE ranges(
stream_id INTEGER NOT NULL,
start_time INTEGER NOT NULL,
end_time INTEGER NOT NULL,
start_pos INTEGER NOT NULL,
end_pos INTEGER NOT NULL
);
CREATE INDEX _ranges_index ON ranges (stream_id, start_time, end_time);
""",
1: """
-- Generic dictionary-type metadata that can be associated with a stream
CREATE TABLE metadata(
stream_id INTEGER NOT NULL,
key TEXT NOT NULL,
value TEXT
);
""",
}
class NilmDBError(Exception):
"""Base exception for NilmDB errors"""
def __init__(self, message = "Unspecified error"):
Exception.__init__(self, self.__class__.__name__ + ": " + message)
class StreamError(NilmDBError):
pass
class OverlapError(NilmDBError):
pass
# Helper that lets us pass a Pytables table into bisect
class BisectableTable(object):
def __init__(self, table):
self.table = table
def __getitem__(self, index):
return self.table[index][0]
class NilmDB(object):
verbose = 0
def __init__(self, basepath, sync=True, max_results=None):
# set up path
self.basepath = os.path.abspath(basepath.rstrip('/'))
# Create the database path if it doesn't exist
try:
os.makedirs(self.basepath)
except OSError as e:
if e.errno != errno.EEXIST:
raise IOError("can't create tree " + self.basepath)
# Our HD5 file goes inside it
h5filename = os.path.abspath(self.basepath + "/data.h5")
self.h5file = tables.openFile(h5filename, "a", "NILM Database")
# SQLite database too
sqlfilename = os.path.abspath(self.basepath + "/data.sql")
# We use check_same_thread = False, assuming that the rest
# of the code (e.g. Server) will be smart and not access this
# database from multiple threads simultaneously. That requirement
# may be relaxed later.
self.con = sqlite3.connect(sqlfilename, check_same_thread = False)
self._sql_schema_update()
# See big comment at top about the performance implications of this
if sync:
self.con.execute("PRAGMA synchronous=FULL")
else:
self.con.execute("PRAGMA synchronous=OFF")
# Approximate largest number of elements that we want to send
# in a single reply (for stream_intervals, stream_extract)
if max_results:
self.max_results = max_results
else:
self.max_results = 16384
self.opened = True
# Cached intervals
self._cached_iset = {}
def __del__(self):
if "opened" in self.__dict__: # pragma: no cover
fprintf(sys.stderr,
"error: NilmDB.close() wasn't called, path %s",
self.basepath)
def get_basepath(self):
return self.basepath
def close(self):
if self.con:
self.con.commit()
self.con.close()
self.h5file.close()
del self.opened
def _sql_schema_update(self):
cur = self.con.cursor()
version = cur.execute("PRAGMA user_version").fetchone()[0]
oldversion = version
while version in _sql_schema_updates:
cur.executescript(_sql_schema_updates[version])
version = version + 1
if self.verbose: # pragma: no cover
printf("Schema updated to %d\n", version)
if version != oldversion:
with self.con:
cur.execute("PRAGMA user_version = {v:d}".format(v=version))
def _get_intervals(self, stream_id):
"""
Return a mutable IntervalSet corresponding to the given stream ID.
"""
# Load from database if not cached
if stream_id not in self._cached_iset:
iset = IntervalSet()
result = self.con.execute("SELECT start_time, end_time, "
"start_pos, end_pos "
"FROM ranges "
"WHERE stream_id=?", (stream_id,))
try:
for (start_time, end_time, start_pos, end_pos) in result:
iset += DBInterval(start_time, end_time,
start_time, end_time,
start_pos, end_pos)
except IntervalError as e: # pragma: no cover
raise NilmDBError("unexpected overlap in ranges table!")
self._cached_iset[stream_id] = iset
# Return cached value
return self._cached_iset[stream_id]
# TODO: Split add_interval into two pieces, one to add
# and one to flush to disk?
# Need to think about this. Basic problem is that we can't
# mess with intervals once they're in the IntervalSet,
# without mucking with bxinterval internals.
# Maybe add a separate optimization step?
# Join intervals that have a fairly small gap between them
def _add_interval(self, stream_id, interval, start_pos, end_pos):
"""
Add interval to the internal interval cache, and to the database.
Note: arguments must be ints (not numpy.int64, etc)
"""
# Ensure this stream's intervals are cached, and add the new
# interval to that cache.
iset = self._get_intervals(stream_id)
try:
iset += DBInterval(interval.start, interval.end,
interval.start, interval.end,
start_pos, end_pos)
except IntervalError as e: # pragma: no cover
raise NilmDBError("new interval overlaps existing data")
# Insert into the database
self.con.execute("INSERT INTO ranges "
"(stream_id,start_time,end_time,start_pos,end_pos) "
"VALUES (?,?,?,?,?)",
(stream_id, interval.start, interval.end,
int(start_pos), int(end_pos)))
self.con.commit()
def stream_list(self, path = None, layout = None):
"""Return list of [path, layout] lists of all streams
in the database.
If path is specified, include only streams with a path that
matches the given string.
If layout is specified, include only streams with a layout
that matches the given string.
"""
where = "WHERE 1=1"
params = ()
if layout:
where += " AND layout=?"
params += (layout,)
if path:
where += " AND path=?"
params += (path,)
result = self.con.execute("SELECT path, layout "
"FROM streams " + where, params).fetchall()
return sorted(list(x) for x in result)
def stream_intervals(self, path, start = None, end = None):
"""
Returns (intervals, restart) tuple.
intervals is a list of [start,end] timestamps of all intervals
that exist for path, between start and end.
restart, if nonzero, means that there were too many results to
return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated,
and a new request with a start time of 'restart' will fetch
the next block of data.
"""
stream_id = self._stream_id(path)
intervals = self._get_intervals(stream_id)
requested = Interval(start or 0, end or 1e12)
result = []
for n, i in enumerate(intervals.intersection(requested)):
if n >= self.max_results:
restart = i.start
break
result.append([i.start, i.end])
else:
restart = 0
return (result, restart)
def stream_create(self, path, layout_name):
"""Create a new table in the database.
path: path to the data (e.g. '/newton/prep').
Paths must contain at least two elements, e.g.:
/newton/prep
/newton/raw
/newton/upstairs/prep
/newton/upstairs/raw
layout_name: string for nilmdb.layout.get_named(), e.g. 'float32_8'
"""
if path[0] != '/':
raise ValueError("paths must start with /")
[ group, node ] = path.rsplit("/", 1)
if group == '':
raise ValueError("invalid path")
# Make the group structure, one element at a time
group_path = group.lstrip('/').split("/")
for i in range(len(group_path)):
parent = "/" + "/".join(group_path[0:i])
child = group_path[i]
try:
self.h5file.createGroup(parent, child)
except tables.NodeError:
pass
# Get description
try:
desc = nilmdb.layout.get_named(layout_name).description()
except KeyError:
raise ValueError("no such layout")
# Estimated table size (for PyTables optimization purposes): assume
# 3 months worth of data at 8 KHz. It's OK if this is wrong.
exp_rows = 8000 * 60*60*24*30*3
# Create the table
table = self.h5file.createTable(group, node,
description = desc,
expectedrows = exp_rows)
# Insert into SQL database once the PyTables is happy
with self.con as con:
con.execute("INSERT INTO streams (path, layout) VALUES (?,?)",
(path, layout_name))
def _stream_id(self, path):
"""Return unique stream ID"""
result = self.con.execute("SELECT id FROM streams WHERE path=?",
(path,)).fetchone()
if result is None:
raise StreamError("No stream at path " + path)
return result[0]
def stream_set_metadata(self, path, data):
"""Set stream metadata from a dictionary, e.g.
{ description = 'Downstairs lighting',
v_scaling = 123.45 }
This replaces all existing metadata.
"""
stream_id = self._stream_id(path)
with self.con as con:
con.execute("DELETE FROM metadata "
"WHERE stream_id=?", (stream_id,))
for key in data:
if data[key] != '':
con.execute("INSERT INTO metadata VALUES (?, ?, ?)",
(stream_id, key, data[key]))
def stream_get_metadata(self, path):
"""Return stream metadata as a dictionary."""
stream_id = self._stream_id(path)
result = self.con.execute("SELECT metadata.key, metadata.value "
"FROM metadata "
"WHERE metadata.stream_id=?", (stream_id,))
data = {}
for (key, value) in result:
data[key] = value
return data
def stream_update_metadata(self, path, newdata):
"""Update stream metadata from a dictionary"""
data = self.stream_get_metadata(path)
data.update(newdata)
self.stream_set_metadata(path, data)
def stream_insert(self, path, parser, old_timestamp = None):
"""Insert new data into the database.
path: Path at which to add the data
parser: nilmdb.layout.Parser instance full of data to insert
"""
if (not parser.min_timestamp or not parser.max_timestamp or
not len(parser.data)):
raise StreamError("no data provided")
# If we were provided with an old timestamp, the expectation
# is that the client has a contiguous block of time it is sending,
# but it's doing it over multiple calls to stream_insert.
# old_timestamp is the max_timestamp of the previous insert.
# To make things continuous, use that as our starting timestamp
# instead of what the parser found.
if old_timestamp:
min_timestamp = old_timestamp
else:
min_timestamp = parser.min_timestamp
# First check for basic overlap using timestamp info given.
stream_id = self._stream_id(path)
iset = self._get_intervals(stream_id)
interval = Interval(min_timestamp, parser.max_timestamp)
if iset.intersects(interval):
raise OverlapError("new data overlaps existing data: "
+ str(iset & interval))
# Insert the data into pytables
table = self.h5file.getNode(path)
row_start = table.nrows
table.append(parser.data)
row_end = table.nrows
table.flush()
# Insert the record into the sql database.
# Casts are to convert from numpy.int64.
self._add_interval(stream_id, interval, int(row_start), int(row_end))
# And that's all
return "ok"
def _find_start(self, table, interval):
"""
Given a DBInterval, find the row in the database that
corresponds to the start time. Return the first database
position with a timestamp (first element) greater than or
equal to 'start'.
"""
# Optimization for the common case where an interval wasn't truncated
if interval.start == interval.db_start:
return interval.db_startpos
return bisect.bisect_left(BisectableTable(table),
interval.start,
interval.db_startpos,
interval.db_endpos)
def _find_end(self, table, interval):
"""
Given a DBInterval, find the row in the database that follows
the end time. Return the first database position after the
row with timestamp (first element) greater than or equal
to 'end'.
"""
# Optimization for the common case where an interval wasn't truncated
if interval.end == interval.db_end:
return interval.db_endpos
# Note that we still use bisect_left here, because we don't
# want to include the given timestamp in the results. This is
# so a queries like 1:00 -> 2:00 and 2:00 -> 3:00 return
# non-overlapping data.
return bisect.bisect_left(BisectableTable(table),
interval.end,
interval.db_startpos,
interval.db_endpos)
def stream_extract(self, path, start = None, end = None, count = False):
"""
Returns (data, restart) tuple.
data is a list of raw data from the database, suitable for
passing to e.g. nilmdb.layout.Formatter to translate into
textual form.
restart, if nonzero, means that there were too many results to
return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated,
and a new request with a start time of 'restart' will fetch
the next block of data.
count, if true, means to not return raw data, but just the count
of rows that would have been returned. This is much faster
than actually fetching the data. It is not limited by
max_results.
"""
table = self.h5file.getNode(path)
stream_id = self._stream_id(path)
intervals = self._get_intervals(stream_id)
requested = Interval(start or 0, end or 1e12)
result = []
matched = 0
remaining = self.max_results
restart = 0
for interval in intervals.intersection(requested):
# Reading single rows from the table is too slow, so
# we use two bisections to find both the starting and
# ending row for this particular interval, then
# read the entire range as one slice.
row_start = self._find_start(table, interval)
row_end = self._find_end(table, interval)
if count:
matched += row_end - row_start
continue
# Shorten it if we'll hit the maximum number of results
row_max = row_start + remaining
if row_max < row_end:
row_end = row_max
restart = table[row_max][0]
# Gather these results up
result.extend(table[row_start:row_end])
# Count them
remaining -= row_end - row_start
if restart:
break
if count:
return matched
return (result, restart)

View File

@@ -0,0 +1 @@
# Command line scripts

25
nilmdb/scripts/nilmdb_fsck.py Executable file
View File

@@ -0,0 +1,25 @@
#!/usr/bin/python
import nilmdb.fsck
import argparse
import os
import sys
def main():
"""Main entry point for the 'nilmdb-fsck' command line script"""
parser = argparse.ArgumentParser(
description = 'Check database consistency',
formatter_class = argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("-V", "--version", action="version",
version = nilmdb.__version__)
parser.add_argument("-f", "--fix", action="store_true",
default=False, help = 'Fix errors when possible '
'(which may involve removing data)')
parser.add_argument('database', help = 'Database directory')
args = parser.parse_args()
nilmdb.fsck.Fsck(args.database, args.fix).check()
if __name__ == "__main__":
main()

87
nilmdb/scripts/nilmdb_server.py Executable file
View File

@@ -0,0 +1,87 @@
#!/usr/bin/python
import nilmdb.server
import argparse
import os
import socket
def main():
"""Main entry point for the 'nilmdb-server' command line script"""
parser = argparse.ArgumentParser(
description = 'Run the NilmDB server',
formatter_class = argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("-V", "--version", action="version",
version = nilmdb.__version__)
group = parser.add_argument_group("Standard options")
group.add_argument('-a', '--address',
help = 'Only listen on the given address',
default = '0.0.0.0')
group.add_argument('-p', '--port', help = 'Listen on the given port',
type = int, default = 12380)
group.add_argument('-d', '--database', help = 'Database directory',
default = "./db")
group.add_argument('-q', '--quiet', help = 'Silence output',
action = 'store_true')
group.add_argument('-t', '--traceback',
help = 'Provide tracebacks in client errors',
action = 'store_true', default = False)
group = parser.add_argument_group("Debug options")
group.add_argument('-y', '--yappi', help = 'Run under yappi profiler and '
'invoke interactive shell afterwards',
action = 'store_true')
args = parser.parse_args()
# Create database object. Needs to be serialized before passing
# to the Server.
db = nilmdb.utils.serializer_proxy(nilmdb.server.NilmDB)(args.database)
# Configure the server
if args.quiet:
embedded = True
else:
embedded = False
server = nilmdb.server.Server(db,
host = args.address,
port = args.port,
embedded = embedded,
force_traceback = args.traceback)
# Print info
if not args.quiet:
print "Version: %s" % nilmdb.__version__
print "Database: %s" % (os.path.realpath(args.database))
if args.address == '0.0.0.0' or args.address == '::':
host = socket.getfqdn()
else:
host = args.address
print "Server URL: http://%s:%d/" % ( host, args.port)
print "----"
# Run it
if args.yappi:
print "Running in yappi"
try:
import yappi
yappi.start()
server.start(blocking = True)
finally:
yappi.stop()
yappi.print_stats(sort_type = yappi.SORTTYPE_TTOT, limit = 50)
from IPython import embed
embed(header = "Use the yappi object to explore further, "
"quit to exit")
else:
server.start(blocking = True)
# Clean up
if not args.quiet:
print "Closing database"
db.close()
if __name__ == "__main__":
main()

10
nilmdb/scripts/nilmtool.py Executable file
View File

@@ -0,0 +1,10 @@
#!/usr/bin/python
import nilmdb.cmdline
def main():
"""Main entry point for the 'nilmtool' command line script"""
nilmdb.cmdline.Cmdline().run()
if __name__ == "__main__":
main()

View File

@@ -1,69 +0,0 @@
import Queue
import threading
import sys
# This file provides a class that will wrap an object and serialize
# all calls to its methods. All calls to that object will be queued
# and executed from a single thread, regardless of which thread makes
# the call.
# Based partially on http://stackoverflow.com/questions/2642515/
class SerializerThread(threading.Thread):
"""Thread that retrieves call information from the queue, makes the
call, and returns the results."""
def __init__(self, call_queue):
threading.Thread.__init__(self)
self.call_queue = call_queue
def run(self):
while True:
result_queue, func, args, kwargs = self.call_queue.get()
# Terminate if result_queue is None
if result_queue is None:
return
try:
result = func(*args, **kwargs) # wrapped
except:
result_queue.put((sys.exc_info(), None))
else:
result_queue.put((None, result))
class WrapCall(object):
"""Wrap a callable using the given queues"""
def __init__(self, call_queue, result_queue, func):
self.call_queue = call_queue
self.result_queue = result_queue
self.func = func
def __call__(self, *args, **kwargs):
self.call_queue.put((self.result_queue, self.func, args, kwargs))
( exc_info, result ) = self.result_queue.get()
if exc_info is None:
return result
else:
raise exc_info[0], exc_info[1], exc_info[2]
class WrapObject(object):
"""Wrap all calls to methods in a target object with WrapCall"""
def __init__(self, target):
self.__wrap_target = target
self.__wrap_call_queue = Queue.Queue()
self.__wrap_serializer = SerializerThread(self.__wrap_call_queue)
self.__wrap_serializer.daemon = True
self.__wrap_serializer.start()
def __getattr__(self, key):
"""Wrap methods of self.__wrap_target in a WrapCall instance"""
func = getattr(self.__wrap_target, key)
if not callable(func):
raise TypeError("Can't serialize attribute %r (type: %s)"
% (key, type(func)))
result_queue = Queue.Queue()
return WrapCall(self.__wrap_call_queue, result_queue, func)
def __del__(self):
self.__wrap_call_queue.put((None, None, None, None))
self.__wrap_serializer.join()

View File

@@ -1,403 +0,0 @@
"""CherryPy-based server for accessing NILM database via HTTP"""
# Need absolute_import so that "import nilmdb" won't pull in nilmdb.py,
# but will pull the nilmdb module instead.
from __future__ import absolute_import
import nilmdb
from nilmdb.printf import *
import cherrypy
import sys
import time
import os
import simplejson as json
try:
import cherrypy
cherrypy.tools.json_out
except: # pragma: no cover
sys.stderr.write("Cherrypy 3.2+ required\n")
sys.exit(1)
class NilmApp(object):
def __init__(self, db):
self.db = db
version = "1.1"
class Root(NilmApp):
"""Root application for NILM database"""
def __init__(self, db, version):
super(Root, self).__init__(db)
self.server_version = version
# /
@cherrypy.expose
def index(self):
raise cherrypy.NotFound()
# /favicon.ico
@cherrypy.expose
def favicon_ico(self):
raise cherrypy.NotFound()
# /version
@cherrypy.expose
@cherrypy.tools.json_out()
def version(self):
return self.server_version
# /dbpath
@cherrypy.expose
@cherrypy.tools.json_out()
def dbpath(self):
return self.db.get_basepath()
# /dbsize
@cherrypy.expose
@cherrypy.tools.json_out()
def dbsize(self):
return nilmdb.du.du(self.db.get_basepath())
class Stream(NilmApp):
"""Stream-specific operations"""
# /stream/list
# /stream/list?layout=PrepData
# /stream/list?path=/newton/prep
@cherrypy.expose
@cherrypy.tools.json_out()
def list(self, path = None, layout = None):
"""List all streams in the database. With optional path or
layout parameter, just list streams that match the given path
or layout"""
return self.db.stream_list(path, layout)
# /stream/create?path=/newton/prep&layout=PrepData
@cherrypy.expose
@cherrypy.tools.json_out()
def create(self, path, layout):
"""Create a new stream in the database. Provide path
and one of the nilmdb.layout.layouts keys.
"""
try:
return self.db.stream_create(path, layout)
except Exception as e:
message = sprintf("%s: %s", type(e).__name__, e.message)
raise cherrypy.HTTPError("400 Bad Request", message)
# /stream/get_metadata?path=/newton/prep
# /stream/get_metadata?path=/newton/prep&key=foo&key=bar
@cherrypy.expose
@cherrypy.tools.json_out()
def get_metadata(self, path, key=None):
"""Get metadata for the named stream. If optional
key parameters are specified, only return metadata
matching the given keys."""
try:
data = self.db.stream_get_metadata(path)
except nilmdb.nilmdb.StreamError as e:
raise cherrypy.HTTPError("404 Not Found", e.message)
if key is None: # If no keys specified, return them all
key = data.keys()
elif not isinstance(key, list):
key = [ key ]
result = {}
for k in key:
if k in data:
result[k] = data[k]
else: # Return "None" for keys with no matching value
result[k] = None
return result
# /stream/set_metadata?path=/newton/prep&data=<json>
@cherrypy.expose
@cherrypy.tools.json_out()
def set_metadata(self, path, data):
"""Set metadata for the named stream, replacing any
existing metadata. Data should be a json-encoded
dictionary"""
try:
data_dict = json.loads(data)
self.db.stream_set_metadata(path, data_dict)
except Exception as e:
message = sprintf("%s: %s", type(e).__name__, e.message)
raise cherrypy.HTTPError("400 Bad Request", message)
return "ok"
# /stream/update_metadata?path=/newton/prep&data=<json>
@cherrypy.expose
@cherrypy.tools.json_out()
def update_metadata(self, path, data):
"""Update metadata for the named stream. Data
should be a json-encoded dictionary"""
try:
data_dict = json.loads(data)
self.db.stream_update_metadata(path, data_dict)
except Exception as e:
message = sprintf("%s: %s", type(e).__name__, e.message)
raise cherrypy.HTTPError("400 Bad Request", message)
return "ok"
# /stream/insert?path=/newton/prep
@cherrypy.expose
@cherrypy.tools.json_out()
#@cherrypy.tools.disable_prb()
def insert(self, path, old_timestamp = None):
"""
Insert new data into the database. Provide textual data
(matching the path's layout) as a HTTP PUT.
old_timestamp is used when making multiple, split-up insertions
for a larger contiguous block of data. The first insert
will return the maximum timestamp that it saw, and the second
insert should provide this timestamp as an argument. This is
used to extend the previous database interval rather than
start a new one.
"""
# Important that we always read the input before throwing any
# errors, to keep lengths happy for persistent connections.
# However, CherryPy 3.2.2 has a bug where this fails for GET
# requests, so catch that. (issue #1134)
try:
body = cherrypy.request.body.read()
except TypeError:
raise cherrypy.HTTPError("400 Bad Request", "No request body")
# Check path and get layout
streams = self.db.stream_list(path = path)
if len(streams) != 1:
raise cherrypy.HTTPError("404 Not Found", "No such stream")
layout = streams[0][1]
# Parse the input data
try:
parser = nilmdb.layout.Parser(layout)
parser.parse(body)
except nilmdb.layout.ParserError as e:
raise cherrypy.HTTPError("400 Bad Request",
"Error parsing input data: " +
e.message)
# Now do the nilmdb insert, passing it the parser full of data.
try:
if old_timestamp:
old_timestamp = float(old_timestamp)
result = self.db.stream_insert(path, parser, old_timestamp)
except nilmdb.nilmdb.NilmDBError as e:
raise cherrypy.HTTPError("400 Bad Request", e.message)
# Return the maximum timestamp that we saw. The client will
# return this back to us as the old_timestamp parameter, if
# it has more data to send.
return ("ok", parser.max_timestamp)
# /stream/intervals?path=/newton/prep
# /stream/intervals?path=/newton/prep&start=1234567890.0&end=1234567899.0
@cherrypy.expose
def intervals(self, path, start = None, end = None):
"""
Get intervals from backend database. Streams the resulting
intervals as JSON strings separated by newlines. This may
make multiple requests to the nilmdb backend to avoid causing
it to block for too long.
"""
if start is not None:
start = float(start)
if end is not None:
end = float(end)
if start is not None and end is not None:
if end < start:
raise cherrypy.HTTPError("400 Bad Request",
"end before start")
streams = self.db.stream_list(path = path)
if len(streams) != 1:
raise cherrypy.HTTPError("404 Not Found", "No such stream")
def content(start, end):
# Note: disable response.stream below to get better debug info
# from tracebacks in this subfunction.
while True:
(intervals, restart) = self.db.stream_intervals(path,start,end)
response = ''.join([ json.dumps(i) + "\n" for i in intervals ])
yield response
if restart == 0:
break
start = restart
return content(start, end)
intervals._cp_config = { 'response.stream': True } # chunked HTTP response
# /stream/extract?path=/newton/prep&start=1234567890.0&end=1234567899.0
@cherrypy.expose
def extract(self, path, start = None, end = None, count = False):
"""
Extract data from backend database. Streams the resulting
entries as ASCII text lines separated by newlines. This may
make multiple requests to the nilmdb backend to avoid causing
it to block for too long.
Add count=True to return a count rather than actual data.
"""
if start is not None:
start = float(start)
if end is not None:
end = float(end)
# Check parameters
if start is not None and end is not None:
if end < start:
raise cherrypy.HTTPError("400 Bad Request",
"end before start")
# Check path and get layout
streams = self.db.stream_list(path = path)
if len(streams) != 1:
raise cherrypy.HTTPError("404 Not Found", "No such stream")
layout = streams[0][1]
# Get formatter
formatter = nilmdb.layout.Formatter(layout)
def content(start, end, count):
# Note: disable response.stream below to get better debug info
# from tracebacks in this subfunction.
if count:
matched = self.db.stream_extract(path, start, end, count)
yield sprintf("%d\n", matched)
return
while True:
(data, restart) = self.db.stream_extract(path, start, end)
# Format the data and yield it
yield formatter.format(data)
if restart == 0:
return
start = restart
return content(start, end, count)
extract._cp_config = { 'response.stream': True } # chunked HTTP response
class Exiter(object):
"""App that exits the server, for testing"""
@cherrypy.expose
def index(self):
cherrypy.response.headers['Content-Type'] = 'text/plain'
def content():
yield 'Exiting by request'
raise SystemExit
return content()
index._cp_config = { 'response.stream': True }
class Server(object):
def __init__(self, db, host = '127.0.0.1', port = 8080,
stoppable = False, # whether /exit URL exists
embedded = True, # hide diagnostics and output, etc
fast_shutdown = False, # don't wait for clients to disconn.
force_traceback = False # include traceback in all errors
):
self.version = version
# Need to wrap DB object in a serializer because we'll call
# into it from separate threads.
self.embedded = embedded
self.db = nilmdb.serializer.WrapObject(db)
cherrypy.config.update({
'server.socket_host': host,
'server.socket_port': port,
'engine.autoreload_on': False,
'server.max_request_body_size': 4*1024*1024,
'error_page.default': self.json_error_page,
})
if self.embedded:
cherrypy.config.update({ 'environment': 'embedded' })
# Send tracebacks in error responses. They're hidden by the
# error_page function for client errors (code 400-499).
cherrypy.config.update({ 'request.show_tracebacks' : True })
self.force_traceback = force_traceback
cherrypy.tree.apps = {}
cherrypy.tree.mount(Root(self.db, self.version), "/")
cherrypy.tree.mount(Stream(self.db), "/stream")
if stoppable:
cherrypy.tree.mount(Exiter(), "/exit")
# Shutdowns normally wait for clients to disconnect. To speed
# up tests, set fast_shutdown = True
if fast_shutdown:
# Setting timeout to 0 triggers os._exit(70) at shutdown, grr...
cherrypy.server.shutdown_timeout = 0.01
else:
cherrypy.server.shutdown_timeout = 5
def json_error_page(self, status, message, traceback, version):
"""Return a custom error page in JSON so the client can parse it"""
errordata = { "status" : status,
"message" : message,
"traceback" : traceback }
# Don't send a traceback if the error was 400-499 (client's fault)
try:
code = int(status.split()[0])
if not self.force_traceback:
if code >= 400 and code <= 499:
errordata["traceback"] = ""
except Exception as e: # pragma: no cover
pass
# Override the response type, which was previously set to text/html
cherrypy.serving.response.headers['Content-Type'] = (
"application/json;charset=utf-8" )
# Undo the HTML escaping that cherrypy's get_error_page function applies
# (cherrypy issue 1135)
for k, v in errordata.iteritems():
v = v.replace("&lt;","<")
v = v.replace("&gt;",">")
v = v.replace("&amp;","&")
errordata[k] = v
return json.dumps(errordata, separators=(',',':'))
def start(self, blocking = False, event = None):
if not self.embedded: # pragma: no cover
# Handle signals nicely
if hasattr(cherrypy.engine, "signal_handler"):
cherrypy.engine.signal_handler.subscribe()
if hasattr(cherrypy.engine, "console_control_handler"):
cherrypy.engine.console_control_handler.subscribe()
# Cherrypy stupidly calls os._exit(70) when it can't bind the
# port. At least try to print a reasonable error and continue
# in this case, rather than just dying silently (as we would
# otherwise do in embedded mode)
real_exit = os._exit
def fake_exit(code): # pragma: no cover
if code == os.EX_SOFTWARE:
fprintf(sys.stderr, "error: CherryPy called os._exit!\n")
else:
real_exit(code)
os._exit = fake_exit
cherrypy.engine.start()
os._exit = real_exit
if event is not None:
event.set()
if blocking:
try:
cherrypy.engine.wait(cherrypy.engine.states.EXITING,
interval = 0.1, channel = 'main')
except (KeyboardInterrupt, IOError): # pragma: no cover
cherrypy.engine.log('Keyboard Interrupt: shutting down bus')
cherrypy.engine.exit()
except SystemExit: # pragma: no cover
cherrypy.engine.log('SystemExit raised: shutting down bus')
cherrypy.engine.exit()
raise
def stop(self):
cherrypy.engine.exit()

21
nilmdb/server/__init__.py Normal file
View File

@@ -0,0 +1,21 @@
"""nilmdb.server"""
from __future__ import absolute_import
# Try to set up pyximport to automatically rebuild Cython modules. If
# this doesn't work, it's OK, as long as the modules were built externally.
# (e.g. python setup.py build_ext --inplace)
try: # pragma: no cover
import Cython
import distutils.version
if (distutils.version.LooseVersion(Cython.__version__) <
distutils.version.LooseVersion("0.17")): # pragma: no cover
raise ImportError("Cython version too old")
import pyximport
pyximport.install(inplace = True, build_in_temp = False)
except (ImportError, TypeError): # pragma: no cover
pass
from nilmdb.server.nilmdb import NilmDB
from nilmdb.server.server import Server, wsgi_application
from nilmdb.server.errors import NilmDBError, StreamError, OverlapError

618
nilmdb/server/bulkdata.py Normal file
View File

@@ -0,0 +1,618 @@
# Fixed record size bulk data storage
# Need absolute_import so that "import nilmdb" won't pull in
# nilmdb.py, but will pull the parent nilmdb module instead.
from __future__ import absolute_import
from __future__ import division
from nilmdb.utils.printf import *
from nilmdb.utils.time import timestamp_to_string as timestamp_to_string
import nilmdb.utils
import os
import cPickle as pickle
import re
import sys
import tempfile
import nilmdb.utils.lock
from . import rocket
# Up to 256 open file descriptors at any given time.
# These variables are global so they can be used in the decorator arguments.
table_cache_size = 32
fd_cache_size = 8
@nilmdb.utils.must_close(wrap_verify = False)
class BulkData(object):
def __init__(self, basepath, **kwargs):
self.basepath = basepath
self.root = os.path.join(self.basepath, "data")
self.lock = self.root + ".lock"
self.lockfile = None
# Tuneables
if "file_size" in kwargs:
self.file_size = kwargs["file_size"]
else:
# Default to approximately 128 MiB per file
self.file_size = 128 * 1024 * 1024
if "files_per_dir" in kwargs:
self.files_per_dir = kwargs["files_per_dir"]
else:
# 32768 files per dir should work even on FAT32
self.files_per_dir = 32768
# Make root path
if not os.path.isdir(self.root):
os.mkdir(self.root)
# Create the lock
self.lockfile = open(self.lock, "w")
if not nilmdb.utils.lock.exclusive_lock(self.lockfile):
raise IOError('database at "' + self.basepath +
'" is already locked by another process')
def close(self):
self.getnode.cache_remove_all()
if self.lockfile:
nilmdb.utils.lock.exclusive_unlock(self.lockfile)
self.lockfile.close()
try:
os.unlink(self.lock)
except OSError: # pragma: no cover
pass
self.lockfile = None
def _encode_filename(self, path):
# Encode all paths to UTF-8, regardless of sys.getfilesystemencoding(),
# because we want to be able to represent all code points and the user
# will never be directly exposed to filenames. We can then do path
# manipulations on the UTF-8 directly.
if isinstance(path, unicode):
return path.encode('utf-8')
return path
def _create_check_ospath(self, ospath):
if ospath[-1] == '/':
raise ValueError("invalid path; should not end with a /")
if Table.exists(ospath):
raise ValueError("stream already exists at this path")
if os.path.isdir(ospath):
# Look for any files in subdirectories. Fully empty subdirectories
# are OK; they might be there during a rename
for (root, dirs, files) in os.walk(ospath):
if len(files):
raise ValueError(
"non-empty subdirs of this path already exist")
def _create_parents(self, unicodepath):
"""Verify the path name, and create parent directories if they
don't exist. Returns a list of elements that got created."""
path = self._encode_filename(unicodepath)
if path[0] != '/':
raise ValueError("paths must start with /")
[ group, node ] = path.rsplit("/", 1)
if group == '':
raise ValueError("invalid path; path must contain at least one "
"folder")
if node == '':
raise ValueError("invalid path; should not end with a /")
if not Table.valid_path(path):
raise ValueError("path name is invalid or contains reserved words")
# Create the table's base dir. Note that we make a
# distinction here between NilmDB paths (always Unix style,
# split apart manually) and OS paths (built up with
# os.path.join)
# Make directories leading up to this one
elements = path.lstrip('/').split('/')
made_dirs = []
try:
# Make parent elements
for i in range(len(elements)):
ospath = os.path.join(self.root, *elements[0:i])
if Table.exists(ospath):
raise ValueError("path is subdir of existing node")
if not os.path.isdir(ospath):
os.mkdir(ospath)
made_dirs.append(ospath)
except Exception as e:
# Try to remove paths that we created; ignore errors
exc_info = sys.exc_info()
for ospath in reversed(made_dirs): # pragma: no cover (hard to hit)
try:
os.rmdir(ospath)
except OSError:
pass
raise exc_info[1], None, exc_info[2]
return elements
def create(self, unicodepath, layout_name):
"""
unicodepath: path to the data (e.g. u'/newton/prep').
Paths must contain at least two elements, e.g.:
/newton/prep
/newton/raw
/newton/upstairs/prep
/newton/upstairs/raw
layout_name: string for nilmdb.layout.get_named(), e.g. 'float32_8'
"""
elements = self._create_parents(unicodepath)
# Make the final dir
ospath = os.path.join(self.root, *elements)
self._create_check_ospath(ospath)
os.mkdir(ospath)
try:
# Write format string to file
Table.create(ospath, layout_name, self.file_size,
self.files_per_dir)
# Open and cache it
self.getnode(unicodepath)
except Exception:
exc_info = sys.exc_info()
try:
os.rmdir(ospath)
except OSError:
pass
raise exc_info[1], None, exc_info[2]
# Success
return
def _remove_leaves(self, unicodepath):
"""Remove empty directories starting at the leaves of unicodepath"""
path = self._encode_filename(unicodepath)
elements = path.lstrip('/').split('/')
for i in reversed(range(len(elements))):
ospath = os.path.join(self.root, *elements[0:i+1])
try:
os.rmdir(ospath)
except OSError:
pass
def rename(self, oldunicodepath, newunicodepath):
"""Move entire tree from 'oldunicodepath' to
'newunicodepath'"""
oldpath = self._encode_filename(oldunicodepath)
newpath = self._encode_filename(newunicodepath)
# Get OS paths
oldelements = oldpath.lstrip('/').split('/')
oldospath = os.path.join(self.root, *oldelements)
newelements = newpath.lstrip('/').split('/')
newospath = os.path.join(self.root, *newelements)
# Basic checks
if oldospath == newospath:
raise ValueError("old and new paths are the same")
# Move the table to a temporary location
tmpdir = tempfile.mkdtemp(prefix = "rename-", dir = self.root)
tmppath = os.path.join(tmpdir, "table")
os.rename(oldospath, tmppath)
try:
# Check destination path
self._create_check_ospath(newospath)
# Create parent dirs for new location
self._create_parents(newunicodepath)
# Move table into new location
os.rename(tmppath, newospath)
except Exception:
# On failure, move the table back to original path
os.rename(tmppath, oldospath)
os.rmdir(tmpdir)
raise
# Prune old dirs
self._remove_leaves(oldunicodepath)
os.rmdir(tmpdir)
def destroy(self, unicodepath):
"""Fully remove all data at a particular path. No way to undo
it! The group/path structure is removed, too."""
path = self._encode_filename(unicodepath)
# Get OS path
elements = path.lstrip('/').split('/')
ospath = os.path.join(self.root, *elements)
# Remove Table object from cache
self.getnode.cache_remove(self, unicodepath)
# Remove the contents of the target directory
if not Table.exists(ospath):
raise ValueError("nothing at that path")
for (root, dirs, files) in os.walk(ospath, topdown = False):
for name in files:
os.remove(os.path.join(root, name))
for name in dirs:
os.rmdir(os.path.join(root, name))
# Remove leftover empty directories
self._remove_leaves(unicodepath)
# Cache open tables
@nilmdb.utils.lru_cache(size = table_cache_size,
onremove = lambda x: x.close())
def getnode(self, unicodepath):
"""Return a Table object corresponding to the given database
path, which must exist."""
path = self._encode_filename(unicodepath)
elements = path.lstrip('/').split('/')
ospath = os.path.join(self.root, *elements)
return Table(ospath)
@nilmdb.utils.must_close(wrap_verify = False)
class Table(object):
"""Tools to help access a single table (data at a specific OS path)."""
# See design.md for design details
# Class methods, to help keep format details in this class.
@classmethod
def valid_path(cls, root):
"""Return True if a root path is a valid name"""
return "_format" not in root.split("/")
@classmethod
def exists(cls, root):
"""Return True if a table appears to exist at this OS path"""
return os.path.isfile(os.path.join(root, "_format"))
@classmethod
def create(cls, root, layout, file_size, files_per_dir):
"""Initialize a table at the given OS path with the
given layout string"""
# Calculate rows per file so that each file is approximately
# file_size bytes.
rkt = rocket.Rocket(layout, None)
rows_per_file = max(file_size // rkt.binary_size, 1)
rkt.close()
fmt = { "rows_per_file": rows_per_file,
"files_per_dir": files_per_dir,
"layout": layout,
"version": 3 }
with open(os.path.join(root, "_format"), "wb") as f:
pickle.dump(fmt, f, 2)
# Normal methods
def __init__(self, root):
"""'root' is the full OS path to the directory of this table"""
self.root = root
# Load the format
with open(os.path.join(self.root, "_format"), "rb") as f:
fmt = pickle.load(f)
if fmt["version"] != 3: # pragma: no cover
# Old versions used floating point timestamps, which aren't
# valid anymore.
raise NotImplementedError("old version " + str(fmt["version"]) +
" bulk data store is not supported")
self.rows_per_file = fmt["rows_per_file"]
self.files_per_dir = fmt["files_per_dir"]
self.layout = fmt["layout"]
# Use rocket to get row size and file size
rkt = rocket.Rocket(self.layout, None)
self.row_size = rkt.binary_size
self.file_size = rkt.binary_size * self.rows_per_file
rkt.close()
# Find nrows
self.nrows = self._get_nrows()
def close(self):
self.file_open.cache_remove_all()
# Internal helpers
def _get_nrows(self):
"""Find nrows by locating the lexicographically last filename
and using its size"""
# Note that this just finds a 'nrows' that is guaranteed to be
# greater than the row number of any piece of data that
# currently exists, not necessarily all data that _ever_
# existed.
regex = re.compile("^[0-9a-f]{4,}$")
# Find the last directory. We sort and loop through all of them,
# starting with the numerically greatest, because the dirs could be
# empty if something was deleted but the directory was unexpectedly
# not deleted.
subdirs = sorted(filter(regex.search, os.listdir(self.root)),
key = lambda x: int(x, 16), reverse = True)
for subdir in subdirs:
# Now find the last file in that dir
path = os.path.join(self.root, subdir)
files = filter(regex.search, os.listdir(path))
if not files: # pragma: no cover (shouldn't occur)
# Empty dir: try the next one
continue
# Find the numerical max
filename = max(files, key = lambda x: int(x, 16))
offset = os.path.getsize(os.path.join(self.root, subdir, filename))
# Convert to row number
return self._row_from_offset(subdir, filename, offset)
# No files, so no data
return 0
def _offset_from_row(self, row):
"""Return a (subdir, filename, offset, count) tuple:
subdir: subdirectory for the file
filename: the filename that contains the specified row
offset: byte offset of the specified row within the file
count: number of rows (starting at offset) that fit in the file
"""
filenum = row // self.rows_per_file
# It's OK if these format specifiers are too short; the filenames
# will just get longer but will still sort correctly.
dirname = sprintf("%04x", filenum // self.files_per_dir)
filename = sprintf("%04x", filenum % self.files_per_dir)
offset = (row % self.rows_per_file) * self.row_size
count = self.rows_per_file - (row % self.rows_per_file)
return (dirname, filename, offset, count)
def _row_from_offset(self, subdir, filename, offset):
"""Return the row number that corresponds to the given
'subdir/filename' and byte-offset within that file."""
if (offset % self.row_size) != 0: # pragma: no cover
# this shouldn't occur, unless there is some corruption somewhere
raise ValueError("file offset is not a multiple of data size")
filenum = int(subdir, 16) * self.files_per_dir + int(filename, 16)
row = (filenum * self.rows_per_file) + (offset // self.row_size)
return row
def _remove_or_truncate_file(self, subdir, filename, offset = 0):
"""Remove the given file, and remove the subdirectory too
if it's empty. If offset is nonzero, truncate the file
to that size instead."""
# Close potentially open file in file_open LRU cache
self.file_open.cache_remove(self, subdir, filename)
if offset:
# Truncate it
with open(os.path.join(self.root, subdir, filename), "r+b") as f:
f.truncate(offset)
else:
# Remove file
os.remove(os.path.join(self.root, subdir, filename))
# Try deleting subdir, too
try:
os.rmdir(os.path.join(self.root, subdir))
except Exception:
pass
# Cache open files
@nilmdb.utils.lru_cache(size = fd_cache_size,
onremove = lambda f: f.close())
def file_open(self, subdir, filename):
"""Open and map a given 'subdir/filename' (relative to self.root).
Will be automatically closed when evicted from the cache."""
# Create path if it doesn't exist
try:
os.mkdir(os.path.join(self.root, subdir))
except OSError:
pass
# Return a rocket.Rocket object, which contains the open file
return rocket.Rocket(self.layout,
os.path.join(self.root, subdir, filename))
def append_data(self, data, start, end, binary = False):
"""Parse the formatted string in 'data', according to the
current layout, and append it to the table. If any timestamps
are non-monotonic, or don't fall between 'start' and 'end',
a ValueError is raised.
If 'binary' is True, the data should be in raw binary format
instead: little-endian, matching the current table's layout,
including the int64 timestamp.
If this function succeeds, it returns normally. Otherwise,
the table is reverted back to its original state by truncating
or deleting files as necessary."""
data_offset = 0
last_timestamp = nilmdb.utils.time.min_timestamp
tot_rows = self.nrows
count = 0
linenum = 0
try:
while data_offset < len(data):
# See how many rows we can fit into the current file,
# and open it
(subdir, fname, offset, count) = self._offset_from_row(tot_rows)
f = self.file_open(subdir, fname)
# Ask the rocket object to parse and append up to "count"
# rows of data, verifying things along the way.
try:
if binary:
appender = f.append_binary
else:
appender = f.append_string
(added_rows, data_offset, last_timestamp, linenum
) = appender(count, data, data_offset, linenum,
start, end, last_timestamp)
except rocket.ParseError as e:
(linenum, colnum, errtype, obj) = e.args
if binary:
where = "byte %d: " % (linenum)
else:
where = "line %d, column %d: " % (linenum, colnum)
# Extract out the error line, add column marker
try:
if binary:
raise IndexError
bad = data.splitlines()[linenum-1]
bad += '\n' + ' ' * (colnum - 1) + '^'
except IndexError:
bad = ""
if errtype == rocket.ERR_NON_MONOTONIC:
err = "timestamp is not monotonically increasing"
elif errtype == rocket.ERR_OUT_OF_INTERVAL:
if obj < start:
err = sprintf("Data timestamp %s < start time %s",
timestamp_to_string(obj),
timestamp_to_string(start))
else:
err = sprintf("Data timestamp %s >= end time %s",
timestamp_to_string(obj),
timestamp_to_string(end))
else:
err = str(obj)
raise ValueError("error parsing input data: " +
where + err + "\n" + bad)
tot_rows += added_rows
except Exception:
# Some failure, so try to roll things back by truncating or
# deleting files that we may have appended data to.
cleanpos = self.nrows
while cleanpos <= tot_rows:
(subdir, fname, offset, count) = self._offset_from_row(cleanpos)
self._remove_or_truncate_file(subdir, fname, offset)
cleanpos += count
# Re-raise original exception
raise
else:
# Success, so update self.nrows accordingly
self.nrows = tot_rows
def get_data(self, start, stop, binary = False):
"""Extract data corresponding to Python range [n:m],
and returns a formatted string"""
if (start is None or
stop is None or
start > stop or
start < 0 or
stop > self.nrows):
raise IndexError("Index out of range")
ret = []
row = start
remaining = stop - start
while remaining > 0:
(subdir, filename, offset, count) = self._offset_from_row(row)
if count > remaining:
count = remaining
f = self.file_open(subdir, filename)
if binary:
ret.append(f.extract_binary(offset, count))
else:
ret.append(f.extract_string(offset, count))
remaining -= count
row += count
return b"".join(ret)
def __getitem__(self, row):
"""Extract timestamps from a row, with table[n] notation."""
if row < 0 or row >= self.nrows:
raise IndexError("Index out of range")
(subdir, filename, offset, count) = self._offset_from_row(row)
f = self.file_open(subdir, filename)
return f.extract_timestamp(offset)
def _remove_rows(self, subdir, filename, start, stop):
"""Helper to mark specific rows as being removed from a
file, and potentially remove or truncate the file itself."""
# Close potentially open file in file_open LRU cache
self.file_open.cache_remove(self, subdir, filename)
# We keep a file like 0000.removed that contains a list of
# which rows have been "removed". Note that we never have to
# remove entries from this list, because we never decrease
# self.nrows, and so we will never overwrite those locations in the
# file. Only when the list covers the entire extent of the
# file will that file be removed.
datafile = os.path.join(self.root, subdir, filename)
cachefile = datafile + ".removed"
try:
with open(cachefile, "rb") as f:
ranges = pickle.load(f)
cachefile_present = True
except Exception:
ranges = []
cachefile_present = False
# Append our new range and sort
ranges.append((start, stop))
ranges.sort()
# Merge adjacent ranges into "out"
merged = []
prev = None
for new in ranges:
if prev is None:
# No previous range, so remember this one
prev = new
elif prev[1] == new[0]:
# Previous range connected to this new one; extend prev
prev = (prev[0], new[1])
else:
# Not connected; append previous and start again
merged.append(prev)
prev = new
if prev is not None:
merged.append(prev)
# If the range covered the whole file, we can delete it now.
# Note that the last file in a table may be only partially
# full (smaller than self.rows_per_file). We purposely leave
# those files around rather than deleting them, because the
# remainder will be filled on a subsequent append(), and things
# are generally easier if we don't have to special-case that.
if (len(merged) == 1 and
merged[0][0] == 0 and merged[0][1] == self.rows_per_file):
# Delete files
if cachefile_present:
os.remove(cachefile)
self._remove_or_truncate_file(subdir, filename, 0)
else:
# File needs to stick around. This means we can get
# degenerate cases where we have large files containing as
# little as one row. Try to punch a hole in the file,
# so that this region doesn't take up filesystem space.
offset = start * self.row_size
count = (stop - start) * self.row_size
nilmdb.utils.fallocate.punch_hole(datafile, offset, count)
# Update cache. Try to do it atomically.
nilmdb.utils.atomic.replace_file(cachefile,
pickle.dumps(merged, 2))
def remove(self, start, stop):
"""Remove specified rows [start, stop) from this table.
If a file is left empty, it is fully removed. Otherwise, a
parallel data file is used to remember which rows have been
removed, and the file is otherwise untouched."""
if start < 0 or start > stop or stop > self.nrows:
raise IndexError("Index out of range")
row = start
remaining = stop - start
while remaining:
# Loop through each file that we need to touch
(subdir, filename, offset, count) = self._offset_from_row(row)
if count > remaining:
count = remaining
row_offset = offset // self.row_size
# Mark the rows as being removed
self._remove_rows(subdir, filename, row_offset, row_offset + count)
remaining -= count
row += count

12
nilmdb/server/errors.py Normal file
View File

@@ -0,0 +1,12 @@
"""Exceptions"""
class NilmDBError(Exception):
"""Base exception for NilmDB errors"""
def __init__(self, message = "Unspecified error"):
Exception.__init__(self, message)
class StreamError(NilmDBError):
pass
class OverlapError(NilmDBError):
pass

View File

@@ -1,58 +1,81 @@
"""Interval and IntervalSet
"""Interval, IntervalSet
The Interval implemented here is just like
nilmdb.utils.interval.Interval, except implemented in Cython for
speed.
Represents an interval of time, and a set of such intervals.
Intervals are closed, ie. they include timestamps [start, end]
Intervals are half-open, ie. they include data points with timestamps
[start, end)
"""
# First implementation kept a sorted list of intervals and used
# biesct() to optimize some operations, but this was too slow.
# This version is based on the quicksect implementation from python-bx,
# modified slightly to handle floating point intervals.
# Second version was based on the quicksect implementation from
# python-bx, modified slightly to handle floating point intervals.
# This didn't support deletion.
import pyximport
pyximport.install()
import bxintersect
# Third version is more similar to the first version, using a rb-tree
# instead of a simple sorted list to maintain O(log n) operations.
import bisect
# Fourth version is an optimized rb-tree that stores interval starts
# and ends directly in the tree, like bxinterval did.
class IntervalError(Exception):
"""Error due to interval overlap, etc"""
pass
from ..utils.time import min_timestamp as nilmdb_min_timestamp
from ..utils.time import max_timestamp as nilmdb_max_timestamp
from ..utils.time import timestamp_to_string
from ..utils.iterator import imerge
from ..utils.interval import IntervalError
import itertools
class Interval(bxintersect.Interval):
cimport rbtree
from libc.stdint cimport uint64_t, int64_t
ctypedef int64_t timestamp_t
cdef class Interval:
"""Represents an interval of time."""
def __init__(self, start, end):
cdef public timestamp_t start, end
def __init__(self, timestamp_t start, timestamp_t end):
"""
'start' and 'end' are arbitrary floats that represent time
'start' and 'end' are arbitrary numbers that represent time
"""
if start > end:
if start >= end:
# Explicitly disallow zero-width intervals (since they're half-open)
raise IntervalError("start %s must precede end %s" % (start, end))
bxintersect.Interval.__init__(self, start, end)
self.start = start
self.end = end
def __repr__(self):
s = repr(self.start) + ", " + repr(self.end)
return self.__class__.__name__ + "(" + s + ")"
def __str__(self):
return "[" + str(self.start) + " -> " + str(self.end) + "]"
return ("[" + timestamp_to_string(self.start) +
" -> " + timestamp_to_string(self.end) + ")")
def intersects(self, other):
def __cmp__(self, Interval other):
"""Compare two intervals. If non-equal, order by start then end"""
return cmp(self.start, other.start) or cmp(self.end, other.end)
cpdef intersects(self, Interval other):
"""Return True if two Interval objects intersect"""
if (self.end <= other.start or self.start >= other.end):
return False
return True
def subset(self, start, end):
cpdef subset(self, timestamp_t start, timestamp_t end):
"""Return a new Interval that is a subset of this one"""
# A subclass that tracks additional data might override this.
if start < self.start or end > self.end:
raise IntervalError("not a subset")
return Interval(start, end)
class DBInterval(Interval):
cdef class DBInterval(Interval):
"""
Like Interval, but also tracks corresponding start/end times and
positions within the database. These are not currently modified
@@ -66,11 +89,15 @@ class DBInterval(Interval):
end = 150
db_end = 200, db_endpos = 20000
"""
cpdef public timestamp_t db_start, db_end
cpdef public uint64_t db_startpos, db_endpos
def __init__(self, start, end,
db_start, db_end,
db_startpos, db_endpos):
"""
'db_start' and 'db_end' are arbitrary floats that represent
'db_start' and 'db_end' are arbitrary numbers that represent
time. They must be a strict superset of the time interval
covered by 'start' and 'end'. The 'db_startpos' and
'db_endpos' are arbitrary database position indicators that
@@ -90,7 +117,7 @@ class DBInterval(Interval):
s += ", " + repr(self.db_startpos) + ", " + repr(self.db_endpos)
return self.__class__.__name__ + "(" + s + ")"
def subset(self, start, end):
cpdef subset(self, timestamp_t start, timestamp_t end):
"""
Return a new DBInterval that is a subset of this one
"""
@@ -100,21 +127,25 @@ class DBInterval(Interval):
self.db_start, self.db_end,
self.db_startpos, self.db_endpos)
class IntervalSet(object):
cdef class IntervalSet:
"""
A non-intersecting set of intervals.
"""
cdef public rbtree.RBTree tree
def __init__(self, source=None):
"""
'source' is an Interval or IntervalSet to add.
"""
self.tree = bxintersect.IntervalTree()
self.tree = rbtree.RBTree()
if source is not None:
self += source
def __iter__(self):
return self.tree.traverse()
for node in self.tree:
if node.obj:
yield node.obj
def __len__(self):
return sum(1 for x in self)
@@ -127,7 +158,7 @@ class IntervalSet(object):
descs = [ str(x) for x in self ]
return "[" + ", ".join(descs) + "]"
def __eq__(self, other):
def __match__(self, other):
# This isn't particularly efficient, but it shouldn't get used in the
# general case.
"""Test equality of two IntervalSets.
@@ -146,8 +177,8 @@ class IntervalSet(object):
else:
return False
this = [ x for x in self ]
that = [ x for x in other ]
this = list(self)
that = list(other)
try:
while True:
@@ -178,10 +209,20 @@ class IntervalSet(object):
except IndexError:
return False
def __ne__(self, other):
return not self.__eq__(other)
# Use __richcmp__ instead of __eq__, __ne__ for Cython.
def __richcmp__(self, other, int op):
if op == 2: # ==
return self.__match__(other)
elif op == 3: # !=
return not self.__match__(other)
return False
#def __eq__(self, other):
# return self.__match__(other)
#
#def __ne__(self, other):
# return not self.__match__(other)
def __iadd__(self, other):
def __iadd__(self, object other not None):
"""Inplace add -- modifies self
This throws an exception if the regions being added intersect."""
@@ -189,37 +230,49 @@ class IntervalSet(object):
if self.intersects(other):
raise IntervalError("Tried to add overlapping interval "
"to this set")
self.tree.insert_interval(other)
self.tree.insert(rbtree.RBNode(other.start, other.end, other))
else:
for x in other:
self.__iadd__(x)
return self
def __add__(self, other):
def iadd_nocheck(self, Interval other not None):
"""Inplace add -- modifies self.
'Optimized' version that doesn't check for intersection and
only inserts the new interval into the tree."""
self.tree.insert(rbtree.RBNode(other.start, other.end, other))
def __isub__(self, Interval other not None):
"""Inplace subtract -- modifies self
Removes an interval from the set. Must exist exactly
as provided -- cannot remove a subset of an existing interval."""
i = self.tree.find(other.start, other.end)
if i is None:
raise IntervalError("interval " + str(other) + " not in tree")
self.tree.delete(i)
return self
def __add__(self, other not None):
"""Add -- returns a new object"""
new = IntervalSet(self)
new += IntervalSet(other)
return new
def __and__(self, other):
def __and__(self, other not None):
"""
Compute a new IntervalSet from the intersection of two others
Compute a new IntervalSet from the intersection of this
IntervalSet with one other interval.
Output intervals are built as subsets of the intervals in the
first argument (self).
"""
out = IntervalSet()
if not isinstance(other, IntervalSet):
other = [ other ]
for x in other:
for i in self.intersection(x):
out.tree.insert_interval(i)
for i in self.intersection(other):
out.tree.insert(rbtree.RBNode(i.start, i.end, i))
return out
def intersection(self, interval):
def intersection(self, Interval interval not None, orig = False):
"""
Compute a sequence of intervals that correspond to the
intersection between `self` and the provided interval.
@@ -228,14 +281,37 @@ class IntervalSet(object):
Output intervals are built as subsets of the intervals in the
first argument (self).
"""
for i in self.tree.find(interval.start, interval.end):
if i.start > interval.start and i.end < interval.end:
yield i
else:
yield i.subset(max(i.start, interval.start),
min(i.end, interval.end))
def intersects(self, other):
If orig = True, also return the original interval that was
(potentially) subsetted to make the one that is being
returned.
"""
if orig:
for n in self.tree.intersect(interval.start, interval.end):
i = n.obj
subset = i.subset(max(i.start, interval.start),
min(i.end, interval.end))
yield (subset, i)
else:
for n in self.tree.intersect(interval.start, interval.end):
i = n.obj
subset = i.subset(max(i.start, interval.start),
min(i.end, interval.end))
yield subset
cpdef intersects(self, Interval other):
"""Return True if this IntervalSet intersects another interval"""
return len(self.tree.find(other.start, other.end)) > 0
for n in self.tree.intersect(other.start, other.end):
if n.obj.intersects(other):
return True
return False
def find_end(self, timestamp_t t):
"""
Return an Interval from this tree that ends at time t, or
None if it doesn't exist.
"""
n = self.tree.find_left_end(t)
if n and n.obj.end == t:
return n.obj
return None

View File

@@ -0,0 +1 @@
rbtree.pxd

683
nilmdb/server/nilmdb.py Normal file
View File

@@ -0,0 +1,683 @@
# -*- coding: utf-8 -*-
"""NilmDB
Object that represents a NILM database file.
Manages both the SQL database and the table storage backend.
"""
# Need absolute_import so that "import nilmdb" won't pull in
# nilmdb.py, but will pull the parent nilmdb module instead.
from __future__ import absolute_import
import nilmdb.utils
from nilmdb.utils.printf import *
from nilmdb.utils.time import timestamp_to_string
from nilmdb.utils.interval import IntervalError
from nilmdb.server.interval import Interval, DBInterval, IntervalSet
from nilmdb.server import bulkdata
from nilmdb.server.errors import NilmDBError, StreamError, OverlapError
import sqlite3
import os
import errno
import bisect
# Note about performance and transactions:
#
# Committing a transaction in the default sync mode (PRAGMA synchronous=FULL)
# takes about 125msec. sqlite3 will commit transactions at 3 times:
# 1: explicit con.commit()
# 2: between a series of DML commands and non-DML commands, e.g.
# after a series of INSERT, SELECT, but before a CREATE TABLE or PRAGMA.
# 3: at the end of an explicit transaction, e.g. "with self.con as con:"
#
# To speed things up, we can set 'PRAGMA synchronous=OFF'. Or, it
# seems that 'PRAGMA synchronous=NORMAL' and 'PRAGMA journal_mode=WAL'
# give an equivalent speedup more safely. That is what is used here.
_sql_schema_updates = {
0: { "next": 1, "sql": """
-- All streams
CREATE TABLE streams(
id INTEGER PRIMARY KEY, -- stream ID
path TEXT UNIQUE NOT NULL, -- path, e.g. '/newton/prep'
layout TEXT NOT NULL -- layout name, e.g. float32_8
);
-- Individual timestamped ranges in those streams.
-- For a given start_time and end_time, this tells us that the
-- data is stored between start_pos and end_pos.
-- Times are stored as μs since Unix epoch
-- Positions are opaque: PyTables rows, file offsets, etc.
--
-- Note: end_pos points to the row _after_ end_time, so end_pos-1
-- is the last valid row.
CREATE TABLE ranges(
stream_id INTEGER NOT NULL,
start_time INTEGER NOT NULL,
end_time INTEGER NOT NULL,
start_pos INTEGER NOT NULL,
end_pos INTEGER NOT NULL
);
CREATE INDEX _ranges_index ON ranges (stream_id, start_time, end_time);
""" },
1: { "next": 3, "sql": """
-- Generic dictionary-type metadata that can be associated with a stream
CREATE TABLE metadata(
stream_id INTEGER NOT NULL,
key TEXT NOT NULL,
value TEXT
);
""" },
2: { "error": "old format with floating-point timestamps requires "
"nilmdb 1.3.1 or older" },
3: { "next": None },
}
@nilmdb.utils.must_close()
class NilmDB(object):
verbose = 0
def __init__(self, basepath, max_results=None,
max_removals=None, bulkdata_args=None):
"""Initialize NilmDB at the given basepath.
Other arguments are for debugging / testing:
'max_results' is the max rows to send in a single
stream_intervals or stream_extract response.
'max_removals' is the max rows to delete at once
in stream_move.
'bulkdata_args' is kwargs for the bulkdata module.
"""
if bulkdata_args is None:
bulkdata_args = {}
# set up path
self.basepath = os.path.abspath(basepath)
# Create the database path if it doesn't exist
try:
os.makedirs(self.basepath)
except OSError as e:
if e.errno != errno.EEXIST: # pragma: no cover
# (no coverage, because it's hard to trigger this case
# if tests are run as root)
raise IOError("can't create tree " + self.basepath)
# Our data goes inside it
self.data = bulkdata.BulkData(self.basepath, **bulkdata_args)
# SQLite database too
sqlfilename = os.path.join(self.basepath, "data.sql")
self.con = sqlite3.connect(sqlfilename, check_same_thread = True)
try:
self._sql_schema_update()
except Exception: # pragma: no cover
self.data.close()
raise
# See big comment at top about the performance implications of this
self.con.execute("PRAGMA synchronous=NORMAL")
self.con.execute("PRAGMA journal_mode=WAL")
# Approximate largest number of elements that we want to send
# in a single reply (for stream_intervals, stream_extract).
self.max_results = max_results or 16384
# Remove up to this many rows per call to stream_remove.
self.max_removals = max_removals or 1048576
def get_basepath(self):
return self.basepath
def close(self):
if self.con:
self.con.commit()
self.con.close()
self.data.close()
def _sql_schema_update(self):
cur = self.con.cursor()
version = cur.execute("PRAGMA user_version").fetchone()[0]
oldversion = version
while True:
if version not in _sql_schema_updates: # pragma: no cover
raise Exception(self.basepath + ": unknown database version "
+ str(version))
update = _sql_schema_updates[version]
if "error" in update: # pragma: no cover
raise Exception(self.basepath + ": can't use database version "
+ str(version) + ": " + update["error"])
if update["next"] is None:
break
cur.executescript(update["sql"])
version = update["next"]
if self.verbose: # pragma: no cover
printf("Database schema updated to %d\n", version)
if version != oldversion:
with self.con:
cur.execute("PRAGMA user_version = {v:d}".format(v=version))
def _check_user_times(self, start, end):
if start is None:
start = nilmdb.utils.time.min_timestamp
if end is None:
end = nilmdb.utils.time.max_timestamp
if start >= end:
raise NilmDBError("start must precede end")
return (start, end)
@nilmdb.utils.lru_cache(size = 64)
def _get_intervals(self, stream_id):
"""
Return a mutable IntervalSet corresponding to the given stream ID.
"""
iset = IntervalSet()
result = self.con.execute("SELECT start_time, end_time, "
"start_pos, end_pos "
"FROM ranges "
"WHERE stream_id=?", (stream_id,))
try:
for (start_time, end_time, start_pos, end_pos) in result:
iset += DBInterval(start_time, end_time,
start_time, end_time,
start_pos, end_pos)
except IntervalError: # pragma: no cover
raise NilmDBError("unexpected overlap in ranges table!")
return iset
def _sql_interval_insert(self, id, start, end, start_pos, end_pos):
"""Helper that adds interval to the SQL database only"""
self.con.execute("INSERT INTO ranges "
"(stream_id,start_time,end_time,start_pos,end_pos) "
"VALUES (?,?,?,?,?)",
(id, start, end, start_pos, end_pos))
def _sql_interval_delete(self, id, start, end, start_pos, end_pos):
"""Helper that removes interval from the SQL database only"""
self.con.execute("DELETE FROM ranges WHERE "
"stream_id=? AND start_time=? AND "
"end_time=? AND start_pos=? AND end_pos=?",
(id, start, end, start_pos, end_pos))
def _add_interval(self, stream_id, interval, start_pos, end_pos):
"""
Add interval to the internal interval cache, and to the database.
Note: arguments must be ints (not numpy.int64, etc)
"""
# Load this stream's intervals
iset = self._get_intervals(stream_id)
# Check for overlap
if iset.intersects(interval): # pragma: no cover (gets caught earlier)
raise NilmDBError("new interval overlaps existing data")
# Check for adjacency. If there's a stream in the database
# that ends exactly when this one starts, and the database
# rows match up, we can make one interval that covers the
# time range [adjacent.start -> interval.end)
# and database rows [ adjacent.start_pos -> end_pos ].
# Only do this if the resulting interval isn't too large.
max_merged_rows = 8000 * 60 * 60 * 1.05 # 1.05 hours at 8 KHz
adjacent = iset.find_end(interval.start)
if (adjacent is not None and
start_pos == adjacent.db_endpos and
(end_pos - adjacent.db_startpos) < max_merged_rows):
# First delete the old one, both from our iset and the
# database
iset -= adjacent
self._sql_interval_delete(stream_id,
adjacent.db_start, adjacent.db_end,
adjacent.db_startpos, adjacent.db_endpos)
# Now update our interval so the fallthrough add is
# correct.
interval.start = adjacent.start
start_pos = adjacent.db_startpos
# Add the new interval to the iset
iset.iadd_nocheck(DBInterval(interval.start, interval.end,
interval.start, interval.end,
start_pos, end_pos))
# Insert into the database
self._sql_interval_insert(stream_id, interval.start, interval.end,
int(start_pos), int(end_pos))
self.con.commit()
def _remove_interval(self, stream_id, original, remove):
"""
Remove an interval from the internal cache and the database.
stream_id: id of stream
original: original DBInterval; must be already present in DB
to_remove: DBInterval to remove; must be subset of 'original'
"""
# Just return if we have nothing to remove
if remove.start == remove.end: # pragma: no cover
return
# Load this stream's intervals
iset = self._get_intervals(stream_id)
# Remove existing interval from the cached set and the database
iset -= original
self._sql_interval_delete(stream_id,
original.db_start, original.db_end,
original.db_startpos, original.db_endpos)
# Add back the intervals that would be left over if the
# requested interval is removed. There may be two of them, if
# the removed piece was in the middle.
def add(iset, start, end, start_pos, end_pos):
iset += DBInterval(start, end, start, end, start_pos, end_pos)
self._sql_interval_insert(stream_id, start, end, start_pos, end_pos)
if original.start != remove.start:
# Interval before the removed region
add(iset, original.start, remove.start,
original.db_startpos, remove.db_startpos)
if original.end != remove.end:
# Interval after the removed region
add(iset, remove.end, original.end,
remove.db_endpos, original.db_endpos)
# Commit SQL changes
self.con.commit()
return
def stream_list(self, path = None, layout = None, extended = False):
"""Return list of lists of all streams in the database.
If path is specified, include only streams with a path that
matches the given string.
If layout is specified, include only streams with a layout
that matches the given string.
If extended = False, returns a list of lists containing
the path and layout: [ path, layout ]
If extended = True, returns a list of lists containing
more information:
path
layout
interval_min (earliest interval start)
interval_max (latest interval end)
rows (total number of rows of data)
time (total time covered by this stream, in timestamp units)
"""
params = ()
query = "SELECT streams.path, streams.layout"
if extended:
query += ", min(ranges.start_time), max(ranges.end_time) "
query += ", coalesce(sum(ranges.end_pos - ranges.start_pos), 0) "
query += ", coalesce(sum(ranges.end_time - ranges.start_time), 0) "
query += " FROM streams"
if extended:
query += " LEFT JOIN ranges ON streams.id = ranges.stream_id"
query += " WHERE 1=1"
if layout is not None:
query += " AND streams.layout=?"
params += (layout,)
if path is not None:
query += " AND streams.path=?"
params += (path,)
query += " GROUP BY streams.id ORDER BY streams.path"
result = self.con.execute(query, params).fetchall()
return [ list(x) for x in result ]
def stream_intervals(self, path, start = None, end = None, diffpath = None):
"""
List all intervals in 'path' between 'start' and 'end'. If
'diffpath' is not none, list instead the set-difference
between the intervals in the two streams; i.e. all interval
ranges that are present in 'path' but not 'diffpath'.
Returns (intervals, restart) tuple.
'intervals' is a list of [start,end] timestamps of all intervals
that exist for path, between start and end.
'restart', if not None, means that there were too many results
to return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated, and
a new request with a start time of 'restart' will fetch the
next block of data.
"""
stream_id = self._stream_id(path)
intervals = self._get_intervals(stream_id)
if diffpath:
diffstream_id = self._stream_id(diffpath)
diffintervals = self._get_intervals(diffstream_id)
(start, end) = self._check_user_times(start, end)
requested = Interval(start, end)
result = []
if diffpath:
getter = nilmdb.utils.interval.set_difference(
intervals.intersection(requested),
diffintervals.intersection(requested))
else:
getter = intervals.intersection(requested)
for n, i in enumerate(getter):
if n >= self.max_results:
restart = i.start
break
result.append([i.start, i.end])
else:
restart = None
return (result, restart)
def stream_create(self, path, layout_name):
"""Create a new table in the database.
path: path to the data (e.g. '/newton/prep').
Paths must contain at least two elements, e.g.:
/newton/prep
/newton/raw
/newton/upstairs/prep
/newton/upstairs/raw
layout_name: string for nilmdb.layout.get_named(), e.g. 'float32_8'
"""
# Create the bulk storage. Raises ValueError on error, which we
# pass along.
self.data.create(path, layout_name)
# Insert into SQL database once the bulk storage is happy
with self.con as con:
con.execute("INSERT INTO streams (path, layout) VALUES (?,?)",
(path, layout_name))
def _stream_id(self, path):
"""Return unique stream ID"""
result = self.con.execute("SELECT id FROM streams WHERE path=?",
(path,)).fetchone()
if result is None:
raise StreamError("No stream at path " + path)
return result[0]
def stream_set_metadata(self, path, data):
"""Set stream metadata from a dictionary, e.g.
{ description = 'Downstairs lighting',
v_scaling = 123.45 }
This replaces all existing metadata.
"""
stream_id = self._stream_id(path)
with self.con as con:
con.execute("DELETE FROM metadata WHERE stream_id=?", (stream_id,))
for key in data:
if data[key] != '':
con.execute("INSERT INTO metadata VALUES (?, ?, ?)",
(stream_id, key, data[key]))
def stream_get_metadata(self, path):
"""Return stream metadata as a dictionary."""
stream_id = self._stream_id(path)
result = self.con.execute("SELECT metadata.key, metadata.value "
"FROM metadata "
"WHERE metadata.stream_id=?", (stream_id,))
data = {}
for (key, value) in result:
data[key] = value
return data
def stream_update_metadata(self, path, newdata):
"""Update stream metadata from a dictionary"""
data = self.stream_get_metadata(path)
data.update(newdata)
self.stream_set_metadata(path, data)
def stream_rename(self, oldpath, newpath):
"""Rename a stream."""
stream_id = self._stream_id(oldpath)
# Rename the data
self.data.rename(oldpath, newpath)
# Rename the stream in the database
with self.con as con:
con.execute("UPDATE streams SET path=? WHERE id=?",
(newpath, stream_id))
def stream_destroy(self, path):
"""Fully remove a table from the database. Fails if there are
any intervals data present; remove them first. Metadata is
also removed."""
stream_id = self._stream_id(path)
# Verify that no intervals are present, and clear the cache
iset = self._get_intervals(stream_id)
if len(iset):
raise NilmDBError("all intervals must be removed before "
"destroying a stream")
self._get_intervals.cache_remove(self, stream_id)
# Delete the bulkdata storage
self.data.destroy(path)
# Delete metadata, stream, intervals (should be none)
with self.con as con:
con.execute("DELETE FROM metadata WHERE stream_id=?", (stream_id,))
con.execute("DELETE FROM ranges WHERE stream_id=?", (stream_id,))
con.execute("DELETE FROM streams WHERE id=?", (stream_id,))
def stream_insert(self, path, start, end, data, binary = False):
"""Insert new data into the database.
path: Path at which to add the data
start: Starting timestamp
end: Ending timestamp
data: Textual data, formatted according to the layout of path
'binary', if True, means that 'data' is raw binary:
little-endian, matching the current table's layout,
including the int64 timestamp.
"""
# First check for basic overlap using timestamp info given.
stream_id = self._stream_id(path)
iset = self._get_intervals(stream_id)
interval = Interval(start, end)
if iset.intersects(interval):
raise OverlapError("new data overlaps existing data at range: "
+ str(iset & interval))
# Tenatively append the data. This will raise a ValueError if
# there are any parse errors.
table = self.data.getnode(path)
row_start = table.nrows
table.append_data(data, start, end, binary)
row_end = table.nrows
# Insert the record into the sql database.
self._add_interval(stream_id, interval, row_start, row_end)
# And that's all
return
def _find_start(self, table, dbinterval):
"""
Given a DBInterval, find the row in the database that
corresponds to the start time. Return the first database
position with a timestamp (first element) greater than or
equal to 'start'.
"""
# Optimization for the common case where an interval wasn't truncated
if dbinterval.start == dbinterval.db_start:
return dbinterval.db_startpos
return bisect.bisect_left(table,
dbinterval.start,
dbinterval.db_startpos,
dbinterval.db_endpos)
def _find_end(self, table, dbinterval):
"""
Given a DBInterval, find the row in the database that follows
the end time. Return the first database position after the
row with timestamp (first element) greater than or equal
to 'end'.
"""
# Optimization for the common case where an interval wasn't truncated
if dbinterval.end == dbinterval.db_end:
return dbinterval.db_endpos
# Note that we still use bisect_left here, because we don't
# want to include the given timestamp in the results. This is
# so a queries like 1:00 -> 2:00 and 2:00 -> 3:00 return
# non-overlapping data.
return bisect.bisect_left(table,
dbinterval.end,
dbinterval.db_startpos,
dbinterval.db_endpos)
def stream_extract(self, path, start = None, end = None,
count = False, markup = False, binary = False):
"""
Returns (data, restart) tuple.
'data' is ASCII-formatted data from the database, formatted
according to the layout of the stream.
'restart', if not None, means that there were too many results to
return in a single request. The data is complete from the
starting timestamp to the point at which it was truncated,
and a new request with a start time of 'restart' will fetch
the next block of data.
'count', if true, means to not return raw data, but just the count
of rows that would have been returned. This is much faster
than actually fetching the data. It is not limited by
max_results.
'markup', if true, indicates that returned data should be
marked with a comment denoting when a particular interval
starts, and another comment when an interval ends.
'binary', if true, means to return raw binary rather than
ASCII-formatted data.
"""
stream_id = self._stream_id(path)
table = self.data.getnode(path)
intervals = self._get_intervals(stream_id)
(start, end) = self._check_user_times(start, end)
requested = Interval(start, end)
result = []
matched = 0
remaining = self.max_results
restart = None
if binary and (markup or count):
raise NilmDBError("binary mode can't be used with markup or count")
for interval in intervals.intersection(requested):
# Reading single rows from the table is too slow, so
# we use two bisections to find both the starting and
# ending row for this particular interval, then
# read the entire range as one slice.
row_start = self._find_start(table, interval)
row_end = self._find_end(table, interval)
if count:
matched += row_end - row_start
continue
# Shorten it if we'll hit the maximum number of results
row_max = row_start + remaining
if row_max < row_end:
row_end = row_max
restart = table[row_max]
# Add markup
if markup:
result.append("# interval-start " +
timestamp_to_string(interval.start) + "\n")
# Gather these results up
result.append(table.get_data(row_start, row_end, binary))
# Count them
remaining -= row_end - row_start
# Add markup, and exit if restart is set.
if restart is not None:
if markup:
result.append("# interval-end " +
timestamp_to_string(restart) + "\n")
break
if markup:
result.append("# interval-end " +
timestamp_to_string(interval.end) + "\n")
if count:
return matched
return ("".join(result), restart)
def stream_remove(self, path, start = None, end = None):
"""
Remove data from the specified time interval within a stream.
Removes data in the interval [start, end), and intervals are
truncated or split appropriately.
Returns a (removed, restart) tuple.
'removed' is the number of data points that were removed.
'restart', if not None, means there were too many rows to
remove in a single request. This function should be called
again with a start time of 'restart' to complete the removal.
"""
stream_id = self._stream_id(path)
table = self.data.getnode(path)
intervals = self._get_intervals(stream_id)
(start, end) = self._check_user_times(start, end)
to_remove = Interval(start, end)
removed = 0
remaining = self.max_removals
restart = None
# Can't remove intervals from within the iterator, so we need to
# remember what's currently in the intersection now.
all_candidates = list(intervals.intersection(to_remove, orig = True))
for (dbint, orig) in all_candidates:
# Find row start and end
row_start = self._find_start(table, dbint)
row_end = self._find_end(table, dbint)
# Shorten it if we'll hit the maximum number of removals
row_max = row_start + remaining
if row_max < row_end:
row_end = row_max
dbint.end = table[row_max]
restart = dbint.end
# Adjust the DBInterval to match the newly found ends
dbint.db_start = dbint.start
dbint.db_end = dbint.end
dbint.db_startpos = row_start
dbint.db_endpos = row_end
# Remove interval from the database
self._remove_interval(stream_id, orig, dbint)
# Remove data from the underlying table storage
table.remove(row_start, row_end)
# Count how many were removed
removed += row_end - row_start
remaining -= row_end - row_start
if restart is not None:
break
return (removed, restart)

23
nilmdb/server/rbtree.pxd Normal file
View File

@@ -0,0 +1,23 @@
cdef class RBNode:
cdef public object obj
cdef public double start, end
cdef public int red
cdef public RBNode left, right, parent
cdef class RBTree:
cdef public RBNode nil, root
cpdef getroot(RBTree self)
cdef void __rotate_left(RBTree self, RBNode x)
cdef void __rotate_right(RBTree self, RBNode y)
cdef RBNode __successor(RBTree self, RBNode x)
cpdef RBNode successor(RBTree self, RBNode x)
cdef RBNode __predecessor(RBTree self, RBNode x)
cpdef RBNode predecessor(RBTree self, RBNode x)
cpdef insert(RBTree self, RBNode z)
cdef void __insert_fixup(RBTree self, RBNode x)
cpdef delete(RBTree self, RBNode z)
cdef inline void __delete_fixup(RBTree self, RBNode x)
cpdef RBNode find(RBTree self, double start, double end)
cpdef RBNode find_left_end(RBTree self, double t)
cpdef RBNode find_right_start(RBTree self, double t)

377
nilmdb/server/rbtree.pyx Normal file
View File

@@ -0,0 +1,377 @@
# cython: profile=False
# cython: cdivision=True
"""
Jim Paris <jim@jtan.com>
Red-black tree, where keys are stored as start/end timestamps.
This is a basic interval tree that holds half-open intervals:
[start, end)
Intervals must not overlap. Fixing that would involve making this
into an augmented interval tree as described in CLRS 14.3.
Code that assumes non-overlapping intervals is marked with the
string 'non-overlapping'.
"""
import sys
cimport rbtree
cdef class RBNode:
"""One node of the Red/Black tree, containing a key (start, end)
and value (obj)"""
def __init__(self, double start, double end, object obj = None):
self.obj = obj
self.start = start
self.end = end
self.red = False
self.left = None
self.right = None
def __str__(self):
if self.red:
color = "R"
else:
color = "B"
if self.start == sys.float_info.min:
return "[node nil]"
return ("[node ("
+ str(self.obj) + ") "
+ str(self.start) + " -> " + str(self.end) + " "
+ color + "]")
cdef class RBTree:
"""Red/Black tree"""
# Init
def __init__(self):
self.nil = RBNode(start = sys.float_info.min,
end = sys.float_info.min)
self.nil.left = self.nil
self.nil.right = self.nil
self.nil.parent = self.nil
self.root = RBNode(start = sys.float_info.max,
end = sys.float_info.max)
self.root.left = self.nil
self.root.right = self.nil
self.root.parent = self.nil
# We have a dummy root node to simplify operations, so from an
# external point of view, its left child is the real root.
cpdef getroot(self):
return self.root.left
# Rotations and basic operations
cdef void __rotate_left(self, RBNode x):
"""Rotate left:
# x y
# / \ --> / \
# z y x w
# / \ / \
# v w z v
"""
cdef RBNode y = x.right
x.right = y.left
if y.left is not self.nil:
y.left.parent = x
y.parent = x.parent
if x is x.parent.left:
x.parent.left = y
else:
x.parent.right = y
y.left = x
x.parent = y
cdef void __rotate_right(self, RBNode y):
"""Rotate right:
# y x
# / \ --> / \
# x w z y
# / \ / \
# z v v w
"""
cdef RBNode x = y.left
y.left = x.right
if x.right is not self.nil:
x.right.parent = y
x.parent = y.parent
if y is y.parent.left:
y.parent.left = x
else:
y.parent.right = x
x.right = y
y.parent = x
cdef RBNode __successor(self, RBNode x):
"""Returns the successor of RBNode x"""
cdef RBNode y = x.right
if y is not self.nil:
while y.left is not self.nil:
y = y.left
else:
y = x.parent
while x is y.right:
x = y
y = y.parent
if y is self.root:
return self.nil
return y
cpdef RBNode successor(self, RBNode x):
"""Returns the successor of RBNode x, or None"""
cdef RBNode y = self.__successor(x)
return y if y is not self.nil else None
cdef RBNode __predecessor(self, RBNode x):
"""Returns the predecessor of RBNode x"""
cdef RBNode y = x.left
if y is not self.nil:
while y.right is not self.nil:
y = y.right
else:
y = x.parent
while x is y.left:
if y is self.root:
y = self.nil
break
x = y
y = y.parent
return y
cpdef RBNode predecessor(self, RBNode x):
"""Returns the predecessor of RBNode x, or None"""
cdef RBNode y = self.__predecessor(x)
return y if y is not self.nil else None
# Insertion
cpdef insert(self, RBNode z):
"""Insert RBNode z into RBTree and rebalance as necessary"""
z.left = self.nil
z.right = self.nil
cdef RBNode y = self.root
cdef RBNode x = self.root.left
while x is not self.nil:
y = x
if (x.start > z.start or (x.start == z.start and x.end > z.end)):
x = x.left
else:
x = x.right
z.parent = y
if (y is self.root or
(y.start > z.start or (y.start == z.start and y.end > z.end))):
y.left = z
else:
y.right = z
# relabel/rebalance
self.__insert_fixup(z)
cdef void __insert_fixup(self, RBNode x):
"""Rebalance/fix RBTree after a simple insertion of RBNode x"""
x.red = True
while x.parent.red:
if x.parent is x.parent.parent.left:
y = x.parent.parent.right
if y.red:
x.parent.red = False
y.red = False
x.parent.parent.red = True
x = x.parent.parent
else:
if x is x.parent.right:
x = x.parent
self.__rotate_left(x)
x.parent.red = False
x.parent.parent.red = True
self.__rotate_right(x.parent.parent)
else: # same as above, left/right switched
y = x.parent.parent.left
if y.red:
x.parent.red = False
y.red = False
x.parent.parent.red = True
x = x.parent.parent
else:
if x is x.parent.left:
x = x.parent
self.__rotate_right(x)
x.parent.red = False
x.parent.parent.red = True
self.__rotate_left(x.parent.parent)
self.root.left.red = False
# Deletion
cpdef delete(self, RBNode z):
if z.left is None or z.right is None:
raise AttributeError("you can only delete a node object "
+ "from the tree; use find() to get one")
cdef RBNode x, y
if z.left is self.nil or z.right is self.nil:
y = z
else:
y = self.__successor(z)
if y.left is self.nil:
x = y.right
else:
x = y.left
x.parent = y.parent
if x.parent is self.root:
self.root.left = x
else:
if y is y.parent.left:
y.parent.left = x
else:
y.parent.right = x
if y is not z:
# y is the node to splice out, x is its child
y.left = z.left
y.right = z.right
y.parent = z.parent
z.left.parent = y
z.right.parent = y
if z is z.parent.left:
z.parent.left = y
else:
z.parent.right = y
if not y.red:
y.red = z.red
self.__delete_fixup(x)
else:
y.red = z.red
else:
if not y.red:
self.__delete_fixup(x)
cdef void __delete_fixup(self, RBNode x):
"""Rebalance/fix RBTree after a deletion. RBNode x is the
child of the spliced out node."""
cdef RBNode rootLeft = self.root.left
while not x.red and x is not rootLeft:
if x is x.parent.left:
w = x.parent.right
if w.red:
w.red = False
x.parent.red = True
self.__rotate_left(x.parent)
w = x.parent.right
if not w.right.red and not w.left.red:
w.red = True
x = x.parent
else:
if not w.right.red:
w.left.red = False
w.red = True
self.__rotate_right(w)
w = x.parent.right
w.red = x.parent.red
x.parent.red = False
w.right.red = False
self.__rotate_left(x.parent)
x = rootLeft # exit loop
else: # same as above, left/right switched
w = x.parent.left
if w.red:
w.red = False
x.parent.red = True
self.__rotate_right(x.parent)
w = x.parent.left
if not w.left.red and not w.right.red:
w.red = True
x = x.parent
else:
if not w.left.red:
w.right.red = False
w.red = True
self.__rotate_left(w)
w = x.parent.left
w.red = x.parent.red
x.parent.red = False
w.left.red = False
self.__rotate_right(x.parent)
x = rootLeft # exit loop
x.red = False
# Walking, searching
def __iter__(self):
return self.inorder()
def inorder(self, RBNode x = None):
"""Generator that performs an inorder walk for the tree
rooted at RBNode x"""
if x is None:
x = self.getroot()
while x.left is not self.nil:
x = x.left
while x is not self.nil:
yield x
x = self.__successor(x)
cpdef RBNode find(self, double start, double end):
"""Return the node with exactly the given start and end."""
cdef RBNode x = self.getroot()
while x is not self.nil:
if start < x.start:
x = x.left
elif start == x.start:
if end == x.end:
break # found it
elif end < x.end:
x = x.left
else:
x = x.right
else:
x = x.right
return x if x is not self.nil else None
cpdef RBNode find_left_end(self, double t):
"""Find the leftmode node with end >= t. With non-overlapping
intervals, this is the first node that might overlap time t.
Note that this relies on non-overlapping intervals, since
it assumes that we can use the endpoints to traverse the
tree even though it was created using the start points."""
cdef RBNode x = self.getroot()
while x is not self.nil:
if t < x.end:
if x.left is self.nil:
break
x = x.left
elif t == x.end:
break
else:
if x.right is self.nil:
x = self.__successor(x)
break
x = x.right
return x if x is not self.nil else None
cpdef RBNode find_right_start(self, double t):
"""Find the rightmode node with start <= t. With non-overlapping
intervals, this is the last node that might overlap time t."""
cdef RBNode x = self.getroot()
while x is not self.nil:
if t < x.start:
if x.left is self.nil:
x = self.__predecessor(x)
break
x = x.left
elif t == x.start:
break
else:
if x.right is self.nil:
break
x = x.right
return x if x is not self.nil else None
# Intersections
def intersect(self, double start, double end):
"""Generator that returns nodes that overlap the given
(start,end) range. Assumes non-overlapping intervals."""
# Start with the leftmode node that ends after start
cdef RBNode n = self.find_left_end(start)
while n is not None:
if n.start >= end:
# this node starts after the requested end; we're done
break
if start < n.end:
# this node overlaps our requested area
yield n
n = self.successor(n)

View File

@@ -0,0 +1 @@
rbtree.pxd

796
nilmdb/server/rocket.c Normal file
View File

@@ -0,0 +1,796 @@
#include <Python.h>
#include <structmember.h>
#include <endian.h>
#include <ctype.h>
#include <stdint.h>
#define __STDC_FORMAT_MACROS
#include <inttypes.h>
/* Values missing from stdint.h */
#define UINT8_MIN 0
#define UINT16_MIN 0
#define UINT32_MIN 0
#define UINT64_MIN 0
/* Marker values (if min == max, skip range check) */
#define FLOAT32_MIN 0
#define FLOAT32_MAX 0
#define FLOAT64_MIN 0
#define FLOAT64_MAX 0
typedef int64_t timestamp_t;
/* Somewhat arbitrary, just so we can use fixed sizes for strings
etc. */
static const int MAX_LAYOUT_COUNT = 1024;
/* Error object and constants */
static PyObject *ParseError;
typedef enum {
ERR_OTHER,
ERR_NON_MONOTONIC,
ERR_OUT_OF_INTERVAL,
} parseerror_code_t;
static void add_parseerror_codes(PyObject *module)
{
PyModule_AddIntMacro(module, ERR_OTHER);
PyModule_AddIntMacro(module, ERR_NON_MONOTONIC);
PyModule_AddIntMacro(module, ERR_OUT_OF_INTERVAL);
}
/* Helpers to raise ParseErrors. Use "return raise_str(...)" etc. */
static PyObject *raise_str(int line, int col, int code, const char *string)
{
PyObject *o;
o = Py_BuildValue("(iiis)", line, col, code, string);
if (o != NULL) {
PyErr_SetObject(ParseError, o);
Py_DECREF(o);
}
return NULL;
}
static PyObject *raise_int(int line, int col, int code, int64_t num)
{
PyObject *o;
o = Py_BuildValue("(iiiL)", line, col, code, (long long)num);
if (o != NULL) {
PyErr_SetObject(ParseError, o);
Py_DECREF(o);
}
return NULL;
}
/****
* Layout and type helpers
*/
typedef union {
int8_t i;
uint8_t u;
} union8_t;
typedef union {
int16_t i;
uint16_t u;
} union16_t;
typedef union {
int32_t i;
uint32_t u;
float f;
} union32_t;
typedef union {
int64_t i;
uint64_t u;
double d;
} union64_t;
typedef enum {
LAYOUT_TYPE_NONE,
LAYOUT_TYPE_INT8,
LAYOUT_TYPE_UINT8,
LAYOUT_TYPE_INT16,
LAYOUT_TYPE_UINT16,
LAYOUT_TYPE_INT32,
LAYOUT_TYPE_UINT32,
LAYOUT_TYPE_INT64,
LAYOUT_TYPE_UINT64,
LAYOUT_TYPE_FLOAT32,
LAYOUT_TYPE_FLOAT64,
} layout_type_t;
struct {
char *string;
layout_type_t layout;
int size;
} type_lookup[] = {
{ "int8", LAYOUT_TYPE_INT8, 1 },
{ "uint8", LAYOUT_TYPE_UINT8, 1 },
{ "int16", LAYOUT_TYPE_INT16, 2 },
{ "uint16", LAYOUT_TYPE_UINT16, 2 },
{ "int32", LAYOUT_TYPE_INT32, 4 },
{ "uint32", LAYOUT_TYPE_UINT32, 4 },
{ "int64", LAYOUT_TYPE_INT64, 8 },
{ "uint64", LAYOUT_TYPE_UINT64, 8 },
{ "float32", LAYOUT_TYPE_FLOAT32, 4 },
{ "float64", LAYOUT_TYPE_FLOAT64, 8 },
{ NULL }
};
/****
* Object definition, init, etc
*/
/* Rocket object */
typedef struct {
PyObject_HEAD
layout_type_t layout_type;
int layout_count;
int binary_size;
FILE *file;
int file_size;
} Rocket;
/* Dealloc / new */
static void Rocket_dealloc(Rocket *self)
{
if (self->file) {
fprintf(stderr, "rocket: file wasn't closed\n");
fclose(self->file);
self->file = NULL;
}
self->ob_type->tp_free((PyObject *)self);
}
static PyObject *Rocket_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
Rocket *self;
self = (Rocket *)type->tp_alloc(type, 0);
if (!self)
return NULL;
self->layout_type = LAYOUT_TYPE_NONE;
self->layout_count = 0;
self->binary_size = 0;
self->file = NULL;
self->file_size = -1;
return (PyObject *)self;
}
/* .__init__(layout, file) */
static int Rocket_init(Rocket *self, PyObject *args, PyObject *kwds)
{
const char *layout, *path;
static char *kwlist[] = { "layout", "file", NULL };
if (!PyArg_ParseTupleAndKeywords(args, kwds, "sz", kwlist,
&layout, &path))
return -1;
if (!layout)
return -1;
if (path) {
if ((self->file = fopen(path, "a+b")) == NULL) {
PyErr_SetFromErrno(PyExc_OSError);
return -1;
}
self->file_size = -1;
} else {
self->file = NULL;
}
const char *under;
char *tmp;
under = strchr(layout, '_');
if (!under) {
PyErr_SetString(PyExc_ValueError, "no such layout: "
"badly formatted string");
return -1;
}
self->layout_count = strtoul(under+1, &tmp, 10);
if (self->layout_count < 1 || *tmp != '\0') {
PyErr_SetString(PyExc_ValueError, "no such layout: "
"bad count");
return -1;
}
if (self->layout_count >= MAX_LAYOUT_COUNT) {
PyErr_SetString(PyExc_ValueError, "no such layout: "
"count too high");
return -1;
}
int i;
for (i = 0; type_lookup[i].string; i++)
if (strncmp(layout, type_lookup[i].string, under-layout) == 0)
break;
if (!type_lookup[i].string) {
PyErr_SetString(PyExc_ValueError, "no such layout: "
"bad data type");
return -1;
}
self->layout_type = type_lookup[i].layout;
self->binary_size = 8 + (type_lookup[i].size * self->layout_count);
return 0;
}
/* .close() */
static PyObject *Rocket_close(Rocket *self)
{
if (self->file) {
fclose(self->file);
self->file = NULL;
}
Py_INCREF(Py_None);
return Py_None;
}
/* .file_size property */
static PyObject *Rocket_get_file_size(Rocket *self)
{
if (!self->file) {
PyErr_SetString(PyExc_AttributeError, "no file");
return NULL;
}
if (self->file_size < 0) {
int oldpos;
if (((oldpos = ftell(self->file)) < 0) ||
(fseek(self->file, 0, SEEK_END) < 0) ||
((self->file_size = ftell(self->file)) < 0) ||
(fseek(self->file, oldpos, SEEK_SET) < 0)) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
}
return PyInt_FromLong(self->file_size);
}
/****
* Append from string
*/
static inline long int strtoll10(const char *nptr, char **endptr) {
return strtoll(nptr, endptr, 10);
}
static inline long int strtoull10(const char *nptr, char **endptr) {
return strtoull(nptr, endptr, 10);
}
/* .append_string(count, data, offset, linenum, start, end, last_timestamp) */
static PyObject *Rocket_append_string(Rocket *self, PyObject *args)
{
int count;
const char *data;
int offset;
const char *linestart;
int linenum;
long long ll1, ll2, ll3;
timestamp_t start;
timestamp_t end;
timestamp_t last_timestamp;
int written = 0;
char *endptr;
union8_t t8;
union16_t t16;
union32_t t32;
union64_t t64;
int i;
/* It would be nice to use 't#' instead of 's' for data,
but we need the null termination for strto*. If we had
strnto* that took a length, we could use t# and not require
a copy. */
if (!PyArg_ParseTuple(args, "isiiLLL:append_string", &count,
&data, &offset, &linenum,
&ll1, &ll2, &ll3))
return NULL;
start = ll1;
end = ll2;
last_timestamp = ll3;
/* Skip spaces, but don't skip over a newline. */
#define SKIP_BLANK(buf) do { \
while (isspace(*buf)) { \
if (*buf == '\n') \
break; \
buf++; \
} } while(0)
const char *buf = &data[offset];
while (written < count && *buf)
{
linestart = buf;
linenum++;
/* Skip leading whitespace and commented lines */
SKIP_BLANK(buf);
if (*buf == '#') {
while (*buf && *buf != '\n')
buf++;
if (*buf)
buf++;
continue;
}
/* Extract timestamp */
t64.i = strtoll(buf, &endptr, 10);
if (endptr == buf || !isspace(*endptr)) {
/* Try parsing as a double instead */
t64.d = strtod(buf, &endptr);
if (endptr == buf)
goto bad_timestamp;
if (!isspace(*endptr))
goto cant_parse_value;
t64.i = round(t64.d);
}
if (t64.i <= last_timestamp)
return raise_int(linenum, buf - linestart + 1,
ERR_NON_MONOTONIC, t64.i);
last_timestamp = t64.i;
if (t64.i < start || t64.i >= end)
return raise_int(linenum, buf - linestart + 1,
ERR_OUT_OF_INTERVAL, t64.i);
t64.u = le64toh(t64.u);
if (fwrite(&t64.u, 8, 1, self->file) != 1)
goto err;
buf = endptr;
/* Parse all values in the line */
switch (self->layout_type) {
#define CS(type, parsefunc, parsetype, realtype, disktype, letoh, bytes) \
case LAYOUT_TYPE_##type: \
/* parse and write in a loop */ \
for (i = 0; i < self->layout_count; i++) { \
/* skip non-newlines */ \
SKIP_BLANK(buf); \
if (*buf == '\n') \
goto wrong_number_of_values; \
/* parse number */ \
parsetype = parsefunc(buf, &endptr); \
if (*endptr && !isspace(*endptr)) \
goto cant_parse_value; \
/* check limits */ \
if (type##_MIN != type##_MAX && \
(parsetype < type##_MIN || \
parsetype > type##_MAX)) \
goto value_out_of_range; \
/* convert to disk representation */ \
realtype = parsetype; \
disktype = letoh(disktype); \
/* write it */ \
if (fwrite(&disktype, bytes, \
1, self->file) != 1) \
goto err; \
/* advance buf */ \
buf = endptr; \
} \
/* Skip trailing whitespace and comments */ \
SKIP_BLANK(buf); \
if (*buf == '#') \
while (*buf && *buf != '\n') \
buf++; \
if (*buf == '\n') \
buf++; \
else if (*buf != '\0') \
goto extra_data_on_line; \
break
CS(INT8, strtoll10, t64.i, t8.i, t8.u, , 1);
CS(UINT8, strtoull10, t64.u, t8.u, t8.u, , 1);
CS(INT16, strtoll10, t64.i, t16.i, t16.u, le16toh, 2);
CS(UINT16, strtoull10, t64.u, t16.u, t16.u, le16toh, 2);
CS(INT32, strtoll10, t64.i, t32.i, t32.u, le32toh, 4);
CS(UINT32, strtoull10, t64.u, t32.u, t32.u, le32toh, 4);
CS(INT64, strtoll10, t64.i, t64.i, t64.u, le64toh, 8);
CS(UINT64, strtoull10, t64.u, t64.u, t64.u, le64toh, 8);
CS(FLOAT32, strtod, t64.d, t32.f, t32.u, le32toh, 4);
CS(FLOAT64, strtod, t64.d, t64.d, t64.u, le64toh, 8);
#undef CS
default:
PyErr_SetString(PyExc_TypeError, "unknown type");
return NULL;
}
/* Done this line */
written++;
}
fflush(self->file);
/* Build return value and return */
offset = buf - data;
PyObject *o;
o = Py_BuildValue("(iiLi)", written, offset,
(long long)last_timestamp, linenum);
return o;
err:
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
bad_timestamp:
return raise_str(linenum, buf - linestart + 1,
ERR_OTHER, "bad timestamp");
cant_parse_value:
return raise_str(linenum, buf - linestart + 1,
ERR_OTHER, "can't parse value");
wrong_number_of_values:
return raise_str(linenum, buf - linestart + 1,
ERR_OTHER, "wrong number of values");
value_out_of_range:
return raise_str(linenum, buf - linestart + 1,
ERR_OTHER, "value out of range");
extra_data_on_line:
return raise_str(linenum, buf - linestart + 1,
ERR_OTHER, "extra data on line");
}
/****
* Append from binary data
*/
/* .append_binary(count, data, offset, linenum, start, end, last_timestamp) */
static PyObject *Rocket_append_binary(Rocket *self, PyObject *args)
{
int count;
const uint8_t *data;
int data_len;
int linenum;
int offset;
long long ll1, ll2, ll3;
timestamp_t start;
timestamp_t end;
timestamp_t last_timestamp;
if (!PyArg_ParseTuple(args, "it#iiLLL:append_binary",
&count, &data, &data_len, &offset,
&linenum, &ll1, &ll2, &ll3))
return NULL;
start = ll1;
end = ll2;
last_timestamp = ll3;
/* Advance to offset */
if (offset > data_len)
return raise_str(0, 0, ERR_OTHER, "bad offset");
data += offset;
data_len -= offset;
/* Figure out max number of rows to insert */
int rows = data_len / self->binary_size;
if (rows > count)
rows = count;
/* Check timestamps */
timestamp_t ts;
int i;
for (i = 0; i < rows; i++) {
/* Read raw timestamp, byteswap if needed */
memcpy(&ts, &data[i * self->binary_size], 8);
ts = le64toh(ts);
/* Check limits */
if (ts <= last_timestamp)
return raise_int(i, 0, ERR_NON_MONOTONIC, ts);
last_timestamp = ts;
if (ts < start || ts >= end)
return raise_int(i, 0, ERR_OUT_OF_INTERVAL, ts);
}
/* Write binary data */
if (fwrite(data, self->binary_size, rows, self->file) != rows) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
fflush(self->file);
/* Build return value and return */
PyObject *o;
o = Py_BuildValue("(iiLi)", rows, offset + rows * self->binary_size,
(long long)last_timestamp, linenum);
return o;
}
/****
* Extract to string
*/
static PyObject *Rocket_extract_string(Rocket *self, PyObject *args)
{
long count;
long offset;
if (!PyArg_ParseTuple(args, "ll", &offset, &count))
return NULL;
if (!self->file) {
PyErr_SetString(PyExc_Exception, "no file");
return NULL;
}
/* Seek to target location */
if (fseek(self->file, offset, SEEK_SET) < 0) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
char *str = NULL, *new;
long len_alloc = 0;
long len = 0;
int ret;
/* min space free in string (and the maximum length of one
line); this is generous */
const int min_free = 32 * MAX_LAYOUT_COUNT;
/* how much to allocate at once */
const int alloc_size = 1048576;
int row, i;
union8_t t8;
union16_t t16;
union32_t t32;
union64_t t64;
for (row = 0; row < count; row++) {
/* Make sure there's space for a line */
if ((len_alloc - len) < min_free) {
/* grow by 1 meg at a time */
len_alloc += alloc_size;
new = realloc(str, len_alloc);
if (new == NULL)
goto err;
str = new;
}
/* Read and print timestamp */
if (fread(&t64.u, 8, 1, self->file) != 1)
goto err;
t64.u = le64toh(t64.u);
ret = sprintf(&str[len], "%" PRId64, t64.i);
if (ret <= 0)
goto err;
len += ret;
/* Read and print values */
switch (self->layout_type) {
#define CASE(type, fmt, fmttype, disktype, letoh, bytes) \
case LAYOUT_TYPE_##type: \
/* read and format in a loop */ \
for (i = 0; i < self->layout_count; i++) { \
if (fread(&disktype, bytes, \
1, self->file) != 1) \
goto err; \
disktype = letoh(disktype); \
ret = sprintf(&str[len], " " fmt, \
fmttype); \
if (ret <= 0) \
goto err; \
len += ret; \
} \
break
CASE(INT8, "%" PRId8, t8.i, t8.u, , 1);
CASE(UINT8, "%" PRIu8, t8.u, t8.u, , 1);
CASE(INT16, "%" PRId16, t16.i, t16.u, le16toh, 2);
CASE(UINT16, "%" PRIu16, t16.u, t16.u, le16toh, 2);
CASE(INT32, "%" PRId32, t32.i, t32.u, le32toh, 4);
CASE(UINT32, "%" PRIu32, t32.u, t32.u, le32toh, 4);
CASE(INT64, "%" PRId64, t64.i, t64.u, le64toh, 8);
CASE(UINT64, "%" PRIu64, t64.u, t64.u, le64toh, 8);
/* These next two are a bit debatable. floats
are 6-9 significant figures, so we print 7.
Doubles are 15-19, so we print 17. This is
similar to the old prep format for float32.
*/
CASE(FLOAT32, "%.6e", t32.f, t32.u, le32toh, 4);
CASE(FLOAT64, "%.16e", t64.d, t64.u, le64toh, 8);
#undef CASE
default:
PyErr_SetString(PyExc_TypeError, "unknown type");
if (str) free(str);
return NULL;
}
str[len++] = '\n';
}
PyObject *pystr = PyString_FromStringAndSize(str, len);
free(str);
return pystr;
err:
if (str) free(str);
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
/****
* Extract to binary string containing raw little-endian binary data
*/
static PyObject *Rocket_extract_binary(Rocket *self, PyObject *args)
{
long count;
long offset;
if (!PyArg_ParseTuple(args, "ll", &offset, &count))
return NULL;
if (!self->file) {
PyErr_SetString(PyExc_Exception, "no file");
return NULL;
}
/* Seek to target location */
if (fseek(self->file, offset, SEEK_SET) < 0) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
uint8_t *str;
int len = count * self->binary_size;
str = malloc(len);
if (str == NULL) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
/* Data in the file is already in the desired little-endian
binary format, so just read it directly. */
if (fread(str, self->binary_size, count, self->file) != count) {
free(str);
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
PyObject *pystr = PyBytes_FromStringAndSize((char *)str, len);
free(str);
return pystr;
}
/****
* Extract timestamp
*/
static PyObject *Rocket_extract_timestamp(Rocket *self, PyObject *args)
{
long offset;
union64_t t64;
if (!PyArg_ParseTuple(args, "l", &offset))
return NULL;
if (!self->file) {
PyErr_SetString(PyExc_Exception, "no file");
return NULL;
}
/* Seek to target location and read timestamp */
if ((fseek(self->file, offset, SEEK_SET) < 0) ||
(fread(&t64.u, 8, 1, self->file) != 1)) {
PyErr_SetFromErrno(PyExc_OSError);
return NULL;
}
/* Convert and return */
t64.u = le64toh(t64.u);
return Py_BuildValue("L", (long long)t64.i);
}
/****
* Module and type setup
*/
static PyGetSetDef Rocket_getsetters[] = {
{ "file_size", (getter)Rocket_get_file_size, NULL,
"file size in bytes", NULL },
{ NULL },
};
static PyMemberDef Rocket_members[] = {
{ "binary_size", T_INT, offsetof(Rocket, binary_size), 0,
"binary size per row" },
{ NULL },
};
static PyMethodDef Rocket_methods[] = {
{ "close",
(PyCFunction)Rocket_close, METH_NOARGS,
"close(self)\n\n"
"Close file handle" },
{ "append_string",
(PyCFunction)Rocket_append_string, METH_VARARGS,
"append_string(self, count, data, offset, line, start, end, ts)\n\n"
"Parse string and append data.\n"
"\n"
" count: maximum number of rows to add\n"
" data: string data\n"
" offset: byte offset into data to start parsing\n"
" line: current line number of data\n"
" start: starting timestamp for interval\n"
" end: end timestamp for interval\n"
" ts: last timestamp that was previously parsed\n"
"\n"
"Raises ParseError if timestamps are non-monotonic, outside\n"
"the start/end interval etc.\n"
"\n"
"On success, return a tuple:\n"
" added_rows: how many rows were added from the file\n"
" data_offset: current offset into the data string\n"
" last_timestamp: last timestamp we parsed\n"
" linenum: current line number" },
{ "append_binary",
(PyCFunction)Rocket_append_binary, METH_VARARGS,
"append_binary(self, count, data, offset, line, start, end, ts)\n\n"
"Append binary data, which must match the data layout.\n"
"\n"
" count: maximum number of rows to add\n"
" data: binary data\n"
" offset: byte offset into data to start adding\n"
" line: current line number (unused)\n"
" start: starting timestamp for interval\n"
" end: end timestamp for interval\n"
" ts: last timestamp that was previously parsed\n"
"\n"
"Raises ParseError if timestamps are non-monotonic, outside\n"
"the start/end interval etc.\n"
"\n"
"On success, return a tuple:\n"
" added_rows: how many rows were added from the file\n"
" data_offset: current offset into the data string\n"
" last_timestamp: last timestamp we parsed\n"
" linenum: current line number (copied from argument)" },
{ "extract_string",
(PyCFunction)Rocket_extract_string, METH_VARARGS,
"extract_string(self, offset, count)\n\n"
"Extract count rows of data from the file at offset offset.\n"
"Return an ascii formatted string according to the layout" },
{ "extract_binary",
(PyCFunction)Rocket_extract_binary, METH_VARARGS,
"extract_binary(self, offset, count)\n\n"
"Extract count rows of data from the file at offset offset.\n"
"Return a raw binary string of data matching the data layout." },
{ "extract_timestamp",
(PyCFunction)Rocket_extract_timestamp, METH_VARARGS,
"extract_timestamp(self, offset)\n\n"
"Extract a single timestamp from the file" },
{ NULL },
};
static PyTypeObject RocketType = {
PyObject_HEAD_INIT(NULL)
.tp_name = "rocket.Rocket",
.tp_basicsize = sizeof(Rocket),
.tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,
.tp_new = Rocket_new,
.tp_dealloc = (destructor)Rocket_dealloc,
.tp_init = (initproc)Rocket_init,
.tp_methods = Rocket_methods,
.tp_members = Rocket_members,
.tp_getset = Rocket_getsetters,
.tp_doc = ("rocket.Rocket(layout, file)\n\n"
"C implementation of the \"rocket\" data parsing\n"
"interface, which translates between the binary\n"
"format on disk and the ASCII or Python list\n"
"format used when communicating with the rest of\n"
"the system.")
};
static PyMethodDef module_methods[] = {
{ NULL },
};
PyMODINIT_FUNC
initrocket(void)
{
PyObject *module;
RocketType.tp_new = PyType_GenericNew;
if (PyType_Ready(&RocketType) < 0)
return;
module = Py_InitModule3("rocket", module_methods,
"Rocket data parsing and formatting module");
Py_INCREF(&RocketType);
PyModule_AddObject(module, "Rocket", (PyObject *)&RocketType);
ParseError = PyErr_NewException("rocket.ParseError", NULL, NULL);
Py_INCREF(ParseError);
PyModule_AddObject(module, "ParseError", ParseError);
add_parseerror_codes(module);
return;
}

549
nilmdb/server/server.py Normal file
View File

@@ -0,0 +1,549 @@
"""CherryPy-based server for accessing NILM database via HTTP"""
# Need absolute_import so that "import nilmdb" won't pull in
# nilmdb.py, but will pull the nilmdb module instead.
from __future__ import absolute_import
import nilmdb.server
from nilmdb.utils.printf import *
from nilmdb.server.errors import NilmDBError
from nilmdb.utils.time import string_to_timestamp
import cherrypy
import sys
import os
import socket
import simplejson as json
import decorator
import psutil
import traceback
from nilmdb.server.serverutil import (
chunked_response,
response_type,
workaround_cp_bug_1200,
exception_to_httperror,
CORS_allow,
json_to_request_params,
json_error_page,
cherrypy_start,
cherrypy_stop,
bool_param,
)
# Add CORS_allow tool
cherrypy.tools.CORS_allow = cherrypy.Tool('on_start_resource', CORS_allow)
class NilmApp(object):
def __init__(self, db):
self.db = db
# CherryPy apps
class Root(NilmApp):
"""Root application for NILM database"""
def __init__(self, db):
super(Root, self).__init__(db)
# /
@cherrypy.expose
def index(self):
cherrypy.response.headers['Content-Type'] = 'text/plain'
msg = sprintf("This is NilmDB version %s, running on host %s.\n",
nilmdb.__version__, socket.getfqdn())
return msg
# /favicon.ico
@cherrypy.expose
def favicon_ico(self):
raise cherrypy.NotFound()
# /version
@cherrypy.expose
@cherrypy.tools.json_out()
def version(self):
return nilmdb.__version__
# /dbinfo
@cherrypy.expose
@cherrypy.tools.json_out()
def dbinfo(self):
"""Return a dictionary with the database path,
size of the database in bytes, and free disk space in bytes"""
path = self.db.get_basepath()
usage = psutil.disk_usage(path)
dbsize = nilmdb.utils.du(path)
return { "path": path,
"size": dbsize,
"other": usage.used - dbsize,
"reserved": usage.total - usage.used - usage.free,
"free": usage.free }
class Stream(NilmApp):
"""Stream-specific operations"""
# Helpers
def _get_times(self, start_param, end_param):
(start, end) = (None, None)
try:
if start_param is not None:
start = string_to_timestamp(start_param)
except Exception:
raise cherrypy.HTTPError("400 Bad Request", sprintf(
"invalid start (%s): must be a numeric timestamp", start_param))
try:
if end_param is not None:
end = string_to_timestamp(end_param)
except Exception:
raise cherrypy.HTTPError("400 Bad Request", sprintf(
"invalid end (%s): must be a numeric timestamp", end_param))
if start is not None and end is not None:
if start >= end:
raise cherrypy.HTTPError(
"400 Bad Request",
sprintf("start must precede end (%s >= %s)",
start_param, end_param))
return (start, end)
# /stream/list
# /stream/list?layout=float32_8
# /stream/list?path=/newton/prep&extended=1
@cherrypy.expose
@cherrypy.tools.json_out()
def list(self, path = None, layout = None, extended = None):
"""List all streams in the database. With optional path or
layout parameter, just list streams that match the given path
or layout.
If extended is missing or zero, returns a list of lists
containing the path and layout: [ path, layout ]
If extended is true, returns a list of lists containing
extended info: [ path, layout, extent_min, extent_max,
total_rows, total_seconds ]. More data may be added.
"""
return self.db.stream_list(path, layout, bool(extended))
# /stream/create?path=/newton/prep&layout=float32_8
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError, ValueError)
@cherrypy.tools.CORS_allow(methods = ["POST"])
def create(self, path, layout):
"""Create a new stream in the database. Provide path
and one of the nilmdb.layout.layouts keys.
"""
return self.db.stream_create(path, layout)
# /stream/destroy?path=/newton/prep
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError)
@cherrypy.tools.CORS_allow(methods = ["POST"])
def destroy(self, path):
"""Delete a stream. Fails if any data is still present."""
return self.db.stream_destroy(path)
# /stream/rename?oldpath=/newton/prep&newpath=/newton/prep/1
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError, ValueError)
@cherrypy.tools.CORS_allow(methods = ["POST"])
def rename(self, oldpath, newpath):
"""Rename a stream."""
return self.db.stream_rename(oldpath, newpath)
# /stream/get_metadata?path=/newton/prep
# /stream/get_metadata?path=/newton/prep&key=foo&key=bar
@cherrypy.expose
@cherrypy.tools.json_out()
def get_metadata(self, path, key=None):
"""Get metadata for the named stream. If optional
key parameters are specified, only return metadata
matching the given keys."""
try:
data = self.db.stream_get_metadata(path)
except nilmdb.server.nilmdb.StreamError as e:
raise cherrypy.HTTPError("404 Not Found", e.message)
if key is None: # If no keys specified, return them all
key = data.keys()
elif not isinstance(key, list):
key = [ key ]
result = {}
for k in key:
if k in data:
result[k] = data[k]
else: # Return "None" for keys with no matching value
result[k] = None
return result
# Helper for set_metadata and get_metadata
def _metadata_helper(self, function, path, data):
if not isinstance(data, dict):
try:
data = dict(json.loads(data))
except TypeError as e:
raise NilmDBError("can't parse 'data' parameter: " + e.message)
for key in data:
if not (isinstance(data[key], basestring) or
isinstance(data[key], float) or
isinstance(data[key], int)):
raise NilmDBError("metadata values must be a string or number")
function(path, data)
# /stream/set_metadata?path=/newton/prep&data=<json>
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError, LookupError)
@cherrypy.tools.CORS_allow(methods = ["POST"])
def set_metadata(self, path, data):
"""Set metadata for the named stream, replacing any existing
metadata. Data can be json-encoded or a plain dictionary."""
self._metadata_helper(self.db.stream_set_metadata, path, data)
# /stream/update_metadata?path=/newton/prep&data=<json>
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError, LookupError, ValueError)
@cherrypy.tools.CORS_allow(methods = ["POST"])
def update_metadata(self, path, data):
"""Set metadata for the named stream, replacing any existing
metadata. Data can be json-encoded or a plain dictionary."""
self._metadata_helper(self.db.stream_update_metadata, path, data)
# /stream/insert?path=/newton/prep
@cherrypy.expose
@cherrypy.tools.json_out()
@exception_to_httperror(NilmDBError, ValueError)
@cherrypy.tools.CORS_allow(methods = ["PUT"])
def insert(self, path, start, end, binary = False):
"""
Insert new data into the database. Provide textual data
(matching the path's layout) as a HTTP PUT.
If 'binary' is True, expect raw binary data, rather than lines
of ASCII-formatted data. Raw binary data is always
little-endian and matches the database types (including an
int64 timestamp).
"""
binary = bool_param(binary)
# Important that we always read the input before throwing any
# errors, to keep lengths happy for persistent connections.
# Note that CherryPy 3.2.2 has a bug where this fails for GET
# requests, if we ever want to handle those (issue #1134)
body = cherrypy.request.body.read()
# Verify content type for binary data
content_type = cherrypy.request.headers.get('content-type')
if binary and content_type:
if content_type != "application/octet-stream":
raise cherrypy.HTTPError("400", "Content type must be "
"application/octet-stream for "
"binary data, not " + content_type)
# Check path and get layout
if len(self.db.stream_list(path = path)) != 1:
raise cherrypy.HTTPError("404", "No such stream: " + path)
# Check limits
(start, end) = self._get_times(start, end)
# Pass the data directly to nilmdb, which will parse it and
# raise a ValueError if there are any problems.
self.db.stream_insert(path, start, end, body, binary)
# Done
return
# /stream/remove?path=/newton/prep
# /stream/remove?path=/newton/prep&start=1234567890.0&end=1234567899.0
@cherrypy.expose
@cherrypy.tools.json_in()
@cherrypy.tools.CORS_allow(methods = ["POST"])
@chunked_response
@response_type("application/x-json-stream")
def remove(self, path, start = None, end = None):
"""
Remove data from the backend database. Removes all data in
the interval [start, end).
Returns the number of data points removed. Since this is a potentially
long-running operation, multiple numbers may be returned as the
data gets removed from the backend database. The total number of
points removed is the sum of all of these numbers.
"""
(start, end) = self._get_times(start, end)
if len(self.db.stream_list(path = path)) != 1:
raise cherrypy.HTTPError("404", "No such stream: " + path)
@workaround_cp_bug_1200
def content(start, end):
# Note: disable chunked responses to see tracebacks from here.
while True:
(removed, restart) = self.db.stream_remove(path, start, end)
yield json.dumps(removed) + "\r\n"
if restart is None:
break
start = restart
return content(start, end)
# /stream/intervals?path=/newton/prep
# /stream/intervals?path=/newton/prep&start=1234567890.0&end=1234567899.0
# /stream/intervals?path=/newton/prep&diffpath=/newton/prep2
@cherrypy.expose
@chunked_response
@response_type("application/x-json-stream")
def intervals(self, path, start = None, end = None, diffpath = None):
"""
Get intervals from backend database. Streams the resulting
intervals as JSON strings separated by CR LF pairs. This may
make multiple requests to the nilmdb backend to avoid causing
it to block for too long.
Returns intervals between 'start' and 'end' belonging to
'path'. If 'diff' is provided, the set-difference between
intervals in 'path' and intervals in 'diffpath' are
returned instead.
Note that the response type is the non-standard
'application/x-json-stream' for lack of a better option.
"""
(start, end) = self._get_times(start, end)
if len(self.db.stream_list(path = path)) != 1:
raise cherrypy.HTTPError("404", "No such stream: " + path)
if diffpath and len(self.db.stream_list(path = diffpath)) != 1:
raise cherrypy.HTTPError("404", "No such stream: " + diffpath)
@workaround_cp_bug_1200
def content(start, end):
# Note: disable chunked responses to see tracebacks from here.
while True:
(ints, restart) = self.db.stream_intervals(path, start, end,
diffpath)
response = ''.join([ json.dumps(i) + "\r\n" for i in ints ])
yield response
if restart is None:
break
start = restart
return content(start, end)
# /stream/extract?path=/newton/prep&start=1234567890.0&end=1234567899.0
@cherrypy.expose
@chunked_response
def extract(self, path, start = None, end = None,
count = False, markup = False, binary = False):
"""
Extract data from backend database. Streams the resulting
entries as ASCII text lines separated by newlines. This may
make multiple requests to the nilmdb backend to avoid causing
it to block for too long.
If 'count' is True, returns a count rather than actual data.
If 'markup' is True, adds comments to the stream denoting each
interval's start and end timestamp.
If 'binary' is True, return raw binary data, rather than lines
of ASCII-formatted data. Raw binary data is always
little-endian and matches the database types (including an
int64 timestamp).
"""
binary = bool_param(binary)
markup = bool_param(markup)
count = bool_param(count)
(start, end) = self._get_times(start, end)
# Check path and get layout
if len(self.db.stream_list(path = path)) != 1:
raise cherrypy.HTTPError("404", "No such stream: " + path)
if binary:
content_type = "application/octet-stream"
if markup or count:
raise cherrypy.HTTPError("400", "can't mix binary and "
"markup or count modes")
else:
content_type = "text/plain"
cherrypy.response.headers['Content-Type'] = content_type
@workaround_cp_bug_1200
def content(start, end):
# Note: disable chunked responses to see tracebacks from here.
if count:
matched = self.db.stream_extract(path, start, end,
count = True)
yield sprintf("%d\n", matched)
return
while True:
(data, restart) = self.db.stream_extract(
path, start, end, count = False,
markup = markup, binary = binary)
yield data
if restart is None:
return
start = restart
return content(start, end)
class Exiter(object):
"""App that exits the server, for testing"""
@cherrypy.expose
def index(self):
cherrypy.response.headers['Content-Type'] = 'text/plain'
def content():
yield 'Exiting by request'
raise SystemExit
return content()
index._cp_config = { 'response.stream': True }
class Server(object):
def __init__(self, db, host = '127.0.0.1', port = 8080,
stoppable = False, # whether /exit URL exists
embedded = True, # hide diagnostics and output, etc
fast_shutdown = False, # don't wait for clients to disconn.
force_traceback = False, # include traceback in all errors
basepath = '', # base URL path for cherrypy.tree
):
# Save server version, just for verification during tests
self.version = nilmdb.__version__
self.embedded = embedded
self.db = db
if not getattr(db, "_thread_safe", None):
raise KeyError("Database object " + str(db) + " doesn't claim "
"to be thread safe. You should pass "
"nilmdb.utils.serializer_proxy(NilmDB)(args) "
"rather than NilmDB(args).")
# Build up global server configuration
cherrypy.config.update({
'server.socket_host': host,
'server.socket_port': port,
'engine.autoreload_on': False,
'server.max_request_body_size': 8*1024*1024,
})
if self.embedded:
cherrypy.config.update({ 'environment': 'embedded' })
# Build up application specific configuration
app_config = {}
app_config.update({
'error_page.default': self.json_error_page,
})
# Some default headers to just help identify that things are working
app_config.update({ 'response.headers.X-Jim-Is-Awesome': 'yeah' })
# Set up Cross-Origin Resource Sharing (CORS) handler so we
# can correctly respond to browsers' CORS preflight requests.
# This also limits verbs to GET and HEAD by default.
app_config.update({ 'tools.CORS_allow.on': True,
'tools.CORS_allow.methods': ['GET', 'HEAD'] })
# Configure the 'json_in' tool to also allow other content-types
# (like x-www-form-urlencoded), and to treat JSON as a dict that
# fills requests.param.
app_config.update({ 'tools.json_in.force': False,
'tools.json_in.processor': json_to_request_params })
# Send tracebacks in error responses. They're hidden by the
# error_page function for client errors (code 400-499).
app_config.update({ 'request.show_tracebacks' : True })
self.force_traceback = force_traceback
# Patch CherryPy error handler to never pad out error messages.
# This isn't necessary, but then again, neither is padding the
# error messages.
cherrypy._cperror._ie_friendly_error_sizes = {}
# Build up the application and mount it
root = Root(self.db)
root.stream = Stream(self.db)
if stoppable:
root.exit = Exiter()
cherrypy.tree.apps = {}
cherrypy.tree.mount(root, basepath, config = { "/" : app_config })
# Shutdowns normally wait for clients to disconnect. To speed
# up tests, set fast_shutdown = True
if fast_shutdown:
# Setting timeout to 0 triggers os._exit(70) at shutdown, grr...
cherrypy.server.shutdown_timeout = 0.01
else:
cherrypy.server.shutdown_timeout = 5
# Set up the WSGI application pointer for external programs
self.wsgi_application = cherrypy.tree
def json_error_page(self, status, message, traceback, version):
"""Return a custom error page in JSON so the client can parse it"""
return json_error_page(status, message, traceback, version,
self.force_traceback)
def start(self, blocking = False, event = None):
cherrypy_start(blocking, event, self.embedded)
def stop(self):
cherrypy_stop()
# Use a single global nilmdb.server.NilmDB and nilmdb.server.Server
# instance since the database can only be opened once. For this to
# work, the web server must use only a single process and single
# Python interpreter. Multiple threads are OK.
_wsgi_server = None
def wsgi_application(dbpath, basepath): # pragma: no cover
"""Return a WSGI application object with a database at the
specified path.
'dbpath' is a filesystem location, e.g. /home/nilm/db
'basepath' is the URL path of the application base, which
is the same as the first argument to Apache's WSGIScriptAlias
directive.
"""
def application(environ, start_response):
global _wsgi_server
if _wsgi_server is None:
# Try to start the server
try:
db = nilmdb.utils.serializer_proxy(nilmdb.server.NilmDB)(dbpath)
_wsgi_server = nilmdb.server.Server(
db, embedded = True,
basepath = basepath.rstrip('/'))
except Exception:
# Build an error message on failure
import pprint
err = sprintf("Initializing database at path '%s' failed:\n\n",
dbpath)
err += traceback.format_exc()
try:
import pwd
import grp
err += sprintf("\nRunning as: uid=%d (%s), gid=%d (%s) "
"on host %s, pid %d\n",
os.getuid(), pwd.getpwuid(os.getuid())[0],
os.getgid(), grp.getgrgid(os.getgid())[0],
socket.gethostname(), os.getpid())
except ImportError:
pass
err += sprintf("\nEnvironment:\n%s\n", pprint.pformat(environ))
if _wsgi_server is None:
# Serve up the error with our own mini WSGI app.
headers = [ ('Content-type', 'text/plain'),
('Content-length', str(len(err))) ]
start_response("500 Internal Server Error", headers)
return [err]
# Call the normal application
return _wsgi_server.wsgi_application(environ, start_response)
return application

214
nilmdb/server/serverutil.py Normal file
View File

@@ -0,0 +1,214 @@
"""Miscellaneous decorators and other helpers for running a CherryPy
server"""
import cherrypy
import sys
import os
import decorator
import simplejson as json
# Helper to parse parameters into booleans
def bool_param(s):
"""Return a bool indicating whether parameter 's' was True or False,
supporting a few different types for 's'."""
try:
ss = s.lower()
if ss in [ "0", "false", "f", "no", "n" ]:
return False
if ss in [ "1", "true", "t", "yes", "y" ]:
return True
except Exception:
return bool(s)
raise cherrypy.HTTPError("400 Bad Request",
"can't parse parameter: " + ss)
# Decorators
def chunked_response(func):
"""Decorator to enable chunked responses."""
# Set this to False to get better tracebacks from some requests
# (/stream/extract, /stream/intervals).
func._cp_config = { 'response.stream': True }
return func
def response_type(content_type):
"""Return a decorator-generating function that sets the
response type to the specified string."""
def wrapper(func, *args, **kwargs):
cherrypy.response.headers['Content-Type'] = content_type
return func(*args, **kwargs)
return decorator.decorator(wrapper)
@decorator.decorator
def workaround_cp_bug_1200(func, *args, **kwargs): # pragma: no cover
"""Decorator to work around CherryPy bug #1200 in a response
generator.
Even if chunked responses are disabled, LookupError or
UnicodeError exceptions may still be swallowed by CherryPy due to
bug #1200. This throws them as generic Exceptions instead so that
they make it through.
"""
exc_info = None
try:
for val in func(*args, **kwargs):
yield val
except (LookupError, UnicodeError):
# Re-raise it, but maintain the original traceback
exc_info = sys.exc_info()
new_exc = Exception(exc_info[0].__name__ + ": " + str(exc_info[1]))
raise new_exc, None, exc_info[2]
finally:
del exc_info
def exception_to_httperror(*expected):
"""Return a decorator-generating function that catches expected
errors and throws a HTTPError describing it instead.
@exception_to_httperror(NilmDBError, ValueError)
def foo():
pass
"""
def wrapper(func, *args, **kwargs):
exc_info = None
try:
return func(*args, **kwargs)
except expected:
# Re-raise it, but maintain the original traceback
exc_info = sys.exc_info()
new_exc = cherrypy.HTTPError("400 Bad Request", str(exc_info[1]))
raise new_exc, None, exc_info[2]
finally:
del exc_info
# We need to preserve the function's argspecs for CherryPy to
# handle argument errors correctly. Decorator.decorator takes
# care of that.
return decorator.decorator(wrapper)
# Custom CherryPy tools
def CORS_allow(methods):
"""This does several things:
Handles CORS preflight requests.
Adds Allow: header to all requests.
Raise 405 if request.method not in method.
It is similar to cherrypy.tools.allow, with the CORS stuff added.
Add this to CherryPy with:
cherrypy.tools.CORS_allow = cherrypy.Tool('on_start_resource', CORS_allow)
"""
request = cherrypy.request.headers
response = cherrypy.response.headers
if not isinstance(methods, (tuple, list)): # pragma: no cover
methods = [ methods ]
methods = [ m.upper() for m in methods if m ]
if not methods: # pragma: no cover
methods = [ 'GET', 'HEAD' ]
elif 'GET' in methods and 'HEAD' not in methods: # pragma: no cover
methods.append('HEAD')
response['Allow'] = ', '.join(methods)
# Allow all origins
if 'Origin' in request:
response['Access-Control-Allow-Origin'] = request['Origin']
# If it's a CORS request, send response.
request_method = request.get("Access-Control-Request-Method", None)
request_headers = request.get("Access-Control-Request-Headers", None)
if (cherrypy.request.method == "OPTIONS" and
request_method and request_headers):
response['Access-Control-Allow-Headers'] = request_headers
response['Access-Control-Allow-Methods'] = ', '.join(methods)
# Try to stop further processing and return a 200 OK
cherrypy.response.status = "200 OK"
cherrypy.response.body = ""
cherrypy.request.handler = lambda: ""
return
# Reject methods that were not explicitly allowed
if cherrypy.request.method not in methods:
raise cherrypy.HTTPError(405)
# Helper for json_in tool to process JSON data into normal request
# parameters.
def json_to_request_params(body):
cherrypy.lib.jsontools.json_processor(body)
if not isinstance(cherrypy.request.json, dict):
raise cherrypy.HTTPError(415)
cherrypy.request.params.update(cherrypy.request.json)
# Used as an "error_page.default" handler
def json_error_page(status, message, traceback, version,
force_traceback = False):
"""Return a custom error page in JSON so the client can parse it"""
errordata = { "status" : status,
"message" : message,
"traceback" : traceback }
# Don't send a traceback if the error was 400-499 (client's fault)
try:
code = int(status.split()[0])
if not force_traceback:
if code >= 400 and code <= 499:
errordata["traceback"] = ""
except Exception: # pragma: no cover
pass
# Override the response type, which was previously set to text/html
cherrypy.serving.response.headers['Content-Type'] = (
"application/json;charset=utf-8" )
# Undo the HTML escaping that cherrypy's get_error_page function applies
# (cherrypy issue 1135)
for k, v in errordata.iteritems():
v = v.replace("&lt;","<")
v = v.replace("&gt;",">")
v = v.replace("&amp;","&")
errordata[k] = v
return json.dumps(errordata, separators=(',',':'))
# Start/stop CherryPy standalone server
def cherrypy_start(blocking = False, event = False, embedded = False):
"""Start the CherryPy server, handling errors and signals
somewhat gracefully."""
if not embedded: # pragma: no cover
# Handle signals nicely
if hasattr(cherrypy.engine, "signal_handler"):
cherrypy.engine.signal_handler.subscribe()
if hasattr(cherrypy.engine, "console_control_handler"):
cherrypy.engine.console_control_handler.subscribe()
# Cherrypy stupidly calls os._exit(70) when it can't bind the
# port. At least try to print a reasonable error and continue
# in this case, rather than just dying silently (as we would
# otherwise do in embedded mode)
real_exit = os._exit
def fake_exit(code): # pragma: no cover
if code == os.EX_SOFTWARE:
fprintf(sys.stderr, "error: CherryPy called os._exit!\n")
else:
real_exit(code)
os._exit = fake_exit
cherrypy.engine.start()
os._exit = real_exit
# Signal that the engine has started successfully
if event is not None:
event.set()
if blocking:
try:
cherrypy.engine.wait(cherrypy.engine.states.EXITING,
interval = 0.1, channel = 'main')
except (KeyboardInterrupt, IOError): # pragma: no cover
cherrypy.engine.log('Keyboard Interrupt: shutting down bus')
cherrypy.engine.exit()
except SystemExit: # pragma: no cover
cherrypy.engine.log('SystemExit raised: shutting down bus')
cherrypy.engine.exit()
raise
# Stop CherryPy server
def cherrypy_stop():
cherrypy.engine.exit()

17
nilmdb/utils/__init__.py Normal file
View File

@@ -0,0 +1,17 @@
"""NilmDB utilities"""
from __future__ import absolute_import
from nilmdb.utils.timer import Timer
from nilmdb.utils.serializer import serializer_proxy
from nilmdb.utils.lrucache import lru_cache
from nilmdb.utils.diskusage import du, human_size
from nilmdb.utils.mustclose import must_close
from nilmdb.utils import atomic
import nilmdb.utils.threadsafety
import nilmdb.utils.fallocate
import nilmdb.utils.time
import nilmdb.utils.iterator
import nilmdb.utils.interval
import nilmdb.utils.lock
import nilmdb.utils.sort
import nilmdb.utils.unicode

26
nilmdb/utils/atomic.py Normal file
View File

@@ -0,0 +1,26 @@
# Atomic file writing helper.
import os
def replace_file(filename, content):
"""Attempt to atomically and durably replace the filename with the
given contents. This is intended to be 'pretty good on most
OSes', but not necessarily bulletproof."""
newfilename = filename + ".new"
# Write to new file, flush it
with open(newfilename, "wb") as f:
f.write(content)
f.flush()
os.fsync(f.fileno())
# Move new file over old one
try:
os.rename(newfilename, filename)
except OSError: # pragma: no cover
# Some OSes might not support renaming over an existing file.
# This is definitely NOT atomic!
os.remove(filename)
os.rename(newfilename, filename)

View File

@@ -1,8 +1,8 @@
import nilmdb
import os
import errno
from math import log
def sizeof_fmt(num):
def human_size(num):
"""Human friendly file size"""
unit_list = zip(['bytes', 'kiB', 'MiB', 'GiB', 'TiB'], [0, 0, 1, 2, 2])
if num > 1:
@@ -16,15 +16,18 @@ def sizeof_fmt(num):
if num == 1: # pragma: no cover
return '1 byte'
def du_bytes(path):
"""Like du -sb, returns total size of path in bytes."""
size = os.path.getsize(path)
if os.path.isdir(path):
for file in os.listdir(path):
filepath = os.path.join(path, file)
size += du_bytes(filepath)
return size
def du(path):
"""Like du -sh, returns total size of path as a human-readable string."""
return sizeof_fmt(du_bytes(path))
"""Like du -sb, returns total size of path in bytes. Ignore
errors that might occur if we encounter broken symlinks or
files in the process of being removed."""
try:
size = os.path.getsize(path)
if os.path.isdir(path):
for thisfile in os.listdir(path):
filepath = os.path.join(path, thisfile)
size += du(filepath)
return size
except OSError as e: # pragma: no cover
if e.errno != errno.ENOENT:
raise
return 0

49
nilmdb/utils/fallocate.py Normal file
View File

@@ -0,0 +1,49 @@
# Implementation of hole punching via fallocate, if the OS
# and filesystem support it.
try:
import os
import ctypes
import ctypes.util
def make_fallocate():
libc_name = ctypes.util.find_library('c')
libc = ctypes.CDLL(libc_name, use_errno=True)
_fallocate = libc.fallocate
_fallocate.restype = ctypes.c_int
_fallocate.argtypes = [ ctypes.c_int, ctypes.c_int,
ctypes.c_int64, ctypes.c_int64 ]
del libc
del libc_name
def fallocate(fd, mode, offset, len_):
res = _fallocate(fd, mode, offset, len_)
if res != 0: # pragma: no cover
errno = ctypes.get_errno()
raise IOError(errno, os.strerror(errno))
return fallocate
fallocate = make_fallocate()
del make_fallocate
except Exception: # pragma: no cover
fallocate = None
FALLOC_FL_KEEP_SIZE = 0x01
FALLOC_FL_PUNCH_HOLE = 0x02
def punch_hole(filename, offset, length, ignore_errors = True):
"""Punch a hole in the file. This isn't well supported, so errors
are ignored by default."""
try:
if fallocate is None: # pragma: no cover
raise IOError("fallocate not available")
with open(filename, "r+") as f:
fallocate(f.fileno(),
FALLOC_FL_KEEP_SIZE | FALLOC_FL_PUNCH_HOLE,
offset, length)
except IOError: # pragma: no cover
if ignore_errors:
return
raise

147
nilmdb/utils/interval.py Normal file
View File

@@ -0,0 +1,147 @@
"""Interval. Like nilmdb.server.interval, but re-implemented here
in plain Python so clients have easier access to it, and with a few
helper functions.
Intervals are half-open, ie. they include data points with timestamps
[start, end)
"""
import nilmdb.utils.time
import nilmdb.utils.iterator
class IntervalError(Exception):
"""Error due to interval overlap, etc"""
pass
# Interval
class Interval:
"""Represents an interval of time."""
def __init__(self, start, end):
"""
'start' and 'end' are arbitrary numbers that represent time
"""
if start >= end:
# Explicitly disallow zero-width intervals (since they're half-open)
raise IntervalError("start %s must precede end %s" % (start, end))
self.start = start
self.end = end
def __repr__(self):
s = repr(self.start) + ", " + repr(self.end)
return self.__class__.__name__ + "(" + s + ")"
def __str__(self):
return ("[" + nilmdb.utils.time.timestamp_to_string(self.start) +
" -> " + nilmdb.utils.time.timestamp_to_string(self.end) + ")")
def human_string(self):
return ("[ " + nilmdb.utils.time.timestamp_to_human(self.start) +
" -> " + nilmdb.utils.time.timestamp_to_human(self.end) + " ]")
def __cmp__(self, other):
"""Compare two intervals. If non-equal, order by start then end"""
return cmp(self.start, other.start) or cmp(self.end, other.end)
def intersects(self, other):
"""Return True if two Interval objects intersect"""
if not isinstance(other, Interval):
raise TypeError("need an Interval")
if self.end <= other.start or self.start >= other.end:
return False
return True
def subset(self, start, end):
"""Return a new Interval that is a subset of this one"""
# A subclass that tracks additional data might override this.
if start < self.start or end > self.end:
raise IntervalError("not a subset")
return Interval(start, end)
def _interval_math_helper(a, b, op, subset = True):
"""Helper for set_difference, intersection functions,
to compute interval subsets based on a math operator on ranges
present in A and B. Subsets are computed from A, or new intervals
are generated if subset = False."""
# Iterate through all starts and ends in sorted order. Add a
# tag to the iterator so that we can figure out which one they
# were, after sorting.
def decorate(it, key_start, key_end):
for i in it:
yield i.start, key_start, i
yield i.end, key_end, i
a_iter = decorate(iter(a), 0, 2)
b_iter = decorate(iter(b), 1, 3)
# Now iterate over the timestamps of each start and end.
# At each point, evaluate which type of end it is, to determine
# how to build up the output intervals.
a_interval = None
in_a = False
in_b = False
out_start = None
for (ts, k, i) in nilmdb.utils.iterator.imerge(a_iter, b_iter):
if k == 0:
a_interval = i
in_a = True
elif k == 1:
in_b = True
elif k == 2:
in_a = False
elif k == 3:
in_b = False
include = op(in_a, in_b)
if include and out_start is None:
out_start = ts
elif not include:
if out_start is not None and out_start != ts:
if subset:
yield a_interval.subset(out_start, ts)
else:
yield Interval(out_start, ts)
out_start = None
def set_difference(a, b):
"""
Compute the difference (a \\ b) between the intervals in 'a' and
the intervals in 'b'; i.e., the ranges that are present in 'self'
but not 'other'.
'a' and 'b' must both be iterables.
Returns a generator that yields each interval in turn.
Output intervals are built as subsets of the intervals in the
first argument (a).
"""
return _interval_math_helper(a, b, (lambda a, b: a and not b))
def intersection(a, b):
"""
Compute the intersection between the intervals in 'a' and the
intervals in 'b'; i.e., the ranges that are present in both 'a'
and 'b'.
'a' and 'b' must both be iterables.
Returns a generator that yields each interval in turn.
Output intervals are built as subsets of the intervals in the
first argument (a).
"""
return _interval_math_helper(a, b, (lambda a, b: a and b))
def optimize(it):
"""
Given an iterable 'it' with intervals, optimize them by joining
together intervals that are adjacent in time, and return a generator
that yields the new intervals.
"""
saved_int = None
for interval in it:
if saved_int is not None:
if saved_int.end == interval.start:
interval.start = saved_int.start
else:
yield saved_int
saved_int = interval
if saved_int is not None:
yield saved_int

36
nilmdb/utils/iterator.py Normal file
View File

@@ -0,0 +1,36 @@
# Misc iterator tools
# Iterator merging, based on http://code.activestate.com/recipes/491285/
import heapq
def imerge(*iterables):
'''Merge multiple sorted inputs into a single sorted output.
Equivalent to: sorted(itertools.chain(*iterables))
>>> list(imerge([1,3,5,7], [0,2,4,8], [5,10,15,20], [], [25]))
[0, 1, 2, 3, 4, 5, 5, 7, 8, 10, 15, 20, 25]
'''
heappop, siftup, _Stop = heapq.heappop, heapq._siftup, StopIteration
h = []
h_append = h.append
for it in map(iter, iterables):
try:
next = it.next
h_append([next(), next])
except _Stop:
pass
heapq.heapify(h)
while 1:
try:
while 1:
v, next = s = h[0] # raises IndexError when h is empty
yield v
s[0] = next() # raises StopIteration when exhausted
siftup(h, 0) # restore heap condition
except _Stop:
heappop(h) # remove empty iterator
except IndexError:
return

33
nilmdb/utils/lock.py Normal file
View File

@@ -0,0 +1,33 @@
# File locking
import warnings
try:
import fcntl
import errno
def exclusive_lock(f):
"""Acquire an exclusive lock. Returns True on successful
lock, or False on error."""
try:
fcntl.flock(f.fileno(), fcntl.LOCK_EX | fcntl.LOCK_NB)
except IOError as e:
if e.errno in (errno.EACCES, errno.EAGAIN):
return False
else: # pragma: no cover
raise
return True
def exclusive_unlock(f):
"""Release an exclusive lock."""
fcntl.flock(f.fileno(), fcntl.LOCK_UN)
except ImportError: # pragma: no cover
def exclusive_lock(f):
"""Dummy lock function -- does not lock!"""
warnings.warn("Pretending to lock " + str(f))
return True
def exclusive_unlock(f):
"""Release an exclusive lock."""
return

76
nilmdb/utils/lrucache.py Normal file
View File

@@ -0,0 +1,76 @@
# Memoize a function's return value with a least-recently-used cache
# Based on:
# http://code.activestate.com/recipes/498245-lru-and-lfu-cache-decorators/
# with added 'destructor' functionality.
import collections
import decorator
def lru_cache(size = 10, onremove = None, keys = slice(None)):
"""Least-recently-used cache decorator.
@lru_cache(size = 10, onevict = None)
def f(...):
pass
Given a function and arguments, memoize its return value. Up to
'size' elements are cached. 'keys' is a slice object that
represents which arguments are used as the cache key.
When evicting a value from the cache, call the function
'onremove' with the value that's being evicted.
Call f.cache_remove(...) to evict the cache entry with the given
arguments. Call f.cache_remove_all() to evict all entries.
f.cache_hits and f.cache_misses give statistics.
"""
def decorate(func):
cache = collections.OrderedDict() # order: least- to most-recent
def evict(value):
if onremove:
onremove(value)
def wrapper(orig, *args, **kwargs):
if kwargs:
raise NotImplementedError("kwargs not supported")
key = args[keys]
try:
value = cache.pop(key)
orig.cache_hits += 1
except KeyError:
value = orig(*args)
orig.cache_misses += 1
if len(cache) >= size:
evict(cache.popitem(0)[1]) # evict LRU cache entry
cache[key] = value # (re-)insert this key at end
return value
def cache_remove(*args):
"""Remove the described key from this cache, if present."""
key = args
if key in cache:
evict(cache.pop(key))
else:
if len(cache) > 0 and len(args) != len(cache.iterkeys().next()):
raise KeyError("trying to remove from LRU cache, but "
"number of arguments doesn't match the "
"cache key length")
def cache_remove_all():
for key in cache:
evict(cache.pop(key))
def cache_info():
return (func.cache_hits, func.cache_misses)
new = decorator.decorator(wrapper, func)
func.cache_hits = 0
func.cache_misses = 0
new.cache_info = cache_info
new.cache_remove = cache_remove
new.cache_remove_all = cache_remove_all
return new
return decorate

61
nilmdb/utils/mustclose.py Normal file
View File

@@ -0,0 +1,61 @@
from nilmdb.utils.printf import *
import sys
import inspect
import decorator
def must_close(errorfile = sys.stderr, wrap_verify = False):
"""Class decorator that warns on 'errorfile' at deletion time if
the class's close() member wasn't called.
If 'wrap_verify' is True, every class method is wrapped with a
verifier that will raise AssertionError if the .close() method has
already been called."""
def class_decorator(cls):
def wrap_class_method(wrapper):
try:
orig = getattr(cls, wrapper.__name__).im_func
except Exception:
orig = lambda x: None
setattr(cls, wrapper.__name__, decorator.decorator(wrapper, orig))
@wrap_class_method
def __init__(orig, self, *args, **kwargs):
ret = orig(self, *args, **kwargs)
self.__dict__["_must_close"] = True
self.__dict__["_must_close_initialized"] = True
return ret
@wrap_class_method
def __del__(orig, self, *args, **kwargs):
if "_must_close" in self.__dict__:
fprintf(errorfile, "error: %s.close() wasn't called!\n",
self.__class__.__name__)
return orig(self, *args, **kwargs)
@wrap_class_method
def close(orig, self, *args, **kwargs):
if "_must_close" in self.__dict__:
del self._must_close
return orig(self, *args, **kwargs)
# Optionally wrap all other functions
def verifier(orig, self, *args, **kwargs):
if ("_must_close" not in self.__dict__ and
"_must_close_initialized" in self.__dict__):
raise AssertionError("called " + str(orig) + " after close")
return orig(self, *args, **kwargs)
if wrap_verify:
for (name, method) in inspect.getmembers(cls, inspect.ismethod):
# Skip class methods
if method.__self__ is not None:
continue
# Skip some methods
if name in [ "__del__", "__init__" ]:
continue
# Set up wrapper
setattr(cls, name, decorator.decorator(verifier,
method.im_func))
return cls
return class_decorator

123
nilmdb/utils/serializer.py Normal file
View File

@@ -0,0 +1,123 @@
import Queue
import threading
import sys
import decorator
import inspect
import types
import functools
# This file provides a class that will wrap an object and serialize
# all calls to its methods. All calls to that object will be queued
# and executed from a single thread, regardless of which thread makes
# the call.
# Based partially on http://stackoverflow.com/questions/2642515/
class SerializerThread(threading.Thread):
"""Thread that retrieves call information from the queue, makes the
call, and returns the results."""
def __init__(self, classname, call_queue):
threading.Thread.__init__(self)
self.name = "Serializer-" + classname + "-" + self.name
self.call_queue = call_queue
def run(self):
while True:
result_queue, func, args, kwargs = self.call_queue.get()
# Terminate if result_queue is None
if result_queue is None:
return
exception = None
result = None
try:
result = func(*args, **kwargs) # wrapped
except:
exception = sys.exc_info()
# Ensure we delete these before returning a result, so
# we don't unncessarily hold onto a reference while
# we're waiting for the next call.
del func, args, kwargs
result_queue.put((exception, result))
del exception, result
def serializer_proxy(obj_or_type):
"""Wrap the given object or type in a SerializerObjectProxy.
Returns a SerializerObjectProxy object that proxies all method
calls to the object, as well as attribute retrievals.
The proxied requests, including instantiation, are performed in a
single thread and serialized between caller threads.
"""
class SerializerCallProxy(object):
def __init__(self, call_queue, func, objectproxy):
self.call_queue = call_queue
self.func = func
# Need to hold a reference to object proxy so it doesn't
# go away (and kill the thread) until after get called.
self.objectproxy = objectproxy
def __call__(self, *args, **kwargs):
result_queue = Queue.Queue()
self.call_queue.put((result_queue, self.func, args, kwargs))
( exc_info, result ) = result_queue.get()
if exc_info is None:
return result
else:
raise exc_info[0], exc_info[1], exc_info[2]
class SerializerObjectProxy(object):
def __init__(self, obj_or_type, *args, **kwargs):
self.__object = obj_or_type
try:
if type(obj_or_type) in (types.TypeType, types.ClassType):
classname = obj_or_type.__name__
else:
classname = obj_or_type.__class__.__name__
except AttributeError: # pragma: no cover
classname = "???"
self.__call_queue = Queue.Queue()
self.__thread = SerializerThread(classname, self.__call_queue)
self.__thread.daemon = True
self.__thread.start()
self._thread_safe = True
def __getattr__(self, key):
if key.startswith("_SerializerObjectProxy__"): # pragma: no cover
raise AttributeError
attr = getattr(self.__object, key)
if not callable(attr):
getter = SerializerCallProxy(self.__call_queue, getattr, self)
return getter(self.__object, key)
r = SerializerCallProxy(self.__call_queue, attr, self)
return r
# For an interable object, on __iter__(), save the object's
# iterator and return this proxy. On next(), call the object's
# iterator through this proxy.
def __iter__(self):
attr = getattr(self.__object, "__iter__")
self.__iter = SerializerCallProxy(self.__call_queue, attr, self)()
return self
def next(self):
return SerializerCallProxy(self.__call_queue,
self.__iter.next, self)()
def __getitem__(self, key):
return self.__getattr__("__getitem__")(key)
def __call__(self, *args, **kwargs):
"""Call this to instantiate the type, if a type was passed
to serializer_proxy. Otherwise, pass the call through."""
ret = SerializerCallProxy(self.__call_queue,
self.__object, self)(*args, **kwargs)
if type(self.__object) in (types.TypeType, types.ClassType):
# Instantiation
self.__object = ret
return self
return ret
def __del__(self):
self.__call_queue.put((None, None, None, None))
self.__thread.join()
return SerializerObjectProxy(obj_or_type)

18
nilmdb/utils/sort.py Normal file
View File

@@ -0,0 +1,18 @@
import re
def sort_human(items, key = None):
"""Human-friendly sort (/stream/2 before /stream/10)"""
def to_num(val):
try:
return int(val)
except Exception:
return val
def human_key(text):
if key:
text = key(text)
# Break into character and numeric chunks.
chunks = re.split(r'([0-9]+)', text)
return [ to_num(c) for c in chunks ]
return sorted(items, key = human_key)

View File

@@ -0,0 +1,109 @@
from nilmdb.utils.printf import *
import threading
import warnings
import types
def verify_proxy(obj_or_type, exception = False, check_thread = True,
check_concurrent = True):
"""Wrap the given object or type in a VerifyObjectProxy.
Returns a VerifyObjectProxy that proxies all method calls to the
given object, as well as attribute retrievals.
When calling methods, the following checks are performed. If
exception is True, an exception is raised. Otherwise, a warning
is printed.
check_thread = True # Warn/fail if two different threads call methods.
check_concurrent = True # Warn/fail if two functions are concurrently
# run through this proxy
"""
class Namespace(object):
pass
class VerifyCallProxy(object):
def __init__(self, func, parent_namespace):
self.func = func
self.parent_namespace = parent_namespace
def __call__(self, *args, **kwargs):
p = self.parent_namespace
this = threading.current_thread()
try:
callee = self.func.__name__
except AttributeError:
callee = "???"
if p.thread is None:
p.thread = this
p.thread_callee = callee
if check_thread and p.thread != this:
err = sprintf("unsafe threading: %s called %s.%s,"
" but %s called %s.%s",
p.thread.name, p.classname, p.thread_callee,
this.name, p.classname, callee)
if exception:
raise AssertionError(err)
else: # pragma: no cover
warnings.warn(err)
need_concur_unlock = False
if check_concurrent:
if p.concur_lock.acquire(False) == False:
err = sprintf("unsafe concurrency: %s called %s.%s "
"while %s is still in %s.%s",
this.name, p.classname, callee,
p.concur_tname, p.classname, p.concur_callee)
if exception:
raise AssertionError(err)
else: # pragma: no cover
warnings.warn(err)
else:
p.concur_tname = this.name
p.concur_callee = callee
need_concur_unlock = True
try:
ret = self.func(*args, **kwargs)
finally:
if need_concur_unlock:
p.concur_lock.release()
return ret
class VerifyObjectProxy(object):
def __init__(self, obj_or_type, *args, **kwargs):
p = Namespace()
self.__ns = p
p.thread = None
p.thread_callee = None
p.concur_lock = threading.Lock()
p.concur_tname = None
p.concur_callee = None
self.__obj = obj_or_type
try:
if type(obj_or_type) in (types.TypeType, types.ClassType):
p.classname = self.__obj.__name__
else:
p.classname = self.__obj.__class__.__name__
except AttributeError: # pragma: no cover
p.classname = "???"
def __getattr__(self, key):
if key.startswith("_VerifyObjectProxy__"): # pragma: no cover
raise AttributeError
attr = getattr(self.__obj, key)
if not callable(attr):
return VerifyCallProxy(getattr, self.__ns)(self.__obj, key)
return VerifyCallProxy(attr, self.__ns)
def __call__(self, *args, **kwargs):
"""Call this to instantiate the type, if a type was passed
to verify_proxy. Otherwise, pass the call through."""
ret = VerifyCallProxy(self.__obj, self.__ns)(*args, **kwargs)
if type(self.__obj) in (types.TypeType, types.ClassType):
# Instantiation
self.__obj = ret
return self
return ret
return VerifyObjectProxy(obj_or_type)

134
nilmdb/utils/time.py Normal file
View File

@@ -0,0 +1,134 @@
from __future__ import absolute_import
from nilmdb.utils import datetime_tz
import re
import time
# Range
min_timestamp = (-2**63)
max_timestamp = (2**63 - 1)
# Smallest representable step
epsilon = 1
def string_to_timestamp(str):
"""Convert a string that represents an integer number of microseconds
since epoch."""
try:
# Parse a string like "1234567890123456" and return an integer
return int(str)
except ValueError:
# Try parsing as a float, in case it's "1234567890123456.0"
return int(round(float(str)))
def timestamp_to_string(timestamp):
"""Convert a timestamp (integer microseconds since epoch) to a string"""
if isinstance(timestamp, float):
return str(int(round(timestamp)))
else:
return str(timestamp)
def timestamp_to_human(timestamp):
"""Convert a timestamp (integer microseconds since epoch) to a
human-readable string, using the local timezone for display
(e.g. from the TZ env var)."""
if timestamp == min_timestamp:
return "(minimum)"
if timestamp == max_timestamp:
return "(maximum)"
dt = datetime_tz.datetime_tz.fromtimestamp(timestamp_to_unix(timestamp))
return dt.strftime("%a, %d %b %Y %H:%M:%S.%f %z")
def unix_to_timestamp(unix):
"""Convert a Unix timestamp (floating point seconds since epoch)
into a NILM timestamp (integer microseconds since epoch)"""
return int(round(unix * 1e6))
seconds_to_timestamp = unix_to_timestamp
def timestamp_to_unix(timestamp):
"""Convert a NILM timestamp (integer microseconds since epoch)
into a Unix timestamp (floating point seconds since epoch)"""
return timestamp / 1e6
timestamp_to_seconds = timestamp_to_unix
def rate_to_period(hz, cycles = 1):
"""Convert a rate (in Hz) to a period (in timestamp units).
Returns an integer."""
period = unix_to_timestamp(cycles) / float(hz)
return int(round(period))
def parse_time(toparse):
"""
Parse a free-form time string and return a nilmdb timestamp
(integer microseconds since epoch). If the string doesn't contain a
timestamp, the current local timezone is assumed (e.g. from the TZ
env var).
"""
if toparse == "min":
return min_timestamp
if toparse == "max":
return max_timestamp
# If it starts with @, treat it as a NILM timestamp
# (integer microseconds since epoch)
try:
if toparse[0] == '@':
return int(toparse[1:])
except (ValueError, KeyError, IndexError):
pass
# If string isn't "now" and doesn't contain at least 4 digits,
# consider it invalid. smartparse might otherwise accept
# empty strings and strings with just separators.
if toparse != "now" and len(re.findall(r"\d", toparse)) < 4:
raise ValueError("not enough digits for a timestamp")
# Try to just parse the time as given
try:
return unix_to_timestamp(datetime_tz.datetime_tz.
smartparse(toparse).totimestamp())
except (ValueError, OverflowError):
pass
# If it's parseable as a float, treat it as a Unix or NILM
# timestamp based on its range.
try:
val = float(toparse)
# range is from about year 2001 - 2128
if val > 1e9 and val < 5e9:
return unix_to_timestamp(val)
if val > 1e15 and val < 5e15:
return val
except ValueError:
pass
# Try to extract a substring in a condensed format that we expect
# to see in a filename or header comment
res = re.search(r"(^|[^\d])(" # non-numeric or SOL
r"(199\d|2\d\d\d)" # year
r"[-/]?" # separator
r"(0[1-9]|1[012])" # month
r"[-/]?" # separator
r"([012]\d|3[01])" # day
r"[-T ]?" # separator
r"([01]\d|2[0-3])" # hour
r"[:]?" # separator
r"([0-5]\d)" # minute
r"[:]?" # separator
r"([0-5]\d)?" # second
r"([-+]\d\d\d\d)?" # timezone
r")", toparse)
if res is not None:
try:
return unix_to_timestamp(datetime_tz.datetime_tz.
smartparse(res.group(2)).totimestamp())
except ValueError:
pass
# Could also try to successively parse substrings, but let's
# just give up for now.
raise ValueError("unable to parse timestamp")
def now():
"""Return current timestamp"""
return unix_to_timestamp(time.time())

View File

@@ -2,9 +2,11 @@
# Simple timer to time a block of code, for optimization debugging
# use like:
# with nilmdb.Timer("flush"):
# with nilmdb.utils.Timer("flush"):
# foo.flush()
from __future__ import print_function
from __future__ import absolute_import
import contextlib
import time
@@ -18,4 +20,4 @@ def Timer(name = None, tosyslog = False):
import syslog
syslog.syslog(msg)
else:
print msg
print(msg)

View File

@@ -1,22 +1,18 @@
"""File-like objects that add timestamps to the input lines"""
from __future__ import absolute_import
from nilmdb.printf import *
import time
import os
import datetime_tz
from nilmdb.utils.printf import *
import nilmdb.utils.time
class Timestamper(object):
"""A file-like object that adds timestamps to lines of an input file."""
def __init__(self, file, ts_iter):
def __init__(self, infile, ts_iter):
"""file: filename, or another file-like object
ts_iter: iterator that returns a timestamp string for
each line of the file"""
if isinstance(file, basestring):
self.file = open(file, "r")
if isinstance(infile, basestring):
self.file = open(infile, "r")
else:
self.file = file
self.file = infile
self.ts_iter = ts_iter
def close(self):
@@ -55,7 +51,7 @@ class Timestamper(object):
class TimestamperRate(Timestamper):
"""Timestamper that uses a start time and a fixed rate"""
def __init__(self, file, start, rate, end = None):
def __init__(self, infile, start, rate, end = None):
"""
file: file name or object
@@ -65,44 +61,33 @@ class TimestamperRate(Timestamper):
end: If specified, raise StopIteration before outputting a value
greater than this."""
timestamp_to_string = nilmdb.utils.time.timestamp_to_string
rate_to_period = nilmdb.utils.time.rate_to_period
def iterator(start, rate, end):
n = 0
rate = float(rate)
while True:
now = start + n / rate
now = start + rate_to_period(rate, n)
if end and now >= end:
raise StopIteration
yield sprintf("%.6f ", start + n / rate)
yield timestamp_to_string(now) + " "
n += 1
# Handle case where we're passed a datetime or datetime_tz object
if "totimestamp" in dir(start):
start = start.totimestamp()
Timestamper.__init__(self, file, iterator(start, rate, end))
Timestamper.__init__(self, infile, iterator(start, rate, end))
self.start = start
self.rate = rate
def __str__(self):
start = datetime_tz.datetime_tz.fromtimestamp(self.start)
start = start.strftime("%a, %d %b %Y %H:%M:%S %Z")
return sprintf("TimestamperRate(..., start=\"%s\", rate=%g)",
str(start), self.rate)
nilmdb.utils.time.timestamp_to_human(self.start),
self.rate)
class TimestamperNow(Timestamper):
"""Timestamper that uses current time"""
def __init__(self, file):
def __init__(self, infile):
timestamp_to_string = nilmdb.utils.time.timestamp_to_string
get_now = nilmdb.utils.time.now
def iterator():
while True:
now = datetime_tz.datetime_tz.utcnow().totimestamp()
yield sprintf("%.6f ", now)
Timestamper.__init__(self, file, iterator())
yield timestamp_to_string(get_now()) + " "
Timestamper.__init__(self, infile, iterator())
def __str__(self):
return "TimestamperNow(...)"
class TimestamperNull(Timestamper):
"""Timestamper that adds nothing to each line"""
def __init__(self, file):
def iterator():
while True:
yield ""
Timestamper.__init__(self, file, iterator())
def __str__(self):
return "TimestamperNull(...)"

29
nilmdb/utils/unicode.py Normal file
View File

@@ -0,0 +1,29 @@
import sys
if sys.version_info[0] >= 3: # pragma: no cover (future Python3 compat)
text_type = str
else:
text_type = unicode
def encode(u):
"""Try to encode something from Unicode to a string using the
default encoding. If it fails, try encoding as UTF-8."""
if not isinstance(u, text_type):
return u
try:
return u.encode()
except UnicodeEncodeError:
return u.encode("utf-8")
def decode(s):
"""Try to decode someting from string to Unicode using the
default encoding. If it fails, try decoding as UTF-8."""
if isinstance(s, text_type):
return s
try:
return s.decode()
except UnicodeDecodeError:
try:
return s.decode("utf-8")
except UnicodeDecodeError:
return s # best we can do

View File

@@ -1,6 +0,0 @@
#!/usr/bin/python
import nilmdb
import sys
nilmdb.cmdline.Cmdline(sys.argv[1:]).run()

View File

@@ -1,32 +0,0 @@
#!/usr/bin/python
import nilmdb
import argparse
parser = argparse.ArgumentParser(description='Run the NILM server')
parser.add_argument('-p', '--port', help='Port number', type=int, default=12380)
parser.add_argument('-y', '--yappi', help='Run with yappi profiler',
action='store_true')
args = parser.parse_args()
# Start web app on a custom port
db = nilmdb.NilmDB("db")
server = nilmdb.Server(db, host = "127.0.0.1",
port = args.port,
embedded = False)
if args.yappi:
print "Running in yappi"
try:
import yappi
yappi.start()
server.start(blocking = True)
finally:
yappi.stop()
print "Try: yappi.print_stats(sort_type=yappi.SORTTYPE_TTOT,limit=50)"
from IPython import embed
embed()
else:
server.start(blocking = True)
db.close()

View File

@@ -1,23 +1,41 @@
[aliases]
test = nosetests
[nosetests]
# note: the value doesn't matter, that's why they're empty here
nocapture=
nologcapture= # comment to see cherrypy logs on failure
with-coverage=
cover-inclusive=
# Note: values must be set to 1, and have no comments on the same line,
# for "python setup.py nosetests" to work correctly.
nocapture=1
# Comment this out to see CherryPy logs on failure:
nologcapture=1
with-coverage=1
cover-inclusive=1
cover-package=nilmdb
cover-erase=
##cover-html= # this works, puts html output in cover/ dir
##cover-branches= # need nose 1.1.3 for this
stop=
cover-erase=1
# this works, puts html output in cover/ dir:
# cover-html=1
# need nose 1.1.3 for this:
# cover-branches=1
#debug=nose
#debug-log=nose.log
stop=1
verbosity=2
tests=tests
#tests=tests/test_threadsafety.py
#tests=tests/test_bulkdata.py
#tests=tests/test_mustclose.py
#tests=tests/test_lrucache.py
#tests=tests/test_cmdline.py
#tests=tests/test_layout.py
tests=tests/test_interval.py
#tests=tests/test_rbtree.py
#tests=tests/test_interval.py
#tests=tests/test_rbtree.py,tests/test_interval.py
#tests=tests/test_interval.py
#tests=tests/test_client.py
#tests=tests/test_timestamper.py
#tests=tests/test_serializer.py
#tests=tests/test_iteratorizer.py
#tests=tests/test_client.py:TestClient.test_client_nilmdb
#with-profile=
#tests=tests/test_nilmdb.py
#with-profile=1
#profile-sort=time
##profile-restrict=10 # doesn't work right, treated as string or something

141
setup.py Executable file
View File

@@ -0,0 +1,141 @@
#!/usr/bin/python
# To release a new version, tag it:
# git tag -a nilmdb-1.1 -m "Version 1.1"
# git push --tags
# Then just package it up:
# python setup.py sdist
# This is supposed to be using Distribute:
#
# distutils provides a "setup" method.
# setuptools is a set of monkeypatches on top of that.
# distribute is a particular version/implementation of setuptools.
#
# So we don't really know if this is using the old setuptools or the
# Distribute-provided version of setuptools.
import traceback
import sys
import os
try:
from setuptools import setup, find_packages
from distutils.extension import Extension
import distutils.version
except ImportError:
traceback.print_exc()
print "Please install the prerequisites listed in README.txt"
sys.exit(1)
# Versioneer manages version numbers from git tags.
# https://github.com/warner/python-versioneer
import versioneer
versioneer.versionfile_source = 'nilmdb/_version.py'
versioneer.versionfile_build = 'nilmdb/_version.py'
versioneer.tag_prefix = 'nilmdb-'
versioneer.parentdir_prefix = 'nilmdb-'
# Hack to workaround logging/multiprocessing issue:
# https://groups.google.com/d/msg/nose-users/fnJ-kAUbYHQ/_UsLN786ygcJ
try: import multiprocessing
except Exception: pass
# Use Cython if it's new enough, otherwise use preexisting C files.
cython_modules = [ 'nilmdb.server.interval',
'nilmdb.server.rbtree' ]
try:
import Cython
from Cython.Build import cythonize
if (distutils.version.LooseVersion(Cython.__version__) <
distutils.version.LooseVersion("0.16")):
print "Cython version", Cython.__version__, "is too old; not using it."
raise ImportError()
use_cython = True
except ImportError:
use_cython = False
ext_modules = [ Extension('nilmdb.server.rocket', ['nilmdb/server/rocket.c' ]) ]
for modulename in cython_modules:
filename = modulename.replace('.','/')
if use_cython:
ext_modules.extend(cythonize(filename + ".pyx"))
else:
cfile = filename + ".c"
if not os.path.exists(cfile):
raise Exception("Missing source file " + cfile + ". "
"Try installing cython >= 0.16.")
ext_modules.append(Extension(modulename, [ cfile ]))
# We need a MANIFEST.in. Generate it here rather than polluting the
# repository with yet another setup-related file.
with open("MANIFEST.in", "w") as m:
m.write("""
# Root
include README.txt
include setup.cfg
include setup.py
include versioneer.py
include Makefile
include .coveragerc
include .pylintrc
# Cython files -- include source.
recursive-include nilmdb/server *.pyx *.pyxdep *.pxd
# Tests
recursive-include tests *.py
recursive-include tests/data *
include tests/test.order
# Docs
recursive-include docs Makefile *.md
# Extras
recursive-include extras *
""")
# Run setup
setup(name='nilmdb',
version = versioneer.get_version(),
cmdclass = versioneer.get_cmdclass(),
url = 'https://git.jim.sh/jim/lees/nilmdb.git',
author = 'Jim Paris',
description = "NILM Database",
long_description = "NILM Database",
license = "Proprietary",
author_email = 'jim@jtan.com',
tests_require = [ 'nose',
'coverage',
'numpy',
],
setup_requires = [ 'distribute',
],
install_requires = [ 'decorator',
'cherrypy >= 3.2',
'simplejson',
'python-dateutil',
'pytz',
'psutil >= 0.3.0',
'requests >= 1.1.0, < 2.0.0',
'progressbar >= 2.2',
],
packages = [ 'nilmdb',
'nilmdb.utils',
'nilmdb.utils.datetime_tz',
'nilmdb.server',
'nilmdb.client',
'nilmdb.cmdline',
'nilmdb.scripts',
'nilmdb.fsck',
],
entry_points = {
'console_scripts': [
'nilmtool = nilmdb.scripts.nilmtool:main',
'nilmdb-server = nilmdb.scripts.nilmdb_server:main',
'nilmdb-fsck = nilmdb.scripts.nilmdb_fsck:main',
],
},
ext_modules = ext_modules,
zip_safe = False,
)

View File

@@ -1,419 +0,0 @@
#-----------------------------------------------
#aplotter.py - ascii art function plotter
#Copyright (c) 2006, Imri Goldberg
#All rights reserved.
#
#Redistribution and use in source and binary forms,
#with or without modification, are permitted provided
#that the following conditions are met:
#
# * Redistributions of source code must retain the
# above copyright notice, this list of conditions
# and the following disclaimer.
# * Redistributions in binary form must reproduce the
# above copyright notice, this list of conditions
# and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# * Neither the name of the <ORGANIZATION> nor the names of
# its contributors may be used to endorse or promote products
# derived from this software without specific prior written permission.
#
#THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
#AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
#IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
#ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
#LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
#DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
#SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
#CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
#OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
#OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#-----------------------------------------------
import math
EPSILON = 0.000001
def transposed(mat):
result = []
for i in xrange(len(mat[0])):
result.append([x[i] for x in mat])
return result
def y_reversed(mat):
result = []
for i in range(len(mat)):
result.append(list(reversed(mat[i])))
return result
def sign(x):
if 0<x:
return 1
if 0 == x:
return 0
return -1
class Plotter(object):
class PlotData(object):
def __init__(self, x_size, y_size, min_x, max_x, min_y, max_y, x_mod, y_mod):
self.x_size = x_size
self.y_size = y_size
self.min_x = min_x
self.max_x = max_x
self.min_y = min_y
self.max_y = max_y
self.x_mod = x_mod
self.y_mod = y_mod
self.x_step = float(max_x - min_x)/float(self.x_size)
self.y_step = float(max_y - min_y)/float(self.y_size)
self.inv_x_step = 1/self.x_step
self.inv_y_step = 1/self.y_step
self.ratio = self.y_step / self.x_step
def __repr__(self):
s = "size: %s, bl: %s, tr: %s, step: %s" % ((self.x_size, self.y_size), (self.min_x, self.min_y), (self.max_x, self.max_y),
(self.x_step, self.y_step))
return s
def __init__(self, **kwargs):
self.x_size = kwargs.get("x_size", 80)
self.y_size = kwargs.get("y_size", 20)
self.will_draw_axes = kwargs.get("draw_axes", True)
self.new_line = kwargs.get("newline", "\n")
self.dot = kwargs.get("dot", "*")
self.plot_slope = kwargs.get("plot_slope", True)
self.x_margin = kwargs.get("x_margin", 0.05)
self.y_margin = kwargs.get("y_margin", 0.1)
self.will_plot_labels = kwargs.get("plot_labels", True)
@staticmethod
def get_symbol_by_slope(slope, default_symbol):
draw_symbol = default_symbol
if slope > math.tan(3*math.pi/8):
draw_symbol = "|"
elif slope > math.tan(math.pi/8) and slope < math.tan(3*math.pi/8):
draw_symbol = "/"
elif abs(slope) < math.tan(math.pi/8):
draw_symbol = "-"
elif slope < math.tan(-math.pi/8) and slope > math.tan(-3*math.pi/8):
draw_symbol = "\\"
elif slope < math.tan(-3*math.pi/8):
draw_symbol = "|"
return draw_symbol
def plot_labels(self, output_buffer, plot_data):
if plot_data.y_size < 2:
return
margin_factor = 1
do_plot_x_label = True
do_plot_y_label = True
x_str = "%+g"
if plot_data.x_size < 16:
do_plot_x_label = False
elif plot_data.x_size < 23:
x_str = "%+.2g"
y_str = "%+g"
if plot_data.x_size < 8:
do_plot_y_label = False
elif plot_data.x_size < 11:
y_str = "%+.2g"
act_min_x = (plot_data.min_x + plot_data.x_mod*margin_factor)
act_max_x = (plot_data.max_x - plot_data.x_mod*margin_factor)
act_min_y = (plot_data.min_y + plot_data.y_mod*margin_factor)
act_max_y = (plot_data.max_y - plot_data.y_mod*margin_factor)
if abs(act_min_x) < 1:
min_x_str = "%+.2g" % act_min_x
else:
min_x_str = x_str % act_min_x
if abs(act_max_x) < 1:
max_x_str = "%+.2g" % act_max_x
else:
max_x_str = x_str % act_max_x
if abs(act_min_y) < 1:
min_y_str = "%+.2g" % act_min_y
else:
min_y_str = y_str % act_min_y
if abs(act_max_y) < 1:
max_y_str = "%+.2g" % act_max_y
else:
max_y_str = y_str % act_max_y
min_x_coord = self.get_coord(act_min_x,plot_data.min_x,plot_data.x_step)
max_x_coord = self.get_coord(act_max_x,plot_data.min_x,plot_data.x_step)
min_y_coord = self.get_coord(act_min_y,plot_data.min_y,plot_data.y_step)
max_y_coord = self.get_coord(act_max_y,plot_data.min_y,plot_data.y_step)
#print plot_data
y_zero_coord = self.get_coord(0, plot_data.min_y, plot_data.y_step)
#if plot_data.min_x < 0 and plot_data.max_x > 0:
x_zero_coord = self.get_coord(0, plot_data.min_x, plot_data.x_step)
#else:
#pass
output_buffer[x_zero_coord][min_y_coord] = "+"
output_buffer[x_zero_coord][max_y_coord] = "+"
output_buffer[min_x_coord][y_zero_coord] = "+"
output_buffer[max_x_coord][y_zero_coord] = "+"
if do_plot_x_label:
for i,c in enumerate(min_x_str):
output_buffer[min_x_coord+i][y_zero_coord-1] = c
for i,c in enumerate(max_x_str):
output_buffer[max_x_coord+i-len(max_x_str)][y_zero_coord-1] = c
if do_plot_y_label:
for i,c in enumerate(max_y_str):
output_buffer[x_zero_coord+i][max_y_coord] = c
for i,c in enumerate(min_y_str):
output_buffer[x_zero_coord+i][min_y_coord] = c
def plot_data(self, xy_seq, output_buffer, plot_data):
if self.plot_slope:
xy_seq = list(xy_seq)
#sort according to the x coord
xy_seq.sort(key = lambda c: c[0])
prev_p = xy_seq[0]
e_xy_seq = enumerate(xy_seq)
e_xy_seq.next()
for i,(x,y) in e_xy_seq:
draw_symbol = self.dot
line_drawn = self.plot_line(prev_p, (x,y), output_buffer, plot_data)
prev_p = (x,y)
if not line_drawn:
if i > 0 and i < len(xy_seq)-1:
px,py = xy_seq[i-1]
nx,ny = xy_seq[i+1]
if abs(nx-px) > EPSILON:
slope = (1.0/plot_data.ratio)*(ny-py)/(nx-px)
draw_symbol = self.get_symbol_by_slope(slope, draw_symbol)
if x < plot_data.min_x or x >= plot_data.max_x or y < plot_data.min_y or y >= plot_data.max_y:
continue
x_coord = self.get_coord(x, plot_data.min_x, plot_data.x_step)
y_coord = self.get_coord(y, plot_data.min_y, plot_data.y_step)
if x_coord >= 0 and x_coord < len(output_buffer) and y_coord >= 0 and y_coord < len(output_buffer[0]):
if self.draw_axes:
if y_coord == self.get_coord(0, plot_data.min_y, plot_data.y_step) and draw_symbol == "-":
draw_symbol = "="
output_buffer[x_coord][y_coord] = draw_symbol
else:
for x,y in xy_seq:
if x < plot_data.min_x or x >= plot_data.max_x or y < plot_data.min_y or y >= plot_data.max_y:
continue
x_coord = self.get_coord(x, plot_data.min_x, plot_data.x_step)
y_coord = self.get_coord(y, plot_data.min_y, plot_data.y_step)
if x_coord >= 0 and x_coord < len(output_buffer) and y_coord > 0 and y_coord < len(output_buffer[0]):
output_buffer[x_coord][y_coord] = self.dot
def plot_line(self, start, end, output_buffer, plot_data):
start_coord = self.get_coord(start[0], plot_data.min_x, plot_data.x_step), self.get_coord(start[1], plot_data.min_y, plot_data.y_step)
end_coord = self.get_coord(end[0], plot_data.min_x, plot_data.x_step), self.get_coord(end[1], plot_data.min_y, plot_data.y_step)
x0,y0 = start_coord
x1,y1 = end_coord
if (x0,y0) == (x1,y1):
return True
clipped_line = clip_line(start, end, (plot_data.min_x, plot_data.min_y), (plot_data.max_x, plot_data.max_y))
if clipped_line != None:
start,end = clipped_line
else:
return False
start_coord = self.get_coord(start[0], plot_data.min_x, plot_data.x_step), self.get_coord(start[1], plot_data.min_y, plot_data.y_step)
end_coord = self.get_coord(end[0], plot_data.min_x, plot_data.x_step), self.get_coord(end[1], plot_data.min_y, plot_data.y_step)
x0,y0 = start_coord
x1,y1 = end_coord
if (x0,y0) == (x1,y1):
return True
x_zero_coord = self.get_coord(0, plot_data.min_x, plot_data.x_step)
y_zero_coord = self.get_coord(0, plot_data.min_y, plot_data.y_step)
if start[0]-end[0] == 0:
draw_symbol = "|"
else:
slope = (1.0/plot_data.ratio)*(end[1]-start[1])/(end[0]-start[0])
draw_symbol = self.get_symbol_by_slope(slope, self.dot)
try:
delta = x1-x0, y1-y0
if abs(delta[0])>abs(delta[1]):
s = sign(delta[0])
slope = float(delta[1])/delta[0]
for i in range(0,abs(int(delta[0]))):
cur_draw_symbol = draw_symbol
x = i*s
cur_y = int(y0+slope*x)
if self.draw_axes and cur_y == y_zero_coord and draw_symbol == "-":
cur_draw_symbol = "="
output_buffer[x0+x][cur_y] = cur_draw_symbol
else:
s = sign(delta[1])
slope = float(delta[0])/delta[1]
for i in range(0,abs(int(delta[1]))):
y = i*s
cur_draw_symbol = draw_symbol
cur_y = y0+y
if self.draw_axes and cur_y == y_zero_coord and draw_symbol == "-":
cur_draw_symbol = "="
output_buffer[int(x0+slope*y)][cur_y] = cur_draw_symbol
except:
print start, end
print start_coord, end_coord
print plot_data
raise
return False
def plot_single(self, seq, min_x = None, max_x = None, min_y = None, max_y = None):
return self.plot_double(range(len(seq)),seq, min_x, max_x, min_y, max_y)
def plot_double(self, x_seq, y_seq, min_x = None, max_x = None, min_y = None, max_y = None):
if min_x == None:
min_x = min(x_seq)
if max_x == None:
max_x = max(x_seq)
if min_y == None:
min_y = min(y_seq)
if max_y == None:
max_y = max(y_seq)
if max_y == min_y:
max_y += 1
x_mod = (max_x-min_x)*self.x_margin
y_mod = (max_y-min_y)*self.y_margin
min_x-=x_mod
max_x+=x_mod
min_y-=y_mod
max_y+=y_mod
plot_data = self.PlotData(self.x_size, self.y_size, min_x, max_x, min_y, max_y, x_mod, y_mod)
output_buffer = [[" "]*self.y_size for i in range(self.x_size)]
if self.will_draw_axes:
self.draw_axes(output_buffer, plot_data)
self.plot_data(zip(x_seq, y_seq), output_buffer, plot_data)
if self.will_plot_labels:
self.plot_labels(output_buffer, plot_data)
trans_result = transposed(y_reversed(output_buffer))
result = self.new_line.join(["".join(row) for row in trans_result])
return result
def draw_axes(self, output_buffer, plot_data):
draw_x = False
draw_y = False
if plot_data.min_x <= 0 and plot_data.max_x > 0:
draw_y = True
zero_x = self.get_coord(0, plot_data.min_x, plot_data.x_step)
for y in xrange(plot_data.y_size):
output_buffer[zero_x][y] = "|"
if plot_data.min_y <= 0 and plot_data.max_y > 0:
draw_x = True
zero_y = self.get_coord(0, plot_data.min_y, plot_data.y_step)
for x in xrange(plot_data.x_size):
output_buffer[x][zero_y] = "-"
if draw_x and draw_y:
output_buffer[zero_x][zero_y] = "+"
@staticmethod
def get_coord(val, min, step):
result = int((val - min)/step)
return result
def clip_line(line_pt_1, line_pt_2, rect_bottom_left, rect_top_right):
ts = [0.0,1.0]
if line_pt_1[0] == line_pt_2[0]:
return ((line_pt_1[0], max(min(line_pt_1[1], line_pt_2[1]), rect_bottom_left[1])),
(line_pt_1[0], min(max(line_pt_1[1], line_pt_2[1]), rect_top_right[1])))
if line_pt_1[1] == line_pt_2[1]:
return ((max(min(line_pt_1[0], line_pt_2[0]), rect_bottom_left[0]), line_pt_1[1]),
(min(max(line_pt_1[0], line_pt_2[0]), rect_top_right[0]), line_pt_1[1]))
if ((rect_bottom_left[0] <= line_pt_1[0] and line_pt_1[0] < rect_top_right[0]) and
(rect_bottom_left[1] <= line_pt_1[1] and line_pt_1[1] < rect_top_right[1]) and
(rect_bottom_left[0] <= line_pt_2[0] and line_pt_2[0] < rect_top_right[0]) and
(rect_bottom_left[1] <= line_pt_2[1] and line_pt_2[1] < rect_top_right[1])):
return line_pt_1, line_pt_2
ts.append( float(rect_bottom_left[0]-line_pt_1[0])/(line_pt_2[0]-line_pt_1[0]) )
ts.append( float(rect_top_right[0]-line_pt_1[0])/(line_pt_2[0]-line_pt_1[0]) )
ts.append( float(rect_bottom_left[1]-line_pt_1[1])/(line_pt_2[1]-line_pt_1[1]) )
ts.append( float(rect_top_right[1]-line_pt_1[1])/(line_pt_2[1]-line_pt_1[1]) )
ts.sort()
if ts[2] < 0 or ts[2] >= 1 or ts[3] < 0 or ts[2]>= 1:
return None
result = [(pt_1 + t*(pt_2-pt_1)) for t in (ts[2],ts[3]) for (pt_1, pt_2) in zip(line_pt_1, line_pt_2)]
return (result[0],result[1]), (result[2], result[3])
def plot(*args,**flags):
limit_flags_names = set(["min_x","min_y","max_x","max_y"])
limit_flags = dict([(n,flags[n]) for n in limit_flags_names & set(flags)])
settting_flags = dict([(n,flags[n]) for n in set(flags) - limit_flags_names])
if len(args) == 1:
p = Plotter(**settting_flags)
print p.plot_single(args[0],**limit_flags)
elif len(args) == 2:
p = Plotter(**settting_flags)
print p.plot_double(args[0],args[1],**limit_flags)
else:
raise NotImplementedError("can't draw multiple graphs yet")
__all__ = ["Plotter","plot"]

View File

@@ -1,124 +1,124 @@
# path: /newton/prep
# layout: PrepData
# layout: float32_8
# start: Fri, 23 Mar 2012 10:00:30.000000 +0000
# end: Fri, 23 Mar 2012 10:00:31.000000 +0000
1332496830.000000 251774.000000 224241.000000 5688.100098 1915.530029 9329.219727 4183.709961 1212.349976 2641.790039
1332496830.008333 259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
1332496830.016667 263073.000000 223304.000000 4961.640137 2197.120117 7687.310059 4861.859863 2732.780029 3008.540039
1332496830.025000 257614.000000 223323.000000 5003.660156 3525.139893 7165.310059 4685.620117 1715.380005 3440.479980
1332496830.033333 255780.000000 221915.000000 6357.310059 2145.290039 8426.969727 3775.350098 1475.390015 3797.239990
1332496830.041667 260166.000000 223008.000000 6702.589844 1484.959961 9288.099609 3330.830078 1228.500000 3214.320068
1332496830.050000 261231.000000 226426.000000 4980.060059 2982.379883 8499.629883 4267.669922 994.088989 2292.889893
1332496830.058333 255117.000000 226642.000000 4584.410156 4656.439941 7860.149902 5317.310059 1473.599976 2111.689941
1332496830.066667 253300.000000 223554.000000 6455.089844 3036.649902 8869.750000 4986.310059 2607.360107 2839.590088
1332496830.075000 261061.000000 221263.000000 6951.979980 1500.239990 9386.099609 3791.679932 2677.010010 3980.629883
1332496830.083333 266503.000000 223198.000000 5189.609863 2594.560059 8571.530273 3175.000000 919.840027 3792.010010
1332496830.091667 260692.000000 225184.000000 3782.479980 4642.879883 7662.959961 3917.790039 -251.097000 2907.060059
1332496830.100000 253963.000000 225081.000000 5123.529785 3839.550049 8669.030273 4877.819824 943.723999 2527.449951
1332496830.108333 256555.000000 224169.000000 5930.600098 2298.540039 8906.709961 5331.680176 2549.909912 3053.560059
1332496830.116667 260889.000000 225010.000000 4681.129883 2971.870117 7900.040039 4874.080078 2322.429932 3649.120117
1332496830.125000 257944.000000 224923.000000 3291.139893 4357.089844 7131.589844 4385.560059 1077.050049 3664.040039
1332496830.133333 255009.000000 223018.000000 4584.819824 2864.000000 8469.490234 3625.580078 985.557007 3504.229980
1332496830.141667 260114.000000 221947.000000 5676.189941 1210.339966 9393.780273 3390.239990 1654.020020 3018.699951
1332496830.150000 264277.000000 224438.000000 4446.620117 2176.719971 8142.089844 4584.879883 2327.830078 2615.800049
1332496830.158333 259221.000000 226471.000000 2734.439941 4182.759766 6389.549805 5540.520020 1958.880005 2720.120117
1332496830.166667 252650.000000 224831.000000 4163.640137 2989.989990 7179.200195 5213.060059 1929.550049 3457.659912
1332496830.175000 257083.000000 222048.000000 5759.040039 702.440979 8566.549805 3552.020020 1832.939941 3956.189941
1332496830.183333 263130.000000 222967.000000 5141.140137 1166.119995 8666.959961 2720.370117 971.374023 3479.729980
1332496830.191667 260236.000000 225265.000000 3425.139893 3339.080078 7853.609863 3674.949951 525.908020 2443.310059
1332496830.200000 253503.000000 224527.000000 4398.129883 2927.429932 8110.279785 4842.470215 1513.869995 2467.100098
1332496830.208333 256126.000000 222693.000000 6043.529785 656.223999 8797.559570 4832.410156 2832.370117 3426.139893
1332496830.216667 261677.000000 223608.000000 5830.459961 1033.910034 8123.939941 3980.689941 1927.959961 4092.719971
1332496830.225000 259457.000000 225536.000000 4015.570068 2995.989990 7135.439941 3713.550049 307.220001 3849.429932
1332496830.233333 253352.000000 224216.000000 4650.560059 3196.620117 8131.279785 3586.159912 70.832298 3074.179932
1332496830.241667 256124.000000 221513.000000 6100.479980 821.979980 9757.540039 3474.510010 1647.520020 2559.860107
1332496830.250000 263024.000000 221559.000000 5789.959961 699.416992 9129.740234 4153.080078 2829.250000 2677.270020
1332496830.258333 261720.000000 224015.000000 4358.500000 2645.360107 7414.109863 4810.669922 2225.989990 3185.989990
1332496830.266667 254756.000000 224240.000000 4857.379883 3229.679932 7539.310059 4769.140137 1507.130005 3668.260010
1332496830.275000 256889.000000 222658.000000 6473.419922 1214.109985 9010.759766 3848.729980 1303.839966 3778.500000
1332496830.283333 264208.000000 223316.000000 5700.450195 1116.560059 9087.610352 3846.679932 1293.589966 2891.560059
1332496830.291667 263310.000000 225719.000000 3936.120117 3252.360107 7552.850098 4897.859863 1156.630005 2037.160034
1332496830.300000 255079.000000 225086.000000 4536.450195 3960.110107 7454.589844 5479.069824 1596.359985 2190.800049
1332496830.308333 254487.000000 222508.000000 6635.859863 1758.849976 8732.969727 4466.970215 2650.360107 3139.310059
1332496830.316667 261241.000000 222432.000000 6702.270020 1085.130005 8989.230469 3112.989990 1933.560059 3828.409912
1332496830.325000 262119.000000 225587.000000 4714.950195 2892.360107 8107.819824 2961.310059 239.977997 3273.719971
1332496830.333333 254999.000000 226514.000000 4532.089844 4126.899902 8200.129883 3872.590088 56.089001 2370.580078
1332496830.341667 254289.000000 224033.000000 6538.810059 2251.439941 9419.429688 4564.450195 2077.810059 2508.169922
1332496830.350000 261890.000000 221960.000000 6846.089844 1475.270020 9125.589844 4598.290039 3299.219971 3475.419922
1332496830.358333 264502.000000 223085.000000 5066.379883 3270.560059 7933.169922 4173.709961 1908.910034 3867.459961
1332496830.366667 257889.000000 223656.000000 4201.660156 4473.640137 7688.339844 4161.580078 687.578979 3653.689941
1332496830.375000 254270.000000 223151.000000 5715.140137 2752.139893 9273.320312 3772.949951 896.403992 3256.060059
1332496830.383333 258257.000000 224217.000000 6114.310059 1856.859985 9604.320312 4200.490234 1764.380005 2939.219971
1332496830.391667 260020.000000 226868.000000 4237.529785 3605.879883 8066.220215 5430.250000 2138.580078 2696.709961
1332496830.400000 255083.000000 225924.000000 3350.310059 4853.069824 7045.819824 5925.200195 1893.609985 2897.340088
1332496830.408333 254453.000000 222127.000000 5271.330078 2491.500000 8436.679688 5032.080078 2436.050049 3724.590088
1332496830.416667 262588.000000 219950.000000 5994.620117 789.273987 9029.650391 3515.739990 1953.569946 4014.520020
1332496830.425000 265610.000000 223333.000000 4391.410156 2400.959961 8146.459961 3536.959961 530.231995 3133.919922
1332496830.433333 257470.000000 226977.000000 2975.320068 4633.529785 7278.560059 4640.100098 -50.150200 2024.959961
1332496830.441667 250687.000000 226331.000000 4517.859863 3183.800049 8072.600098 5281.660156 1605.140015 2335.139893
1332496830.450000 255563.000000 224495.000000 5551.000000 1101.300049 8461.490234 4725.700195 2726.669922 3480.540039
1332496830.458333 261335.000000 224645.000000 4764.680176 1557.020020 7833.350098 3524.810059 1577.410034 4038.620117
1332496830.466667 260269.000000 224008.000000 3558.030029 2987.610107 7362.439941 3279.229980 562.442017 3786.550049
1332496830.475000 257435.000000 221777.000000 4972.600098 2166.879883 8481.440430 3328.719971 1037.130005 3271.370117
1332496830.483333 261046.000000 221550.000000 5816.180176 590.216980 9120.929688 3895.399902 2382.669922 2824.169922
1332496830.491667 262766.000000 224473.000000 4835.049805 1785.770020 7880.759766 4745.620117 2443.659912 3229.550049
1332496830.500000 256509.000000 226413.000000 3758.870117 3461.199951 6743.770020 4928.959961 1536.619995 3546.689941
1332496830.508333 250793.000000 224372.000000 5218.490234 2865.260010 7803.959961 4351.089844 1333.819946 3680.489990
1332496830.516667 256319.000000 222066.000000 6403.970215 732.344971 9627.759766 3089.300049 1516.780029 3653.689941
1332496830.525000 263343.000000 223235.000000 5200.430176 1388.579956 9372.849609 3371.229980 1450.390015 2678.909912
1332496830.533333 260903.000000 225110.000000 3722.580078 3246.659912 7876.540039 4716.810059 1498.439941 2116.520020
1332496830.541667 254416.000000 223769.000000 4841.649902 2956.399902 8115.919922 5392.359863 2142.810059 2652.320068
1332496830.550000 256698.000000 222172.000000 6471.229980 970.395996 8834.980469 4816.839844 2376.629883 3605.860107
1332496830.558333 261841.000000 223537.000000 5500.740234 1189.660034 8365.730469 4016.469971 1042.270020 3821.199951
1332496830.566667 259503.000000 225840.000000 3827.929932 3088.840088 7676.140137 3978.310059 -357.006989 3016.419922
1332496830.575000 253457.000000 224636.000000 4914.609863 3097.449951 8224.900391 4321.439941 171.373993 2412.360107
1332496830.583333 256029.000000 222221.000000 6841.799805 1028.500000 9252.299805 4387.569824 2418.139893 2510.100098
1332496830.591667 262840.000000 222550.000000 6210.250000 1410.729980 8538.900391 4152.580078 3009.300049 3219.760010
1332496830.600000 261633.000000 225065.000000 4284.529785 3357.209961 7282.169922 3823.590088 1402.839966 3644.669922
1332496830.608333 254591.000000 225109.000000 4693.160156 3647.739990 7745.160156 3686.379883 490.161011 3448.860107
1332496830.616667 254780.000000 223599.000000 6527.379883 1569.869995 9438.429688 3456.580078 1162.520020 3252.010010
1332496830.625000 260639.000000 224107.000000 6531.049805 1633.050049 9283.719727 4174.020020 2089.550049 2775.750000
1332496830.633333 261108.000000 225472.000000 4968.259766 3527.850098 7692.870117 5137.100098 2207.389893 2436.659912
1332496830.641667 255775.000000 223708.000000 4963.450195 4017.370117 7701.419922 5269.649902 2284.399902 2842.080078
1332496830.650000 257398.000000 220947.000000 6767.500000 1645.709961 9107.070312 4000.179932 2548.860107 3624.770020
1332496830.658333 264924.000000 221559.000000 6471.459961 1110.329956 9459.650391 3108.169922 1696.969971 3893.439941
1332496830.666667 265339.000000 225733.000000 4348.799805 3459.510010 8475.299805 4031.239990 573.346985 2910.270020
1332496830.675000 256814.000000 226995.000000 3479.540039 4949.790039 7499.910156 5624.709961 751.656006 2347.709961
1332496830.683333 253316.000000 225161.000000 5147.060059 3218.429932 8460.160156 5869.299805 2336.320068 2987.959961
1332496830.691667 259360.000000 223101.000000 5549.120117 1869.949951 8740.759766 4668.939941 2457.909912 3758.820068
1332496830.700000 262012.000000 224016.000000 4173.609863 3004.129883 8157.040039 3704.729980 987.963989 3652.750000
1332496830.708333 257176.000000 224420.000000 3517.300049 4118.750000 7822.240234 3718.229980 37.264900 2953.679932
1332496830.716667 255146.000000 223322.000000 4923.979980 2330.679932 9095.910156 3792.399902 1013.070007 2711.239990
1332496830.725000 260524.000000 223651.000000 5413.629883 1146.209961 8817.169922 4419.649902 2446.649902 2832.050049
1332496830.733333 262098.000000 225752.000000 4262.979980 2270.969971 7135.479980 5067.120117 2294.679932 3376.620117
1332496830.741667 256889.000000 225379.000000 3606.459961 3568.189941 6552.649902 4970.270020 1516.380005 3662.570068
1332496830.750000 253948.000000 222631.000000 5511.700195 2066.300049 7952.660156 4019.909912 1513.140015 3752.629883
1332496830.758333 259799.000000 222067.000000 5873.500000 608.583984 9253.780273 2870.739990 1348.239990 3344.199951
1332496830.766667 262547.000000 224901.000000 4346.080078 1928.099976 8590.969727 3455.459961 904.390991 2379.270020
1332496830.775000 256137.000000 226761.000000 3423.560059 3379.080078 7471.149902 4894.169922 1153.540039 2031.410034
1332496830.783333 250326.000000 225013.000000 5519.979980 2423.969971 7991.759766 5117.950195 2098.790039 3099.239990
1332496830.791667 255454.000000 222992.000000 6547.950195 496.496002 8751.339844 3900.560059 2132.290039 4076.810059
1332496830.800000 261286.000000 223489.000000 5152.850098 1501.510010 8425.610352 2888.030029 776.114014 3786.360107
1332496830.808333 258969.000000 224069.000000 3832.610107 3001.979980 7979.259766 3182.310059 52.716000 2874.800049
1332496830.816667 254946.000000 222035.000000 5317.879883 2139.800049 9103.139648 3955.610107 1235.170044 2394.149902
1332496830.825000 258676.000000 221205.000000 6594.910156 505.343994 9423.360352 4562.470215 2913.739990 2892.350098
1332496830.833333 262125.000000 223566.000000 5116.750000 1773.599976 8082.200195 4776.370117 2386.389893 3659.729980
1332496830.841667 257835.000000 225918.000000 3714.300049 3477.080078 7205.370117 4554.609863 711.539001 3878.419922
1332496830.850000 253660.000000 224371.000000 5022.450195 2592.429932 8277.200195 4119.370117 486.507996 3666.739990
1332496830.858333 259503.000000 222061.000000 6589.950195 659.935974 9596.919922 3598.100098 1702.489990 3036.600098
1332496830.866667 265495.000000 222843.000000 5541.850098 1728.430054 8459.959961 4492.000000 2231.969971 2430.620117
1332496830.875000 260929.000000 224996.000000 4000.949951 3745.989990 6983.790039 5430.859863 1855.260010 2533.379883
1332496830.883333 252716.000000 224335.000000 5086.560059 3401.149902 7597.970215 5196.120117 1755.719971 3079.760010
1332496830.891667 254110.000000 223111.000000 6822.189941 1229.079956 9164.339844 3761.229980 1679.390015 3584.879883
1332496830.900000 259969.000000 224693.000000 6183.950195 1538.500000 9222.080078 3139.169922 949.901978 3180.800049
1332496830.908333 259078.000000 226913.000000 4388.890137 3694.820068 8195.019531 3933.000000 426.079987 2388.449951
1332496830.916667 254563.000000 224760.000000 5168.439941 4020.939941 8450.269531 4758.910156 1458.900024 2286.429932
1332496830.925000 258059.000000 221217.000000 6883.459961 1649.530029 9232.780273 4457.649902 3057.820068 3031.949951
1332496830.933333 264667.000000 221177.000000 6218.509766 1645.729980 8657.179688 3663.500000 2528.280029 3978.340088
1332496830.941667 262925.000000 224382.000000 4627.500000 3635.929932 7892.799805 3431.320068 604.508972 3901.370117
1332496830.950000 254708.000000 225448.000000 4408.250000 4461.040039 8197.169922 3953.750000 -44.534599 3154.870117
1332496830.958333 253702.000000 224635.000000 5825.770020 2577.050049 9590.049805 4569.250000 1460.270020 2785.169922
1332496830.966667 260206.000000 224140.000000 5387.979980 1951.160034 8789.509766 5131.660156 2706.379883 2972.479980
1332496830.975000 261240.000000 224737.000000 3860.810059 3418.310059 7414.529785 5284.520020 2271.379883 3183.149902
1332496830.983333 256140.000000 223252.000000 3850.010010 3957.139893 7262.649902 4964.640137 1499.510010 3453.129883
1332496830.991667 256116.000000 221349.000000 5594.479980 2054.399902 8835.129883 3662.010010 1485.510010 3613.010010
1332496830000000 2.517740e+05 2.242410e+05 5.688100e+03 1.915530e+03 9.329220e+03 4.183710e+03 1.212350e+03 2.641790e+03
1332496830008333 2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
1332496830016667 2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03
1332496830025000 2.576140e+05 2.233230e+05 5.003660e+03 3.525140e+03 7.165310e+03 4.685620e+03 1.715380e+03 3.440480e+03
1332496830033333 2.557800e+05 2.219150e+05 6.357310e+03 2.145290e+03 8.426970e+03 3.775350e+03 1.475390e+03 3.797240e+03
1332496830041667 2.601660e+05 2.230080e+05 6.702590e+03 1.484960e+03 9.288100e+03 3.330830e+03 1.228500e+03 3.214320e+03
1332496830050000 2.612310e+05 2.264260e+05 4.980060e+03 2.982380e+03 8.499630e+03 4.267670e+03 9.940890e+02 2.292890e+03
1332496830058333 2.551170e+05 2.266420e+05 4.584410e+03 4.656440e+03 7.860150e+03 5.317310e+03 1.473600e+03 2.111690e+03
1332496830066667 2.533000e+05 2.235540e+05 6.455090e+03 3.036650e+03 8.869750e+03 4.986310e+03 2.607360e+03 2.839590e+03
1332496830075000 2.610610e+05 2.212630e+05 6.951980e+03 1.500240e+03 9.386100e+03 3.791680e+03 2.677010e+03 3.980630e+03
1332496830083333 2.665030e+05 2.231980e+05 5.189610e+03 2.594560e+03 8.571530e+03 3.175000e+03 9.198400e+02 3.792010e+03
1332496830091667 2.606920e+05 2.251840e+05 3.782480e+03 4.642880e+03 7.662960e+03 3.917790e+03 -2.510970e+02 2.907060e+03
1332496830100000 2.539630e+05 2.250810e+05 5.123530e+03 3.839550e+03 8.669030e+03 4.877820e+03 9.437240e+02 2.527450e+03
1332496830108333 2.565550e+05 2.241690e+05 5.930600e+03 2.298540e+03 8.906710e+03 5.331680e+03 2.549910e+03 3.053560e+03
1332496830116667 2.608890e+05 2.250100e+05 4.681130e+03 2.971870e+03 7.900040e+03 4.874080e+03 2.322430e+03 3.649120e+03
1332496830125000 2.579440e+05 2.249230e+05 3.291140e+03 4.357090e+03 7.131590e+03 4.385560e+03 1.077050e+03 3.664040e+03
1332496830133333 2.550090e+05 2.230180e+05 4.584820e+03 2.864000e+03 8.469490e+03 3.625580e+03 9.855570e+02 3.504230e+03
1332496830141667 2.601140e+05 2.219470e+05 5.676190e+03 1.210340e+03 9.393780e+03 3.390240e+03 1.654020e+03 3.018700e+03
1332496830150000 2.642770e+05 2.244380e+05 4.446620e+03 2.176720e+03 8.142090e+03 4.584880e+03 2.327830e+03 2.615800e+03
1332496830158333 2.592210e+05 2.264710e+05 2.734440e+03 4.182760e+03 6.389550e+03 5.540520e+03 1.958880e+03 2.720120e+03
1332496830166667 2.526500e+05 2.248310e+05 4.163640e+03 2.989990e+03 7.179200e+03 5.213060e+03 1.929550e+03 3.457660e+03
1332496830175000 2.570830e+05 2.220480e+05 5.759040e+03 7.024410e+02 8.566550e+03 3.552020e+03 1.832940e+03 3.956190e+03
1332496830183333 2.631300e+05 2.229670e+05 5.141140e+03 1.166120e+03 8.666960e+03 2.720370e+03 9.713740e+02 3.479730e+03
1332496830191667 2.602360e+05 2.252650e+05 3.425140e+03 3.339080e+03 7.853610e+03 3.674950e+03 5.259080e+02 2.443310e+03
1332496830200000 2.535030e+05 2.245270e+05 4.398130e+03 2.927430e+03 8.110280e+03 4.842470e+03 1.513870e+03 2.467100e+03
1332496830208333 2.561260e+05 2.226930e+05 6.043530e+03 6.562240e+02 8.797560e+03 4.832410e+03 2.832370e+03 3.426140e+03
1332496830216667 2.616770e+05 2.236080e+05 5.830460e+03 1.033910e+03 8.123940e+03 3.980690e+03 1.927960e+03 4.092720e+03
1332496830225000 2.594570e+05 2.255360e+05 4.015570e+03 2.995990e+03 7.135440e+03 3.713550e+03 3.072200e+02 3.849430e+03
1332496830233333 2.533520e+05 2.242160e+05 4.650560e+03 3.196620e+03 8.131280e+03 3.586160e+03 7.083230e+01 3.074180e+03
1332496830241667 2.561240e+05 2.215130e+05 6.100480e+03 8.219800e+02 9.757540e+03 3.474510e+03 1.647520e+03 2.559860e+03
1332496830250000 2.630240e+05 2.215590e+05 5.789960e+03 6.994170e+02 9.129740e+03 4.153080e+03 2.829250e+03 2.677270e+03
1332496830258333 2.617200e+05 2.240150e+05 4.358500e+03 2.645360e+03 7.414110e+03 4.810670e+03 2.225990e+03 3.185990e+03
1332496830266667 2.547560e+05 2.242400e+05 4.857380e+03 3.229680e+03 7.539310e+03 4.769140e+03 1.507130e+03 3.668260e+03
1332496830275000 2.568890e+05 2.226580e+05 6.473420e+03 1.214110e+03 9.010760e+03 3.848730e+03 1.303840e+03 3.778500e+03
1332496830283333 2.642080e+05 2.233160e+05 5.700450e+03 1.116560e+03 9.087610e+03 3.846680e+03 1.293590e+03 2.891560e+03
1332496830291667 2.633100e+05 2.257190e+05 3.936120e+03 3.252360e+03 7.552850e+03 4.897860e+03 1.156630e+03 2.037160e+03
1332496830300000 2.550790e+05 2.250860e+05 4.536450e+03 3.960110e+03 7.454590e+03 5.479070e+03 1.596360e+03 2.190800e+03
1332496830308333 2.544870e+05 2.225080e+05 6.635860e+03 1.758850e+03 8.732970e+03 4.466970e+03 2.650360e+03 3.139310e+03
1332496830316667 2.612410e+05 2.224320e+05 6.702270e+03 1.085130e+03 8.989230e+03 3.112990e+03 1.933560e+03 3.828410e+03
1332496830325000 2.621190e+05 2.255870e+05 4.714950e+03 2.892360e+03 8.107820e+03 2.961310e+03 2.399780e+02 3.273720e+03
1332496830333333 2.549990e+05 2.265140e+05 4.532090e+03 4.126900e+03 8.200130e+03 3.872590e+03 5.608900e+01 2.370580e+03
1332496830341667 2.542890e+05 2.240330e+05 6.538810e+03 2.251440e+03 9.419430e+03 4.564450e+03 2.077810e+03 2.508170e+03
1332496830350000 2.618900e+05 2.219600e+05 6.846090e+03 1.475270e+03 9.125590e+03 4.598290e+03 3.299220e+03 3.475420e+03
1332496830358333 2.645020e+05 2.230850e+05 5.066380e+03 3.270560e+03 7.933170e+03 4.173710e+03 1.908910e+03 3.867460e+03
1332496830366667 2.578890e+05 2.236560e+05 4.201660e+03 4.473640e+03 7.688340e+03 4.161580e+03 6.875790e+02 3.653690e+03
1332496830375000 2.542700e+05 2.231510e+05 5.715140e+03 2.752140e+03 9.273320e+03 3.772950e+03 8.964040e+02 3.256060e+03
1332496830383333 2.582570e+05 2.242170e+05 6.114310e+03 1.856860e+03 9.604320e+03 4.200490e+03 1.764380e+03 2.939220e+03
1332496830391667 2.600200e+05 2.268680e+05 4.237530e+03 3.605880e+03 8.066220e+03 5.430250e+03 2.138580e+03 2.696710e+03
1332496830400000 2.550830e+05 2.259240e+05 3.350310e+03 4.853070e+03 7.045820e+03 5.925200e+03 1.893610e+03 2.897340e+03
1332496830408333 2.544530e+05 2.221270e+05 5.271330e+03 2.491500e+03 8.436680e+03 5.032080e+03 2.436050e+03 3.724590e+03
1332496830416667 2.625880e+05 2.199500e+05 5.994620e+03 7.892740e+02 9.029650e+03 3.515740e+03 1.953570e+03 4.014520e+03
1332496830425000 2.656100e+05 2.233330e+05 4.391410e+03 2.400960e+03 8.146460e+03 3.536960e+03 5.302320e+02 3.133920e+03
1332496830433333 2.574700e+05 2.269770e+05 2.975320e+03 4.633530e+03 7.278560e+03 4.640100e+03 -5.015020e+01 2.024960e+03
1332496830441667 2.506870e+05 2.263310e+05 4.517860e+03 3.183800e+03 8.072600e+03 5.281660e+03 1.605140e+03 2.335140e+03
1332496830450000 2.555630e+05 2.244950e+05 5.551000e+03 1.101300e+03 8.461490e+03 4.725700e+03 2.726670e+03 3.480540e+03
1332496830458333 2.613350e+05 2.246450e+05 4.764680e+03 1.557020e+03 7.833350e+03 3.524810e+03 1.577410e+03 4.038620e+03
1332496830466667 2.602690e+05 2.240080e+05 3.558030e+03 2.987610e+03 7.362440e+03 3.279230e+03 5.624420e+02 3.786550e+03
1332496830475000 2.574350e+05 2.217770e+05 4.972600e+03 2.166880e+03 8.481440e+03 3.328720e+03 1.037130e+03 3.271370e+03
1332496830483333 2.610460e+05 2.215500e+05 5.816180e+03 5.902170e+02 9.120930e+03 3.895400e+03 2.382670e+03 2.824170e+03
1332496830491667 2.627660e+05 2.244730e+05 4.835050e+03 1.785770e+03 7.880760e+03 4.745620e+03 2.443660e+03 3.229550e+03
1332496830500000 2.565090e+05 2.264130e+05 3.758870e+03 3.461200e+03 6.743770e+03 4.928960e+03 1.536620e+03 3.546690e+03
1332496830508333 2.507930e+05 2.243720e+05 5.218490e+03 2.865260e+03 7.803960e+03 4.351090e+03 1.333820e+03 3.680490e+03
1332496830516667 2.563190e+05 2.220660e+05 6.403970e+03 7.323450e+02 9.627760e+03 3.089300e+03 1.516780e+03 3.653690e+03
1332496830525000 2.633430e+05 2.232350e+05 5.200430e+03 1.388580e+03 9.372850e+03 3.371230e+03 1.450390e+03 2.678910e+03
1332496830533333 2.609030e+05 2.251100e+05 3.722580e+03 3.246660e+03 7.876540e+03 4.716810e+03 1.498440e+03 2.116520e+03
1332496830541667 2.544160e+05 2.237690e+05 4.841650e+03 2.956400e+03 8.115920e+03 5.392360e+03 2.142810e+03 2.652320e+03
1332496830550000 2.566980e+05 2.221720e+05 6.471230e+03 9.703960e+02 8.834980e+03 4.816840e+03 2.376630e+03 3.605860e+03
1332496830558333 2.618410e+05 2.235370e+05 5.500740e+03 1.189660e+03 8.365730e+03 4.016470e+03 1.042270e+03 3.821200e+03
1332496830566667 2.595030e+05 2.258400e+05 3.827930e+03 3.088840e+03 7.676140e+03 3.978310e+03 -3.570070e+02 3.016420e+03
1332496830575000 2.534570e+05 2.246360e+05 4.914610e+03 3.097450e+03 8.224900e+03 4.321440e+03 1.713740e+02 2.412360e+03
1332496830583333 2.560290e+05 2.222210e+05 6.841800e+03 1.028500e+03 9.252300e+03 4.387570e+03 2.418140e+03 2.510100e+03
1332496830591667 2.628400e+05 2.225500e+05 6.210250e+03 1.410730e+03 8.538900e+03 4.152580e+03 3.009300e+03 3.219760e+03
1332496830600000 2.616330e+05 2.250650e+05 4.284530e+03 3.357210e+03 7.282170e+03 3.823590e+03 1.402840e+03 3.644670e+03
1332496830608333 2.545910e+05 2.251090e+05 4.693160e+03 3.647740e+03 7.745160e+03 3.686380e+03 4.901610e+02 3.448860e+03
1332496830616667 2.547800e+05 2.235990e+05 6.527380e+03 1.569870e+03 9.438430e+03 3.456580e+03 1.162520e+03 3.252010e+03
1332496830625000 2.606390e+05 2.241070e+05 6.531050e+03 1.633050e+03 9.283720e+03 4.174020e+03 2.089550e+03 2.775750e+03
1332496830633333 2.611080e+05 2.254720e+05 4.968260e+03 3.527850e+03 7.692870e+03 5.137100e+03 2.207390e+03 2.436660e+03
1332496830641667 2.557750e+05 2.237080e+05 4.963450e+03 4.017370e+03 7.701420e+03 5.269650e+03 2.284400e+03 2.842080e+03
1332496830650000 2.573980e+05 2.209470e+05 6.767500e+03 1.645710e+03 9.107070e+03 4.000180e+03 2.548860e+03 3.624770e+03
1332496830658333 2.649240e+05 2.215590e+05 6.471460e+03 1.110330e+03 9.459650e+03 3.108170e+03 1.696970e+03 3.893440e+03
1332496830666667 2.653390e+05 2.257330e+05 4.348800e+03 3.459510e+03 8.475300e+03 4.031240e+03 5.733470e+02 2.910270e+03
1332496830675000 2.568140e+05 2.269950e+05 3.479540e+03 4.949790e+03 7.499910e+03 5.624710e+03 7.516560e+02 2.347710e+03
1332496830683333 2.533160e+05 2.251610e+05 5.147060e+03 3.218430e+03 8.460160e+03 5.869300e+03 2.336320e+03 2.987960e+03
1332496830691667 2.593600e+05 2.231010e+05 5.549120e+03 1.869950e+03 8.740760e+03 4.668940e+03 2.457910e+03 3.758820e+03
1332496830700000 2.620120e+05 2.240160e+05 4.173610e+03 3.004130e+03 8.157040e+03 3.704730e+03 9.879640e+02 3.652750e+03
1332496830708333 2.571760e+05 2.244200e+05 3.517300e+03 4.118750e+03 7.822240e+03 3.718230e+03 3.726490e+01 2.953680e+03
1332496830716667 2.551460e+05 2.233220e+05 4.923980e+03 2.330680e+03 9.095910e+03 3.792400e+03 1.013070e+03 2.711240e+03
1332496830725000 2.605240e+05 2.236510e+05 5.413630e+03 1.146210e+03 8.817170e+03 4.419650e+03 2.446650e+03 2.832050e+03
1332496830733333 2.620980e+05 2.257520e+05 4.262980e+03 2.270970e+03 7.135480e+03 5.067120e+03 2.294680e+03 3.376620e+03
1332496830741667 2.568890e+05 2.253790e+05 3.606460e+03 3.568190e+03 6.552650e+03 4.970270e+03 1.516380e+03 3.662570e+03
1332496830750000 2.539480e+05 2.226310e+05 5.511700e+03 2.066300e+03 7.952660e+03 4.019910e+03 1.513140e+03 3.752630e+03
1332496830758333 2.597990e+05 2.220670e+05 5.873500e+03 6.085840e+02 9.253780e+03 2.870740e+03 1.348240e+03 3.344200e+03
1332496830766667 2.625470e+05 2.249010e+05 4.346080e+03 1.928100e+03 8.590970e+03 3.455460e+03 9.043910e+02 2.379270e+03
1332496830775000 2.561370e+05 2.267610e+05 3.423560e+03 3.379080e+03 7.471150e+03 4.894170e+03 1.153540e+03 2.031410e+03
1332496830783333 2.503260e+05 2.250130e+05 5.519980e+03 2.423970e+03 7.991760e+03 5.117950e+03 2.098790e+03 3.099240e+03
1332496830791667 2.554540e+05 2.229920e+05 6.547950e+03 4.964960e+02 8.751340e+03 3.900560e+03 2.132290e+03 4.076810e+03
1332496830800000 2.612860e+05 2.234890e+05 5.152850e+03 1.501510e+03 8.425610e+03 2.888030e+03 7.761140e+02 3.786360e+03
1332496830808333 2.589690e+05 2.240690e+05 3.832610e+03 3.001980e+03 7.979260e+03 3.182310e+03 5.271600e+01 2.874800e+03
1332496830816667 2.549460e+05 2.220350e+05 5.317880e+03 2.139800e+03 9.103140e+03 3.955610e+03 1.235170e+03 2.394150e+03
1332496830825000 2.586760e+05 2.212050e+05 6.594910e+03 5.053440e+02 9.423360e+03 4.562470e+03 2.913740e+03 2.892350e+03
1332496830833333 2.621250e+05 2.235660e+05 5.116750e+03 1.773600e+03 8.082200e+03 4.776370e+03 2.386390e+03 3.659730e+03
1332496830841667 2.578350e+05 2.259180e+05 3.714300e+03 3.477080e+03 7.205370e+03 4.554610e+03 7.115390e+02 3.878420e+03
1332496830850000 2.536600e+05 2.243710e+05 5.022450e+03 2.592430e+03 8.277200e+03 4.119370e+03 4.865080e+02 3.666740e+03
1332496830858333 2.595030e+05 2.220610e+05 6.589950e+03 6.599360e+02 9.596920e+03 3.598100e+03 1.702490e+03 3.036600e+03
1332496830866667 2.654950e+05 2.228430e+05 5.541850e+03 1.728430e+03 8.459960e+03 4.492000e+03 2.231970e+03 2.430620e+03
1332496830875000 2.609290e+05 2.249960e+05 4.000950e+03 3.745990e+03 6.983790e+03 5.430860e+03 1.855260e+03 2.533380e+03
1332496830883333 2.527160e+05 2.243350e+05 5.086560e+03 3.401150e+03 7.597970e+03 5.196120e+03 1.755720e+03 3.079760e+03
1332496830891667 2.541100e+05 2.231110e+05 6.822190e+03 1.229080e+03 9.164340e+03 3.761230e+03 1.679390e+03 3.584880e+03
1332496830900000 2.599690e+05 2.246930e+05 6.183950e+03 1.538500e+03 9.222080e+03 3.139170e+03 9.499020e+02 3.180800e+03
1332496830908333 2.590780e+05 2.269130e+05 4.388890e+03 3.694820e+03 8.195020e+03 3.933000e+03 4.260800e+02 2.388450e+03
1332496830916667 2.545630e+05 2.247600e+05 5.168440e+03 4.020940e+03 8.450270e+03 4.758910e+03 1.458900e+03 2.286430e+03
1332496830925000 2.580590e+05 2.212170e+05 6.883460e+03 1.649530e+03 9.232780e+03 4.457650e+03 3.057820e+03 3.031950e+03
1332496830933333 2.646670e+05 2.211770e+05 6.218510e+03 1.645730e+03 8.657180e+03 3.663500e+03 2.528280e+03 3.978340e+03
1332496830941667 2.629250e+05 2.243820e+05 4.627500e+03 3.635930e+03 7.892800e+03 3.431320e+03 6.045090e+02 3.901370e+03
1332496830950000 2.547080e+05 2.254480e+05 4.408250e+03 4.461040e+03 8.197170e+03 3.953750e+03 -4.453460e+01 3.154870e+03
1332496830958333 2.537020e+05 2.246350e+05 5.825770e+03 2.577050e+03 9.590050e+03 4.569250e+03 1.460270e+03 2.785170e+03
1332496830966667 2.602060e+05 2.241400e+05 5.387980e+03 1.951160e+03 8.789510e+03 5.131660e+03 2.706380e+03 2.972480e+03
1332496830975000 2.612400e+05 2.247370e+05 3.860810e+03 3.418310e+03 7.414530e+03 5.284520e+03 2.271380e+03 3.183150e+03
1332496830983333 2.561400e+05 2.232520e+05 3.850010e+03 3.957140e+03 7.262650e+03 4.964640e+03 1.499510e+03 3.453130e+03
1332496830991667 2.561160e+05 2.213490e+05 5.594480e+03 2.054400e+03 8.835130e+03 3.662010e+03 1.485510e+03 3.613010e+03

View File

@@ -1,119 +1,119 @@
1332496830.008333 259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
1332496830.016667 263073.000000 223304.000000 4961.640137 2197.120117 7687.310059 4861.859863 2732.780029 3008.540039
1332496830.025000 257614.000000 223323.000000 5003.660156 3525.139893 7165.310059 4685.620117 1715.380005 3440.479980
1332496830.033333 255780.000000 221915.000000 6357.310059 2145.290039 8426.969727 3775.350098 1475.390015 3797.239990
1332496830.041667 260166.000000 223008.000000 6702.589844 1484.959961 9288.099609 3330.830078 1228.500000 3214.320068
1332496830.050000 261231.000000 226426.000000 4980.060059 2982.379883 8499.629883 4267.669922 994.088989 2292.889893
1332496830.058333 255117.000000 226642.000000 4584.410156 4656.439941 7860.149902 5317.310059 1473.599976 2111.689941
1332496830.066667 253300.000000 223554.000000 6455.089844 3036.649902 8869.750000 4986.310059 2607.360107 2839.590088
1332496830.075000 261061.000000 221263.000000 6951.979980 1500.239990 9386.099609 3791.679932 2677.010010 3980.629883
1332496830.083333 266503.000000 223198.000000 5189.609863 2594.560059 8571.530273 3175.000000 919.840027 3792.010010
1332496830.091667 260692.000000 225184.000000 3782.479980 4642.879883 7662.959961 3917.790039 -251.097000 2907.060059
1332496830.100000 253963.000000 225081.000000 5123.529785 3839.550049 8669.030273 4877.819824 943.723999 2527.449951
1332496830.108333 256555.000000 224169.000000 5930.600098 2298.540039 8906.709961 5331.680176 2549.909912 3053.560059
1332496830.116667 260889.000000 225010.000000 4681.129883 2971.870117 7900.040039 4874.080078 2322.429932 3649.120117
1332496830.125000 257944.000000 224923.000000 3291.139893 4357.089844 7131.589844 4385.560059 1077.050049 3664.040039
1332496830.133333 255009.000000 223018.000000 4584.819824 2864.000000 8469.490234 3625.580078 985.557007 3504.229980
1332496830.141667 260114.000000 221947.000000 5676.189941 1210.339966 9393.780273 3390.239990 1654.020020 3018.699951
1332496830.150000 264277.000000 224438.000000 4446.620117 2176.719971 8142.089844 4584.879883 2327.830078 2615.800049
1332496830.158333 259221.000000 226471.000000 2734.439941 4182.759766 6389.549805 5540.520020 1958.880005 2720.120117
1332496830.166667 252650.000000 224831.000000 4163.640137 2989.989990 7179.200195 5213.060059 1929.550049 3457.659912
1332496830.175000 257083.000000 222048.000000 5759.040039 702.440979 8566.549805 3552.020020 1832.939941 3956.189941
1332496830.183333 263130.000000 222967.000000 5141.140137 1166.119995 8666.959961 2720.370117 971.374023 3479.729980
1332496830.191667 260236.000000 225265.000000 3425.139893 3339.080078 7853.609863 3674.949951 525.908020 2443.310059
1332496830.200000 253503.000000 224527.000000 4398.129883 2927.429932 8110.279785 4842.470215 1513.869995 2467.100098
1332496830.208333 256126.000000 222693.000000 6043.529785 656.223999 8797.559570 4832.410156 2832.370117 3426.139893
1332496830.216667 261677.000000 223608.000000 5830.459961 1033.910034 8123.939941 3980.689941 1927.959961 4092.719971
1332496830.225000 259457.000000 225536.000000 4015.570068 2995.989990 7135.439941 3713.550049 307.220001 3849.429932
1332496830.233333 253352.000000 224216.000000 4650.560059 3196.620117 8131.279785 3586.159912 70.832298 3074.179932
1332496830.241667 256124.000000 221513.000000 6100.479980 821.979980 9757.540039 3474.510010 1647.520020 2559.860107
1332496830.250000 263024.000000 221559.000000 5789.959961 699.416992 9129.740234 4153.080078 2829.250000 2677.270020
1332496830.258333 261720.000000 224015.000000 4358.500000 2645.360107 7414.109863 4810.669922 2225.989990 3185.989990
1332496830.266667 254756.000000 224240.000000 4857.379883 3229.679932 7539.310059 4769.140137 1507.130005 3668.260010
1332496830.275000 256889.000000 222658.000000 6473.419922 1214.109985 9010.759766 3848.729980 1303.839966 3778.500000
1332496830.283333 264208.000000 223316.000000 5700.450195 1116.560059 9087.610352 3846.679932 1293.589966 2891.560059
1332496830.291667 263310.000000 225719.000000 3936.120117 3252.360107 7552.850098 4897.859863 1156.630005 2037.160034
1332496830.300000 255079.000000 225086.000000 4536.450195 3960.110107 7454.589844 5479.069824 1596.359985 2190.800049
1332496830.308333 254487.000000 222508.000000 6635.859863 1758.849976 8732.969727 4466.970215 2650.360107 3139.310059
1332496830.316667 261241.000000 222432.000000 6702.270020 1085.130005 8989.230469 3112.989990 1933.560059 3828.409912
1332496830.325000 262119.000000 225587.000000 4714.950195 2892.360107 8107.819824 2961.310059 239.977997 3273.719971
1332496830.333333 254999.000000 226514.000000 4532.089844 4126.899902 8200.129883 3872.590088 56.089001 2370.580078
1332496830.341667 254289.000000 224033.000000 6538.810059 2251.439941 9419.429688 4564.450195 2077.810059 2508.169922
1332496830.350000 261890.000000 221960.000000 6846.089844 1475.270020 9125.589844 4598.290039 3299.219971 3475.419922
1332496830.358333 264502.000000 223085.000000 5066.379883 3270.560059 7933.169922 4173.709961 1908.910034 3867.459961
1332496830.366667 257889.000000 223656.000000 4201.660156 4473.640137 7688.339844 4161.580078 687.578979 3653.689941
1332496830.375000 254270.000000 223151.000000 5715.140137 2752.139893 9273.320312 3772.949951 896.403992 3256.060059
1332496830.383333 258257.000000 224217.000000 6114.310059 1856.859985 9604.320312 4200.490234 1764.380005 2939.219971
1332496830.391667 260020.000000 226868.000000 4237.529785 3605.879883 8066.220215 5430.250000 2138.580078 2696.709961
1332496830.400000 255083.000000 225924.000000 3350.310059 4853.069824 7045.819824 5925.200195 1893.609985 2897.340088
1332496830.408333 254453.000000 222127.000000 5271.330078 2491.500000 8436.679688 5032.080078 2436.050049 3724.590088
1332496830.416667 262588.000000 219950.000000 5994.620117 789.273987 9029.650391 3515.739990 1953.569946 4014.520020
1332496830.425000 265610.000000 223333.000000 4391.410156 2400.959961 8146.459961 3536.959961 530.231995 3133.919922
1332496830.433333 257470.000000 226977.000000 2975.320068 4633.529785 7278.560059 4640.100098 -50.150200 2024.959961
1332496830.441667 250687.000000 226331.000000 4517.859863 3183.800049 8072.600098 5281.660156 1605.140015 2335.139893
1332496830.450000 255563.000000 224495.000000 5551.000000 1101.300049 8461.490234 4725.700195 2726.669922 3480.540039
1332496830.458333 261335.000000 224645.000000 4764.680176 1557.020020 7833.350098 3524.810059 1577.410034 4038.620117
1332496830.466667 260269.000000 224008.000000 3558.030029 2987.610107 7362.439941 3279.229980 562.442017 3786.550049
1332496830.475000 257435.000000 221777.000000 4972.600098 2166.879883 8481.440430 3328.719971 1037.130005 3271.370117
1332496830.483333 261046.000000 221550.000000 5816.180176 590.216980 9120.929688 3895.399902 2382.669922 2824.169922
1332496830.491667 262766.000000 224473.000000 4835.049805 1785.770020 7880.759766 4745.620117 2443.659912 3229.550049
1332496830.500000 256509.000000 226413.000000 3758.870117 3461.199951 6743.770020 4928.959961 1536.619995 3546.689941
1332496830.508333 250793.000000 224372.000000 5218.490234 2865.260010 7803.959961 4351.089844 1333.819946 3680.489990
1332496830.516667 256319.000000 222066.000000 6403.970215 732.344971 9627.759766 3089.300049 1516.780029 3653.689941
1332496830.525000 263343.000000 223235.000000 5200.430176 1388.579956 9372.849609 3371.229980 1450.390015 2678.909912
1332496830.533333 260903.000000 225110.000000 3722.580078 3246.659912 7876.540039 4716.810059 1498.439941 2116.520020
1332496830.541667 254416.000000 223769.000000 4841.649902 2956.399902 8115.919922 5392.359863 2142.810059 2652.320068
1332496830.550000 256698.000000 222172.000000 6471.229980 970.395996 8834.980469 4816.839844 2376.629883 3605.860107
1332496830.558333 261841.000000 223537.000000 5500.740234 1189.660034 8365.730469 4016.469971 1042.270020 3821.199951
1332496830.566667 259503.000000 225840.000000 3827.929932 3088.840088 7676.140137 3978.310059 -357.006989 3016.419922
1332496830.575000 253457.000000 224636.000000 4914.609863 3097.449951 8224.900391 4321.439941 171.373993 2412.360107
1332496830.583333 256029.000000 222221.000000 6841.799805 1028.500000 9252.299805 4387.569824 2418.139893 2510.100098
1332496830.591667 262840.000000 222550.000000 6210.250000 1410.729980 8538.900391 4152.580078 3009.300049 3219.760010
1332496830.600000 261633.000000 225065.000000 4284.529785 3357.209961 7282.169922 3823.590088 1402.839966 3644.669922
1332496830.608333 254591.000000 225109.000000 4693.160156 3647.739990 7745.160156 3686.379883 490.161011 3448.860107
1332496830.616667 254780.000000 223599.000000 6527.379883 1569.869995 9438.429688 3456.580078 1162.520020 3252.010010
1332496830.625000 260639.000000 224107.000000 6531.049805 1633.050049 9283.719727 4174.020020 2089.550049 2775.750000
1332496830.633333 261108.000000 225472.000000 4968.259766 3527.850098 7692.870117 5137.100098 2207.389893 2436.659912
1332496830.641667 255775.000000 223708.000000 4963.450195 4017.370117 7701.419922 5269.649902 2284.399902 2842.080078
1332496830.650000 257398.000000 220947.000000 6767.500000 1645.709961 9107.070312 4000.179932 2548.860107 3624.770020
1332496830.658333 264924.000000 221559.000000 6471.459961 1110.329956 9459.650391 3108.169922 1696.969971 3893.439941
1332496830.666667 265339.000000 225733.000000 4348.799805 3459.510010 8475.299805 4031.239990 573.346985 2910.270020
1332496830.675000 256814.000000 226995.000000 3479.540039 4949.790039 7499.910156 5624.709961 751.656006 2347.709961
1332496830.683333 253316.000000 225161.000000 5147.060059 3218.429932 8460.160156 5869.299805 2336.320068 2987.959961
1332496830.691667 259360.000000 223101.000000 5549.120117 1869.949951 8740.759766 4668.939941 2457.909912 3758.820068
1332496830.700000 262012.000000 224016.000000 4173.609863 3004.129883 8157.040039 3704.729980 987.963989 3652.750000
1332496830.708333 257176.000000 224420.000000 3517.300049 4118.750000 7822.240234 3718.229980 37.264900 2953.679932
1332496830.716667 255146.000000 223322.000000 4923.979980 2330.679932 9095.910156 3792.399902 1013.070007 2711.239990
1332496830.725000 260524.000000 223651.000000 5413.629883 1146.209961 8817.169922 4419.649902 2446.649902 2832.050049
1332496830.733333 262098.000000 225752.000000 4262.979980 2270.969971 7135.479980 5067.120117 2294.679932 3376.620117
1332496830.741667 256889.000000 225379.000000 3606.459961 3568.189941 6552.649902 4970.270020 1516.380005 3662.570068
1332496830.750000 253948.000000 222631.000000 5511.700195 2066.300049 7952.660156 4019.909912 1513.140015 3752.629883
1332496830.758333 259799.000000 222067.000000 5873.500000 608.583984 9253.780273 2870.739990 1348.239990 3344.199951
1332496830.766667 262547.000000 224901.000000 4346.080078 1928.099976 8590.969727 3455.459961 904.390991 2379.270020
1332496830.775000 256137.000000 226761.000000 3423.560059 3379.080078 7471.149902 4894.169922 1153.540039 2031.410034
1332496830.783333 250326.000000 225013.000000 5519.979980 2423.969971 7991.759766 5117.950195 2098.790039 3099.239990
1332496830.791667 255454.000000 222992.000000 6547.950195 496.496002 8751.339844 3900.560059 2132.290039 4076.810059
1332496830.800000 261286.000000 223489.000000 5152.850098 1501.510010 8425.610352 2888.030029 776.114014 3786.360107
1332496830.808333 258969.000000 224069.000000 3832.610107 3001.979980 7979.259766 3182.310059 52.716000 2874.800049
1332496830.816667 254946.000000 222035.000000 5317.879883 2139.800049 9103.139648 3955.610107 1235.170044 2394.149902
1332496830.825000 258676.000000 221205.000000 6594.910156 505.343994 9423.360352 4562.470215 2913.739990 2892.350098
1332496830.833333 262125.000000 223566.000000 5116.750000 1773.599976 8082.200195 4776.370117 2386.389893 3659.729980
1332496830.841667 257835.000000 225918.000000 3714.300049 3477.080078 7205.370117 4554.609863 711.539001 3878.419922
1332496830.850000 253660.000000 224371.000000 5022.450195 2592.429932 8277.200195 4119.370117 486.507996 3666.739990
1332496830.858333 259503.000000 222061.000000 6589.950195 659.935974 9596.919922 3598.100098 1702.489990 3036.600098
1332496830.866667 265495.000000 222843.000000 5541.850098 1728.430054 8459.959961 4492.000000 2231.969971 2430.620117
1332496830.875000 260929.000000 224996.000000 4000.949951 3745.989990 6983.790039 5430.859863 1855.260010 2533.379883
1332496830.883333 252716.000000 224335.000000 5086.560059 3401.149902 7597.970215 5196.120117 1755.719971 3079.760010
1332496830.891667 254110.000000 223111.000000 6822.189941 1229.079956 9164.339844 3761.229980 1679.390015 3584.879883
1332496830.900000 259969.000000 224693.000000 6183.950195 1538.500000 9222.080078 3139.169922 949.901978 3180.800049
1332496830.908333 259078.000000 226913.000000 4388.890137 3694.820068 8195.019531 3933.000000 426.079987 2388.449951
1332496830.916667 254563.000000 224760.000000 5168.439941 4020.939941 8450.269531 4758.910156 1458.900024 2286.429932
1332496830.925000 258059.000000 221217.000000 6883.459961 1649.530029 9232.780273 4457.649902 3057.820068 3031.949951
1332496830.933333 264667.000000 221177.000000 6218.509766 1645.729980 8657.179688 3663.500000 2528.280029 3978.340088
1332496830.941667 262925.000000 224382.000000 4627.500000 3635.929932 7892.799805 3431.320068 604.508972 3901.370117
1332496830.950000 254708.000000 225448.000000 4408.250000 4461.040039 8197.169922 3953.750000 -44.534599 3154.870117
1332496830.958333 253702.000000 224635.000000 5825.770020 2577.050049 9590.049805 4569.250000 1460.270020 2785.169922
1332496830.966667 260206.000000 224140.000000 5387.979980 1951.160034 8789.509766 5131.660156 2706.379883 2972.479980
1332496830.975000 261240.000000 224737.000000 3860.810059 3418.310059 7414.529785 5284.520020 2271.379883 3183.149902
1332496830.983333 256140.000000 223252.000000 3850.010010 3957.139893 7262.649902 4964.640137 1499.510010 3453.129883
1332496830.991667 256116.000000 221349.000000 5594.479980 2054.399902 8835.129883 3662.010010 1485.510010 3613.010010
1332496830008333 2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
1332496830016667 2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03
1332496830025000 2.576140e+05 2.233230e+05 5.003660e+03 3.525140e+03 7.165310e+03 4.685620e+03 1.715380e+03 3.440480e+03
1332496830033333 2.557800e+05 2.219150e+05 6.357310e+03 2.145290e+03 8.426970e+03 3.775350e+03 1.475390e+03 3.797240e+03
1332496830041667 2.601660e+05 2.230080e+05 6.702590e+03 1.484960e+03 9.288100e+03 3.330830e+03 1.228500e+03 3.214320e+03
1332496830050000 2.612310e+05 2.264260e+05 4.980060e+03 2.982380e+03 8.499630e+03 4.267670e+03 9.940890e+02 2.292890e+03
1332496830058333 2.551170e+05 2.266420e+05 4.584410e+03 4.656440e+03 7.860150e+03 5.317310e+03 1.473600e+03 2.111690e+03
1332496830066667 2.533000e+05 2.235540e+05 6.455090e+03 3.036650e+03 8.869750e+03 4.986310e+03 2.607360e+03 2.839590e+03
1332496830075000 2.610610e+05 2.212630e+05 6.951980e+03 1.500240e+03 9.386100e+03 3.791680e+03 2.677010e+03 3.980630e+03
1332496830083333 2.665030e+05 2.231980e+05 5.189610e+03 2.594560e+03 8.571530e+03 3.175000e+03 9.198400e+02 3.792010e+03
1332496830091667 2.606920e+05 2.251840e+05 3.782480e+03 4.642880e+03 7.662960e+03 3.917790e+03 -2.510970e+02 2.907060e+03
1332496830100000 2.539630e+05 2.250810e+05 5.123530e+03 3.839550e+03 8.669030e+03 4.877820e+03 9.437240e+02 2.527450e+03
1332496830108333 2.565550e+05 2.241690e+05 5.930600e+03 2.298540e+03 8.906710e+03 5.331680e+03 2.549910e+03 3.053560e+03
1332496830116667 2.608890e+05 2.250100e+05 4.681130e+03 2.971870e+03 7.900040e+03 4.874080e+03 2.322430e+03 3.649120e+03
1332496830125000 2.579440e+05 2.249230e+05 3.291140e+03 4.357090e+03 7.131590e+03 4.385560e+03 1.077050e+03 3.664040e+03
1332496830133333 2.550090e+05 2.230180e+05 4.584820e+03 2.864000e+03 8.469490e+03 3.625580e+03 9.855570e+02 3.504230e+03
1332496830141667 2.601140e+05 2.219470e+05 5.676190e+03 1.210340e+03 9.393780e+03 3.390240e+03 1.654020e+03 3.018700e+03
1332496830150000 2.642770e+05 2.244380e+05 4.446620e+03 2.176720e+03 8.142090e+03 4.584880e+03 2.327830e+03 2.615800e+03
1332496830158333 2.592210e+05 2.264710e+05 2.734440e+03 4.182760e+03 6.389550e+03 5.540520e+03 1.958880e+03 2.720120e+03
1332496830166667 2.526500e+05 2.248310e+05 4.163640e+03 2.989990e+03 7.179200e+03 5.213060e+03 1.929550e+03 3.457660e+03
1332496830175000 2.570830e+05 2.220480e+05 5.759040e+03 7.024410e+02 8.566550e+03 3.552020e+03 1.832940e+03 3.956190e+03
1332496830183333 2.631300e+05 2.229670e+05 5.141140e+03 1.166120e+03 8.666960e+03 2.720370e+03 9.713740e+02 3.479730e+03
1332496830191667 2.602360e+05 2.252650e+05 3.425140e+03 3.339080e+03 7.853610e+03 3.674950e+03 5.259080e+02 2.443310e+03
1332496830200000 2.535030e+05 2.245270e+05 4.398130e+03 2.927430e+03 8.110280e+03 4.842470e+03 1.513870e+03 2.467100e+03
1332496830208333 2.561260e+05 2.226930e+05 6.043530e+03 6.562240e+02 8.797560e+03 4.832410e+03 2.832370e+03 3.426140e+03
1332496830216667 2.616770e+05 2.236080e+05 5.830460e+03 1.033910e+03 8.123940e+03 3.980690e+03 1.927960e+03 4.092720e+03
1332496830225000 2.594570e+05 2.255360e+05 4.015570e+03 2.995990e+03 7.135440e+03 3.713550e+03 3.072200e+02 3.849430e+03
1332496830233333 2.533520e+05 2.242160e+05 4.650560e+03 3.196620e+03 8.131280e+03 3.586160e+03 7.083230e+01 3.074180e+03
1332496830241667 2.561240e+05 2.215130e+05 6.100480e+03 8.219800e+02 9.757540e+03 3.474510e+03 1.647520e+03 2.559860e+03
1332496830250000 2.630240e+05 2.215590e+05 5.789960e+03 6.994170e+02 9.129740e+03 4.153080e+03 2.829250e+03 2.677270e+03
1332496830258333 2.617200e+05 2.240150e+05 4.358500e+03 2.645360e+03 7.414110e+03 4.810670e+03 2.225990e+03 3.185990e+03
1332496830266667 2.547560e+05 2.242400e+05 4.857380e+03 3.229680e+03 7.539310e+03 4.769140e+03 1.507130e+03 3.668260e+03
1332496830275000 2.568890e+05 2.226580e+05 6.473420e+03 1.214110e+03 9.010760e+03 3.848730e+03 1.303840e+03 3.778500e+03
1332496830283333 2.642080e+05 2.233160e+05 5.700450e+03 1.116560e+03 9.087610e+03 3.846680e+03 1.293590e+03 2.891560e+03
1332496830291667 2.633100e+05 2.257190e+05 3.936120e+03 3.252360e+03 7.552850e+03 4.897860e+03 1.156630e+03 2.037160e+03
1332496830300000 2.550790e+05 2.250860e+05 4.536450e+03 3.960110e+03 7.454590e+03 5.479070e+03 1.596360e+03 2.190800e+03
1332496830308333 2.544870e+05 2.225080e+05 6.635860e+03 1.758850e+03 8.732970e+03 4.466970e+03 2.650360e+03 3.139310e+03
1332496830316667 2.612410e+05 2.224320e+05 6.702270e+03 1.085130e+03 8.989230e+03 3.112990e+03 1.933560e+03 3.828410e+03
1332496830325000 2.621190e+05 2.255870e+05 4.714950e+03 2.892360e+03 8.107820e+03 2.961310e+03 2.399780e+02 3.273720e+03
1332496830333333 2.549990e+05 2.265140e+05 4.532090e+03 4.126900e+03 8.200130e+03 3.872590e+03 5.608900e+01 2.370580e+03
1332496830341667 2.542890e+05 2.240330e+05 6.538810e+03 2.251440e+03 9.419430e+03 4.564450e+03 2.077810e+03 2.508170e+03
1332496830350000 2.618900e+05 2.219600e+05 6.846090e+03 1.475270e+03 9.125590e+03 4.598290e+03 3.299220e+03 3.475420e+03
1332496830358333 2.645020e+05 2.230850e+05 5.066380e+03 3.270560e+03 7.933170e+03 4.173710e+03 1.908910e+03 3.867460e+03
1332496830366667 2.578890e+05 2.236560e+05 4.201660e+03 4.473640e+03 7.688340e+03 4.161580e+03 6.875790e+02 3.653690e+03
1332496830375000 2.542700e+05 2.231510e+05 5.715140e+03 2.752140e+03 9.273320e+03 3.772950e+03 8.964040e+02 3.256060e+03
1332496830383333 2.582570e+05 2.242170e+05 6.114310e+03 1.856860e+03 9.604320e+03 4.200490e+03 1.764380e+03 2.939220e+03
1332496830391667 2.600200e+05 2.268680e+05 4.237530e+03 3.605880e+03 8.066220e+03 5.430250e+03 2.138580e+03 2.696710e+03
1332496830400000 2.550830e+05 2.259240e+05 3.350310e+03 4.853070e+03 7.045820e+03 5.925200e+03 1.893610e+03 2.897340e+03
1332496830408333 2.544530e+05 2.221270e+05 5.271330e+03 2.491500e+03 8.436680e+03 5.032080e+03 2.436050e+03 3.724590e+03
1332496830416667 2.625880e+05 2.199500e+05 5.994620e+03 7.892740e+02 9.029650e+03 3.515740e+03 1.953570e+03 4.014520e+03
1332496830425000 2.656100e+05 2.233330e+05 4.391410e+03 2.400960e+03 8.146460e+03 3.536960e+03 5.302320e+02 3.133920e+03
1332496830433333 2.574700e+05 2.269770e+05 2.975320e+03 4.633530e+03 7.278560e+03 4.640100e+03 -5.015020e+01 2.024960e+03
1332496830441667 2.506870e+05 2.263310e+05 4.517860e+03 3.183800e+03 8.072600e+03 5.281660e+03 1.605140e+03 2.335140e+03
1332496830450000 2.555630e+05 2.244950e+05 5.551000e+03 1.101300e+03 8.461490e+03 4.725700e+03 2.726670e+03 3.480540e+03
1332496830458333 2.613350e+05 2.246450e+05 4.764680e+03 1.557020e+03 7.833350e+03 3.524810e+03 1.577410e+03 4.038620e+03
1332496830466667 2.602690e+05 2.240080e+05 3.558030e+03 2.987610e+03 7.362440e+03 3.279230e+03 5.624420e+02 3.786550e+03
1332496830475000 2.574350e+05 2.217770e+05 4.972600e+03 2.166880e+03 8.481440e+03 3.328720e+03 1.037130e+03 3.271370e+03
1332496830483333 2.610460e+05 2.215500e+05 5.816180e+03 5.902170e+02 9.120930e+03 3.895400e+03 2.382670e+03 2.824170e+03
1332496830491667 2.627660e+05 2.244730e+05 4.835050e+03 1.785770e+03 7.880760e+03 4.745620e+03 2.443660e+03 3.229550e+03
1332496830500000 2.565090e+05 2.264130e+05 3.758870e+03 3.461200e+03 6.743770e+03 4.928960e+03 1.536620e+03 3.546690e+03
1332496830508333 2.507930e+05 2.243720e+05 5.218490e+03 2.865260e+03 7.803960e+03 4.351090e+03 1.333820e+03 3.680490e+03
1332496830516667 2.563190e+05 2.220660e+05 6.403970e+03 7.323450e+02 9.627760e+03 3.089300e+03 1.516780e+03 3.653690e+03
1332496830525000 2.633430e+05 2.232350e+05 5.200430e+03 1.388580e+03 9.372850e+03 3.371230e+03 1.450390e+03 2.678910e+03
1332496830533333 2.609030e+05 2.251100e+05 3.722580e+03 3.246660e+03 7.876540e+03 4.716810e+03 1.498440e+03 2.116520e+03
1332496830541667 2.544160e+05 2.237690e+05 4.841650e+03 2.956400e+03 8.115920e+03 5.392360e+03 2.142810e+03 2.652320e+03
1332496830550000 2.566980e+05 2.221720e+05 6.471230e+03 9.703960e+02 8.834980e+03 4.816840e+03 2.376630e+03 3.605860e+03
1332496830558333 2.618410e+05 2.235370e+05 5.500740e+03 1.189660e+03 8.365730e+03 4.016470e+03 1.042270e+03 3.821200e+03
1332496830566667 2.595030e+05 2.258400e+05 3.827930e+03 3.088840e+03 7.676140e+03 3.978310e+03 -3.570070e+02 3.016420e+03
1332496830575000 2.534570e+05 2.246360e+05 4.914610e+03 3.097450e+03 8.224900e+03 4.321440e+03 1.713740e+02 2.412360e+03
1332496830583333 2.560290e+05 2.222210e+05 6.841800e+03 1.028500e+03 9.252300e+03 4.387570e+03 2.418140e+03 2.510100e+03
1332496830591667 2.628400e+05 2.225500e+05 6.210250e+03 1.410730e+03 8.538900e+03 4.152580e+03 3.009300e+03 3.219760e+03
1332496830600000 2.616330e+05 2.250650e+05 4.284530e+03 3.357210e+03 7.282170e+03 3.823590e+03 1.402840e+03 3.644670e+03
1332496830608333 2.545910e+05 2.251090e+05 4.693160e+03 3.647740e+03 7.745160e+03 3.686380e+03 4.901610e+02 3.448860e+03
1332496830616667 2.547800e+05 2.235990e+05 6.527380e+03 1.569870e+03 9.438430e+03 3.456580e+03 1.162520e+03 3.252010e+03
1332496830625000 2.606390e+05 2.241070e+05 6.531050e+03 1.633050e+03 9.283720e+03 4.174020e+03 2.089550e+03 2.775750e+03
1332496830633333 2.611080e+05 2.254720e+05 4.968260e+03 3.527850e+03 7.692870e+03 5.137100e+03 2.207390e+03 2.436660e+03
1332496830641667 2.557750e+05 2.237080e+05 4.963450e+03 4.017370e+03 7.701420e+03 5.269650e+03 2.284400e+03 2.842080e+03
1332496830650000 2.573980e+05 2.209470e+05 6.767500e+03 1.645710e+03 9.107070e+03 4.000180e+03 2.548860e+03 3.624770e+03
1332496830658333 2.649240e+05 2.215590e+05 6.471460e+03 1.110330e+03 9.459650e+03 3.108170e+03 1.696970e+03 3.893440e+03
1332496830666667 2.653390e+05 2.257330e+05 4.348800e+03 3.459510e+03 8.475300e+03 4.031240e+03 5.733470e+02 2.910270e+03
1332496830675000 2.568140e+05 2.269950e+05 3.479540e+03 4.949790e+03 7.499910e+03 5.624710e+03 7.516560e+02 2.347710e+03
1332496830683333 2.533160e+05 2.251610e+05 5.147060e+03 3.218430e+03 8.460160e+03 5.869300e+03 2.336320e+03 2.987960e+03
1332496830691667 2.593600e+05 2.231010e+05 5.549120e+03 1.869950e+03 8.740760e+03 4.668940e+03 2.457910e+03 3.758820e+03
1332496830700000 2.620120e+05 2.240160e+05 4.173610e+03 3.004130e+03 8.157040e+03 3.704730e+03 9.879640e+02 3.652750e+03
1332496830708333 2.571760e+05 2.244200e+05 3.517300e+03 4.118750e+03 7.822240e+03 3.718230e+03 3.726490e+01 2.953680e+03
1332496830716667 2.551460e+05 2.233220e+05 4.923980e+03 2.330680e+03 9.095910e+03 3.792400e+03 1.013070e+03 2.711240e+03
1332496830725000 2.605240e+05 2.236510e+05 5.413630e+03 1.146210e+03 8.817170e+03 4.419650e+03 2.446650e+03 2.832050e+03
1332496830733333 2.620980e+05 2.257520e+05 4.262980e+03 2.270970e+03 7.135480e+03 5.067120e+03 2.294680e+03 3.376620e+03
1332496830741667 2.568890e+05 2.253790e+05 3.606460e+03 3.568190e+03 6.552650e+03 4.970270e+03 1.516380e+03 3.662570e+03
1332496830750000 2.539480e+05 2.226310e+05 5.511700e+03 2.066300e+03 7.952660e+03 4.019910e+03 1.513140e+03 3.752630e+03
1332496830758333 2.597990e+05 2.220670e+05 5.873500e+03 6.085840e+02 9.253780e+03 2.870740e+03 1.348240e+03 3.344200e+03
1332496830766667 2.625470e+05 2.249010e+05 4.346080e+03 1.928100e+03 8.590970e+03 3.455460e+03 9.043910e+02 2.379270e+03
1332496830775000 2.561370e+05 2.267610e+05 3.423560e+03 3.379080e+03 7.471150e+03 4.894170e+03 1.153540e+03 2.031410e+03
1332496830783333 2.503260e+05 2.250130e+05 5.519980e+03 2.423970e+03 7.991760e+03 5.117950e+03 2.098790e+03 3.099240e+03
1332496830791667 2.554540e+05 2.229920e+05 6.547950e+03 4.964960e+02 8.751340e+03 3.900560e+03 2.132290e+03 4.076810e+03
1332496830800000 2.612860e+05 2.234890e+05 5.152850e+03 1.501510e+03 8.425610e+03 2.888030e+03 7.761140e+02 3.786360e+03
1332496830808333 2.589690e+05 2.240690e+05 3.832610e+03 3.001980e+03 7.979260e+03 3.182310e+03 5.271600e+01 2.874800e+03
1332496830816667 2.549460e+05 2.220350e+05 5.317880e+03 2.139800e+03 9.103140e+03 3.955610e+03 1.235170e+03 2.394150e+03
1332496830825000 2.586760e+05 2.212050e+05 6.594910e+03 5.053440e+02 9.423360e+03 4.562470e+03 2.913740e+03 2.892350e+03
1332496830833333 2.621250e+05 2.235660e+05 5.116750e+03 1.773600e+03 8.082200e+03 4.776370e+03 2.386390e+03 3.659730e+03
1332496830841667 2.578350e+05 2.259180e+05 3.714300e+03 3.477080e+03 7.205370e+03 4.554610e+03 7.115390e+02 3.878420e+03
1332496830850000 2.536600e+05 2.243710e+05 5.022450e+03 2.592430e+03 8.277200e+03 4.119370e+03 4.865080e+02 3.666740e+03
1332496830858333 2.595030e+05 2.220610e+05 6.589950e+03 6.599360e+02 9.596920e+03 3.598100e+03 1.702490e+03 3.036600e+03
1332496830866667 2.654950e+05 2.228430e+05 5.541850e+03 1.728430e+03 8.459960e+03 4.492000e+03 2.231970e+03 2.430620e+03
1332496830875000 2.609290e+05 2.249960e+05 4.000950e+03 3.745990e+03 6.983790e+03 5.430860e+03 1.855260e+03 2.533380e+03
1332496830883333 2.527160e+05 2.243350e+05 5.086560e+03 3.401150e+03 7.597970e+03 5.196120e+03 1.755720e+03 3.079760e+03
1332496830891667 2.541100e+05 2.231110e+05 6.822190e+03 1.229080e+03 9.164340e+03 3.761230e+03 1.679390e+03 3.584880e+03
1332496830900000 2.599690e+05 2.246930e+05 6.183950e+03 1.538500e+03 9.222080e+03 3.139170e+03 9.499020e+02 3.180800e+03
1332496830908333 2.590780e+05 2.269130e+05 4.388890e+03 3.694820e+03 8.195020e+03 3.933000e+03 4.260800e+02 2.388450e+03
1332496830916667 2.545630e+05 2.247600e+05 5.168440e+03 4.020940e+03 8.450270e+03 4.758910e+03 1.458900e+03 2.286430e+03
1332496830925000 2.580590e+05 2.212170e+05 6.883460e+03 1.649530e+03 9.232780e+03 4.457650e+03 3.057820e+03 3.031950e+03
1332496830933333 2.646670e+05 2.211770e+05 6.218510e+03 1.645730e+03 8.657180e+03 3.663500e+03 2.528280e+03 3.978340e+03
1332496830941667 2.629250e+05 2.243820e+05 4.627500e+03 3.635930e+03 7.892800e+03 3.431320e+03 6.045090e+02 3.901370e+03
1332496830950000 2.547080e+05 2.254480e+05 4.408250e+03 4.461040e+03 8.197170e+03 3.953750e+03 -4.453460e+01 3.154870e+03
1332496830958333 2.537020e+05 2.246350e+05 5.825770e+03 2.577050e+03 9.590050e+03 4.569250e+03 1.460270e+03 2.785170e+03
1332496830966667 2.602060e+05 2.241400e+05 5.387980e+03 1.951160e+03 8.789510e+03 5.131660e+03 2.706380e+03 2.972480e+03
1332496830975000 2.612400e+05 2.247370e+05 3.860810e+03 3.418310e+03 7.414530e+03 5.284520e+03 2.271380e+03 3.183150e+03
1332496830983333 2.561400e+05 2.232520e+05 3.850010e+03 3.957140e+03 7.262650e+03 4.964640e+03 1.499510e+03 3.453130e+03
1332496830991667 2.561160e+05 2.213490e+05 5.594480e+03 2.054400e+03 8.835130e+03 3.662010e+03 1.485510e+03 3.613010e+03

View File

@@ -1 +1 @@
1332496830.008333 259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
1332496830008333 2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03

View File

@@ -1,2 +1,2 @@
1332496830.008333 259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
1332496830.016667 263073.000000 223304.000000 4961.640137 2197.120117 7687.310059 4861.859863 2732.780029 3008.540039
1332496830008333 2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
1332496830016667 2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03

View File

@@ -1,124 +1,124 @@
# path: /newton/prep
# layout: PrepData
# layout: float32_8
# start: Fri, 23 Mar 2012 10:00:30.000000 +0000
# end: Fri, 23 Mar 2012 10:00:31.000000 +0000
251774.000000 224241.000000 5688.100098 1915.530029 9329.219727 4183.709961 1212.349976 2641.790039
259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
263073.000000 223304.000000 4961.640137 2197.120117 7687.310059 4861.859863 2732.780029 3008.540039
257614.000000 223323.000000 5003.660156 3525.139893 7165.310059 4685.620117 1715.380005 3440.479980
255780.000000 221915.000000 6357.310059 2145.290039 8426.969727 3775.350098 1475.390015 3797.239990
260166.000000 223008.000000 6702.589844 1484.959961 9288.099609 3330.830078 1228.500000 3214.320068
261231.000000 226426.000000 4980.060059 2982.379883 8499.629883 4267.669922 994.088989 2292.889893
255117.000000 226642.000000 4584.410156 4656.439941 7860.149902 5317.310059 1473.599976 2111.689941
253300.000000 223554.000000 6455.089844 3036.649902 8869.750000 4986.310059 2607.360107 2839.590088
261061.000000 221263.000000 6951.979980 1500.239990 9386.099609 3791.679932 2677.010010 3980.629883
266503.000000 223198.000000 5189.609863 2594.560059 8571.530273 3175.000000 919.840027 3792.010010
260692.000000 225184.000000 3782.479980 4642.879883 7662.959961 3917.790039 -251.097000 2907.060059
253963.000000 225081.000000 5123.529785 3839.550049 8669.030273 4877.819824 943.723999 2527.449951
256555.000000 224169.000000 5930.600098 2298.540039 8906.709961 5331.680176 2549.909912 3053.560059
260889.000000 225010.000000 4681.129883 2971.870117 7900.040039 4874.080078 2322.429932 3649.120117
257944.000000 224923.000000 3291.139893 4357.089844 7131.589844 4385.560059 1077.050049 3664.040039
255009.000000 223018.000000 4584.819824 2864.000000 8469.490234 3625.580078 985.557007 3504.229980
260114.000000 221947.000000 5676.189941 1210.339966 9393.780273 3390.239990 1654.020020 3018.699951
264277.000000 224438.000000 4446.620117 2176.719971 8142.089844 4584.879883 2327.830078 2615.800049
259221.000000 226471.000000 2734.439941 4182.759766 6389.549805 5540.520020 1958.880005 2720.120117
252650.000000 224831.000000 4163.640137 2989.989990 7179.200195 5213.060059 1929.550049 3457.659912
257083.000000 222048.000000 5759.040039 702.440979 8566.549805 3552.020020 1832.939941 3956.189941
263130.000000 222967.000000 5141.140137 1166.119995 8666.959961 2720.370117 971.374023 3479.729980
260236.000000 225265.000000 3425.139893 3339.080078 7853.609863 3674.949951 525.908020 2443.310059
253503.000000 224527.000000 4398.129883 2927.429932 8110.279785 4842.470215 1513.869995 2467.100098
256126.000000 222693.000000 6043.529785 656.223999 8797.559570 4832.410156 2832.370117 3426.139893
261677.000000 223608.000000 5830.459961 1033.910034 8123.939941 3980.689941 1927.959961 4092.719971
259457.000000 225536.000000 4015.570068 2995.989990 7135.439941 3713.550049 307.220001 3849.429932
253352.000000 224216.000000 4650.560059 3196.620117 8131.279785 3586.159912 70.832298 3074.179932
256124.000000 221513.000000 6100.479980 821.979980 9757.540039 3474.510010 1647.520020 2559.860107
263024.000000 221559.000000 5789.959961 699.416992 9129.740234 4153.080078 2829.250000 2677.270020
261720.000000 224015.000000 4358.500000 2645.360107 7414.109863 4810.669922 2225.989990 3185.989990
254756.000000 224240.000000 4857.379883 3229.679932 7539.310059 4769.140137 1507.130005 3668.260010
256889.000000 222658.000000 6473.419922 1214.109985 9010.759766 3848.729980 1303.839966 3778.500000
264208.000000 223316.000000 5700.450195 1116.560059 9087.610352 3846.679932 1293.589966 2891.560059
263310.000000 225719.000000 3936.120117 3252.360107 7552.850098 4897.859863 1156.630005 2037.160034
255079.000000 225086.000000 4536.450195 3960.110107 7454.589844 5479.069824 1596.359985 2190.800049
254487.000000 222508.000000 6635.859863 1758.849976 8732.969727 4466.970215 2650.360107 3139.310059
261241.000000 222432.000000 6702.270020 1085.130005 8989.230469 3112.989990 1933.560059 3828.409912
262119.000000 225587.000000 4714.950195 2892.360107 8107.819824 2961.310059 239.977997 3273.719971
254999.000000 226514.000000 4532.089844 4126.899902 8200.129883 3872.590088 56.089001 2370.580078
254289.000000 224033.000000 6538.810059 2251.439941 9419.429688 4564.450195 2077.810059 2508.169922
261890.000000 221960.000000 6846.089844 1475.270020 9125.589844 4598.290039 3299.219971 3475.419922
264502.000000 223085.000000 5066.379883 3270.560059 7933.169922 4173.709961 1908.910034 3867.459961
257889.000000 223656.000000 4201.660156 4473.640137 7688.339844 4161.580078 687.578979 3653.689941
254270.000000 223151.000000 5715.140137 2752.139893 9273.320312 3772.949951 896.403992 3256.060059
258257.000000 224217.000000 6114.310059 1856.859985 9604.320312 4200.490234 1764.380005 2939.219971
260020.000000 226868.000000 4237.529785 3605.879883 8066.220215 5430.250000 2138.580078 2696.709961
255083.000000 225924.000000 3350.310059 4853.069824 7045.819824 5925.200195 1893.609985 2897.340088
254453.000000 222127.000000 5271.330078 2491.500000 8436.679688 5032.080078 2436.050049 3724.590088
262588.000000 219950.000000 5994.620117 789.273987 9029.650391 3515.739990 1953.569946 4014.520020
265610.000000 223333.000000 4391.410156 2400.959961 8146.459961 3536.959961 530.231995 3133.919922
257470.000000 226977.000000 2975.320068 4633.529785 7278.560059 4640.100098 -50.150200 2024.959961
250687.000000 226331.000000 4517.859863 3183.800049 8072.600098 5281.660156 1605.140015 2335.139893
255563.000000 224495.000000 5551.000000 1101.300049 8461.490234 4725.700195 2726.669922 3480.540039
261335.000000 224645.000000 4764.680176 1557.020020 7833.350098 3524.810059 1577.410034 4038.620117
260269.000000 224008.000000 3558.030029 2987.610107 7362.439941 3279.229980 562.442017 3786.550049
257435.000000 221777.000000 4972.600098 2166.879883 8481.440430 3328.719971 1037.130005 3271.370117
261046.000000 221550.000000 5816.180176 590.216980 9120.929688 3895.399902 2382.669922 2824.169922
262766.000000 224473.000000 4835.049805 1785.770020 7880.759766 4745.620117 2443.659912 3229.550049
256509.000000 226413.000000 3758.870117 3461.199951 6743.770020 4928.959961 1536.619995 3546.689941
250793.000000 224372.000000 5218.490234 2865.260010 7803.959961 4351.089844 1333.819946 3680.489990
256319.000000 222066.000000 6403.970215 732.344971 9627.759766 3089.300049 1516.780029 3653.689941
263343.000000 223235.000000 5200.430176 1388.579956 9372.849609 3371.229980 1450.390015 2678.909912
260903.000000 225110.000000 3722.580078 3246.659912 7876.540039 4716.810059 1498.439941 2116.520020
254416.000000 223769.000000 4841.649902 2956.399902 8115.919922 5392.359863 2142.810059 2652.320068
256698.000000 222172.000000 6471.229980 970.395996 8834.980469 4816.839844 2376.629883 3605.860107
261841.000000 223537.000000 5500.740234 1189.660034 8365.730469 4016.469971 1042.270020 3821.199951
259503.000000 225840.000000 3827.929932 3088.840088 7676.140137 3978.310059 -357.006989 3016.419922
253457.000000 224636.000000 4914.609863 3097.449951 8224.900391 4321.439941 171.373993 2412.360107
256029.000000 222221.000000 6841.799805 1028.500000 9252.299805 4387.569824 2418.139893 2510.100098
262840.000000 222550.000000 6210.250000 1410.729980 8538.900391 4152.580078 3009.300049 3219.760010
261633.000000 225065.000000 4284.529785 3357.209961 7282.169922 3823.590088 1402.839966 3644.669922
254591.000000 225109.000000 4693.160156 3647.739990 7745.160156 3686.379883 490.161011 3448.860107
254780.000000 223599.000000 6527.379883 1569.869995 9438.429688 3456.580078 1162.520020 3252.010010
260639.000000 224107.000000 6531.049805 1633.050049 9283.719727 4174.020020 2089.550049 2775.750000
261108.000000 225472.000000 4968.259766 3527.850098 7692.870117 5137.100098 2207.389893 2436.659912
255775.000000 223708.000000 4963.450195 4017.370117 7701.419922 5269.649902 2284.399902 2842.080078
257398.000000 220947.000000 6767.500000 1645.709961 9107.070312 4000.179932 2548.860107 3624.770020
264924.000000 221559.000000 6471.459961 1110.329956 9459.650391 3108.169922 1696.969971 3893.439941
265339.000000 225733.000000 4348.799805 3459.510010 8475.299805 4031.239990 573.346985 2910.270020
256814.000000 226995.000000 3479.540039 4949.790039 7499.910156 5624.709961 751.656006 2347.709961
253316.000000 225161.000000 5147.060059 3218.429932 8460.160156 5869.299805 2336.320068 2987.959961
259360.000000 223101.000000 5549.120117 1869.949951 8740.759766 4668.939941 2457.909912 3758.820068
262012.000000 224016.000000 4173.609863 3004.129883 8157.040039 3704.729980 987.963989 3652.750000
257176.000000 224420.000000 3517.300049 4118.750000 7822.240234 3718.229980 37.264900 2953.679932
255146.000000 223322.000000 4923.979980 2330.679932 9095.910156 3792.399902 1013.070007 2711.239990
260524.000000 223651.000000 5413.629883 1146.209961 8817.169922 4419.649902 2446.649902 2832.050049
262098.000000 225752.000000 4262.979980 2270.969971 7135.479980 5067.120117 2294.679932 3376.620117
256889.000000 225379.000000 3606.459961 3568.189941 6552.649902 4970.270020 1516.380005 3662.570068
253948.000000 222631.000000 5511.700195 2066.300049 7952.660156 4019.909912 1513.140015 3752.629883
259799.000000 222067.000000 5873.500000 608.583984 9253.780273 2870.739990 1348.239990 3344.199951
262547.000000 224901.000000 4346.080078 1928.099976 8590.969727 3455.459961 904.390991 2379.270020
256137.000000 226761.000000 3423.560059 3379.080078 7471.149902 4894.169922 1153.540039 2031.410034
250326.000000 225013.000000 5519.979980 2423.969971 7991.759766 5117.950195 2098.790039 3099.239990
255454.000000 222992.000000 6547.950195 496.496002 8751.339844 3900.560059 2132.290039 4076.810059
261286.000000 223489.000000 5152.850098 1501.510010 8425.610352 2888.030029 776.114014 3786.360107
258969.000000 224069.000000 3832.610107 3001.979980 7979.259766 3182.310059 52.716000 2874.800049
254946.000000 222035.000000 5317.879883 2139.800049 9103.139648 3955.610107 1235.170044 2394.149902
258676.000000 221205.000000 6594.910156 505.343994 9423.360352 4562.470215 2913.739990 2892.350098
262125.000000 223566.000000 5116.750000 1773.599976 8082.200195 4776.370117 2386.389893 3659.729980
257835.000000 225918.000000 3714.300049 3477.080078 7205.370117 4554.609863 711.539001 3878.419922
253660.000000 224371.000000 5022.450195 2592.429932 8277.200195 4119.370117 486.507996 3666.739990
259503.000000 222061.000000 6589.950195 659.935974 9596.919922 3598.100098 1702.489990 3036.600098
265495.000000 222843.000000 5541.850098 1728.430054 8459.959961 4492.000000 2231.969971 2430.620117
260929.000000 224996.000000 4000.949951 3745.989990 6983.790039 5430.859863 1855.260010 2533.379883
252716.000000 224335.000000 5086.560059 3401.149902 7597.970215 5196.120117 1755.719971 3079.760010
254110.000000 223111.000000 6822.189941 1229.079956 9164.339844 3761.229980 1679.390015 3584.879883
259969.000000 224693.000000 6183.950195 1538.500000 9222.080078 3139.169922 949.901978 3180.800049
259078.000000 226913.000000 4388.890137 3694.820068 8195.019531 3933.000000 426.079987 2388.449951
254563.000000 224760.000000 5168.439941 4020.939941 8450.269531 4758.910156 1458.900024 2286.429932
258059.000000 221217.000000 6883.459961 1649.530029 9232.780273 4457.649902 3057.820068 3031.949951
264667.000000 221177.000000 6218.509766 1645.729980 8657.179688 3663.500000 2528.280029 3978.340088
262925.000000 224382.000000 4627.500000 3635.929932 7892.799805 3431.320068 604.508972 3901.370117
254708.000000 225448.000000 4408.250000 4461.040039 8197.169922 3953.750000 -44.534599 3154.870117
253702.000000 224635.000000 5825.770020 2577.050049 9590.049805 4569.250000 1460.270020 2785.169922
260206.000000 224140.000000 5387.979980 1951.160034 8789.509766 5131.660156 2706.379883 2972.479980
261240.000000 224737.000000 3860.810059 3418.310059 7414.529785 5284.520020 2271.379883 3183.149902
256140.000000 223252.000000 3850.010010 3957.139893 7262.649902 4964.640137 1499.510010 3453.129883
256116.000000 221349.000000 5594.479980 2054.399902 8835.129883 3662.010010 1485.510010 3613.010010
2.517740e+05 2.242410e+05 5.688100e+03 1.915530e+03 9.329220e+03 4.183710e+03 1.212350e+03 2.641790e+03
2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03
2.576140e+05 2.233230e+05 5.003660e+03 3.525140e+03 7.165310e+03 4.685620e+03 1.715380e+03 3.440480e+03
2.557800e+05 2.219150e+05 6.357310e+03 2.145290e+03 8.426970e+03 3.775350e+03 1.475390e+03 3.797240e+03
2.601660e+05 2.230080e+05 6.702590e+03 1.484960e+03 9.288100e+03 3.330830e+03 1.228500e+03 3.214320e+03
2.612310e+05 2.264260e+05 4.980060e+03 2.982380e+03 8.499630e+03 4.267670e+03 9.940890e+02 2.292890e+03
2.551170e+05 2.266420e+05 4.584410e+03 4.656440e+03 7.860150e+03 5.317310e+03 1.473600e+03 2.111690e+03
2.533000e+05 2.235540e+05 6.455090e+03 3.036650e+03 8.869750e+03 4.986310e+03 2.607360e+03 2.839590e+03
2.610610e+05 2.212630e+05 6.951980e+03 1.500240e+03 9.386100e+03 3.791680e+03 2.677010e+03 3.980630e+03
2.665030e+05 2.231980e+05 5.189610e+03 2.594560e+03 8.571530e+03 3.175000e+03 9.198400e+02 3.792010e+03
2.606920e+05 2.251840e+05 3.782480e+03 4.642880e+03 7.662960e+03 3.917790e+03 -2.510970e+02 2.907060e+03
2.539630e+05 2.250810e+05 5.123530e+03 3.839550e+03 8.669030e+03 4.877820e+03 9.437240e+02 2.527450e+03
2.565550e+05 2.241690e+05 5.930600e+03 2.298540e+03 8.906710e+03 5.331680e+03 2.549910e+03 3.053560e+03
2.608890e+05 2.250100e+05 4.681130e+03 2.971870e+03 7.900040e+03 4.874080e+03 2.322430e+03 3.649120e+03
2.579440e+05 2.249230e+05 3.291140e+03 4.357090e+03 7.131590e+03 4.385560e+03 1.077050e+03 3.664040e+03
2.550090e+05 2.230180e+05 4.584820e+03 2.864000e+03 8.469490e+03 3.625580e+03 9.855570e+02 3.504230e+03
2.601140e+05 2.219470e+05 5.676190e+03 1.210340e+03 9.393780e+03 3.390240e+03 1.654020e+03 3.018700e+03
2.642770e+05 2.244380e+05 4.446620e+03 2.176720e+03 8.142090e+03 4.584880e+03 2.327830e+03 2.615800e+03
2.592210e+05 2.264710e+05 2.734440e+03 4.182760e+03 6.389550e+03 5.540520e+03 1.958880e+03 2.720120e+03
2.526500e+05 2.248310e+05 4.163640e+03 2.989990e+03 7.179200e+03 5.213060e+03 1.929550e+03 3.457660e+03
2.570830e+05 2.220480e+05 5.759040e+03 7.024410e+02 8.566550e+03 3.552020e+03 1.832940e+03 3.956190e+03
2.631300e+05 2.229670e+05 5.141140e+03 1.166120e+03 8.666960e+03 2.720370e+03 9.713740e+02 3.479730e+03
2.602360e+05 2.252650e+05 3.425140e+03 3.339080e+03 7.853610e+03 3.674950e+03 5.259080e+02 2.443310e+03
2.535030e+05 2.245270e+05 4.398130e+03 2.927430e+03 8.110280e+03 4.842470e+03 1.513870e+03 2.467100e+03
2.561260e+05 2.226930e+05 6.043530e+03 6.562240e+02 8.797560e+03 4.832410e+03 2.832370e+03 3.426140e+03
2.616770e+05 2.236080e+05 5.830460e+03 1.033910e+03 8.123940e+03 3.980690e+03 1.927960e+03 4.092720e+03
2.594570e+05 2.255360e+05 4.015570e+03 2.995990e+03 7.135440e+03 3.713550e+03 3.072200e+02 3.849430e+03
2.533520e+05 2.242160e+05 4.650560e+03 3.196620e+03 8.131280e+03 3.586160e+03 7.083230e+01 3.074180e+03
2.561240e+05 2.215130e+05 6.100480e+03 8.219800e+02 9.757540e+03 3.474510e+03 1.647520e+03 2.559860e+03
2.630240e+05 2.215590e+05 5.789960e+03 6.994170e+02 9.129740e+03 4.153080e+03 2.829250e+03 2.677270e+03
2.617200e+05 2.240150e+05 4.358500e+03 2.645360e+03 7.414110e+03 4.810670e+03 2.225990e+03 3.185990e+03
2.547560e+05 2.242400e+05 4.857380e+03 3.229680e+03 7.539310e+03 4.769140e+03 1.507130e+03 3.668260e+03
2.568890e+05 2.226580e+05 6.473420e+03 1.214110e+03 9.010760e+03 3.848730e+03 1.303840e+03 3.778500e+03
2.642080e+05 2.233160e+05 5.700450e+03 1.116560e+03 9.087610e+03 3.846680e+03 1.293590e+03 2.891560e+03
2.633100e+05 2.257190e+05 3.936120e+03 3.252360e+03 7.552850e+03 4.897860e+03 1.156630e+03 2.037160e+03
2.550790e+05 2.250860e+05 4.536450e+03 3.960110e+03 7.454590e+03 5.479070e+03 1.596360e+03 2.190800e+03
2.544870e+05 2.225080e+05 6.635860e+03 1.758850e+03 8.732970e+03 4.466970e+03 2.650360e+03 3.139310e+03
2.612410e+05 2.224320e+05 6.702270e+03 1.085130e+03 8.989230e+03 3.112990e+03 1.933560e+03 3.828410e+03
2.621190e+05 2.255870e+05 4.714950e+03 2.892360e+03 8.107820e+03 2.961310e+03 2.399780e+02 3.273720e+03
2.549990e+05 2.265140e+05 4.532090e+03 4.126900e+03 8.200130e+03 3.872590e+03 5.608900e+01 2.370580e+03
2.542890e+05 2.240330e+05 6.538810e+03 2.251440e+03 9.419430e+03 4.564450e+03 2.077810e+03 2.508170e+03
2.618900e+05 2.219600e+05 6.846090e+03 1.475270e+03 9.125590e+03 4.598290e+03 3.299220e+03 3.475420e+03
2.645020e+05 2.230850e+05 5.066380e+03 3.270560e+03 7.933170e+03 4.173710e+03 1.908910e+03 3.867460e+03
2.578890e+05 2.236560e+05 4.201660e+03 4.473640e+03 7.688340e+03 4.161580e+03 6.875790e+02 3.653690e+03
2.542700e+05 2.231510e+05 5.715140e+03 2.752140e+03 9.273320e+03 3.772950e+03 8.964040e+02 3.256060e+03
2.582570e+05 2.242170e+05 6.114310e+03 1.856860e+03 9.604320e+03 4.200490e+03 1.764380e+03 2.939220e+03
2.600200e+05 2.268680e+05 4.237530e+03 3.605880e+03 8.066220e+03 5.430250e+03 2.138580e+03 2.696710e+03
2.550830e+05 2.259240e+05 3.350310e+03 4.853070e+03 7.045820e+03 5.925200e+03 1.893610e+03 2.897340e+03
2.544530e+05 2.221270e+05 5.271330e+03 2.491500e+03 8.436680e+03 5.032080e+03 2.436050e+03 3.724590e+03
2.625880e+05 2.199500e+05 5.994620e+03 7.892740e+02 9.029650e+03 3.515740e+03 1.953570e+03 4.014520e+03
2.656100e+05 2.233330e+05 4.391410e+03 2.400960e+03 8.146460e+03 3.536960e+03 5.302320e+02 3.133920e+03
2.574700e+05 2.269770e+05 2.975320e+03 4.633530e+03 7.278560e+03 4.640100e+03 -5.015020e+01 2.024960e+03
2.506870e+05 2.263310e+05 4.517860e+03 3.183800e+03 8.072600e+03 5.281660e+03 1.605140e+03 2.335140e+03
2.555630e+05 2.244950e+05 5.551000e+03 1.101300e+03 8.461490e+03 4.725700e+03 2.726670e+03 3.480540e+03
2.613350e+05 2.246450e+05 4.764680e+03 1.557020e+03 7.833350e+03 3.524810e+03 1.577410e+03 4.038620e+03
2.602690e+05 2.240080e+05 3.558030e+03 2.987610e+03 7.362440e+03 3.279230e+03 5.624420e+02 3.786550e+03
2.574350e+05 2.217770e+05 4.972600e+03 2.166880e+03 8.481440e+03 3.328720e+03 1.037130e+03 3.271370e+03
2.610460e+05 2.215500e+05 5.816180e+03 5.902170e+02 9.120930e+03 3.895400e+03 2.382670e+03 2.824170e+03
2.627660e+05 2.244730e+05 4.835050e+03 1.785770e+03 7.880760e+03 4.745620e+03 2.443660e+03 3.229550e+03
2.565090e+05 2.264130e+05 3.758870e+03 3.461200e+03 6.743770e+03 4.928960e+03 1.536620e+03 3.546690e+03
2.507930e+05 2.243720e+05 5.218490e+03 2.865260e+03 7.803960e+03 4.351090e+03 1.333820e+03 3.680490e+03
2.563190e+05 2.220660e+05 6.403970e+03 7.323450e+02 9.627760e+03 3.089300e+03 1.516780e+03 3.653690e+03
2.633430e+05 2.232350e+05 5.200430e+03 1.388580e+03 9.372850e+03 3.371230e+03 1.450390e+03 2.678910e+03
2.609030e+05 2.251100e+05 3.722580e+03 3.246660e+03 7.876540e+03 4.716810e+03 1.498440e+03 2.116520e+03
2.544160e+05 2.237690e+05 4.841650e+03 2.956400e+03 8.115920e+03 5.392360e+03 2.142810e+03 2.652320e+03
2.566980e+05 2.221720e+05 6.471230e+03 9.703960e+02 8.834980e+03 4.816840e+03 2.376630e+03 3.605860e+03
2.618410e+05 2.235370e+05 5.500740e+03 1.189660e+03 8.365730e+03 4.016470e+03 1.042270e+03 3.821200e+03
2.595030e+05 2.258400e+05 3.827930e+03 3.088840e+03 7.676140e+03 3.978310e+03 -3.570070e+02 3.016420e+03
2.534570e+05 2.246360e+05 4.914610e+03 3.097450e+03 8.224900e+03 4.321440e+03 1.713740e+02 2.412360e+03
2.560290e+05 2.222210e+05 6.841800e+03 1.028500e+03 9.252300e+03 4.387570e+03 2.418140e+03 2.510100e+03
2.628400e+05 2.225500e+05 6.210250e+03 1.410730e+03 8.538900e+03 4.152580e+03 3.009300e+03 3.219760e+03
2.616330e+05 2.250650e+05 4.284530e+03 3.357210e+03 7.282170e+03 3.823590e+03 1.402840e+03 3.644670e+03
2.545910e+05 2.251090e+05 4.693160e+03 3.647740e+03 7.745160e+03 3.686380e+03 4.901610e+02 3.448860e+03
2.547800e+05 2.235990e+05 6.527380e+03 1.569870e+03 9.438430e+03 3.456580e+03 1.162520e+03 3.252010e+03
2.606390e+05 2.241070e+05 6.531050e+03 1.633050e+03 9.283720e+03 4.174020e+03 2.089550e+03 2.775750e+03
2.611080e+05 2.254720e+05 4.968260e+03 3.527850e+03 7.692870e+03 5.137100e+03 2.207390e+03 2.436660e+03
2.557750e+05 2.237080e+05 4.963450e+03 4.017370e+03 7.701420e+03 5.269650e+03 2.284400e+03 2.842080e+03
2.573980e+05 2.209470e+05 6.767500e+03 1.645710e+03 9.107070e+03 4.000180e+03 2.548860e+03 3.624770e+03
2.649240e+05 2.215590e+05 6.471460e+03 1.110330e+03 9.459650e+03 3.108170e+03 1.696970e+03 3.893440e+03
2.653390e+05 2.257330e+05 4.348800e+03 3.459510e+03 8.475300e+03 4.031240e+03 5.733470e+02 2.910270e+03
2.568140e+05 2.269950e+05 3.479540e+03 4.949790e+03 7.499910e+03 5.624710e+03 7.516560e+02 2.347710e+03
2.533160e+05 2.251610e+05 5.147060e+03 3.218430e+03 8.460160e+03 5.869300e+03 2.336320e+03 2.987960e+03
2.593600e+05 2.231010e+05 5.549120e+03 1.869950e+03 8.740760e+03 4.668940e+03 2.457910e+03 3.758820e+03
2.620120e+05 2.240160e+05 4.173610e+03 3.004130e+03 8.157040e+03 3.704730e+03 9.879640e+02 3.652750e+03
2.571760e+05 2.244200e+05 3.517300e+03 4.118750e+03 7.822240e+03 3.718230e+03 3.726490e+01 2.953680e+03
2.551460e+05 2.233220e+05 4.923980e+03 2.330680e+03 9.095910e+03 3.792400e+03 1.013070e+03 2.711240e+03
2.605240e+05 2.236510e+05 5.413630e+03 1.146210e+03 8.817170e+03 4.419650e+03 2.446650e+03 2.832050e+03
2.620980e+05 2.257520e+05 4.262980e+03 2.270970e+03 7.135480e+03 5.067120e+03 2.294680e+03 3.376620e+03
2.568890e+05 2.253790e+05 3.606460e+03 3.568190e+03 6.552650e+03 4.970270e+03 1.516380e+03 3.662570e+03
2.539480e+05 2.226310e+05 5.511700e+03 2.066300e+03 7.952660e+03 4.019910e+03 1.513140e+03 3.752630e+03
2.597990e+05 2.220670e+05 5.873500e+03 6.085840e+02 9.253780e+03 2.870740e+03 1.348240e+03 3.344200e+03
2.625470e+05 2.249010e+05 4.346080e+03 1.928100e+03 8.590970e+03 3.455460e+03 9.043910e+02 2.379270e+03
2.561370e+05 2.267610e+05 3.423560e+03 3.379080e+03 7.471150e+03 4.894170e+03 1.153540e+03 2.031410e+03
2.503260e+05 2.250130e+05 5.519980e+03 2.423970e+03 7.991760e+03 5.117950e+03 2.098790e+03 3.099240e+03
2.554540e+05 2.229920e+05 6.547950e+03 4.964960e+02 8.751340e+03 3.900560e+03 2.132290e+03 4.076810e+03
2.612860e+05 2.234890e+05 5.152850e+03 1.501510e+03 8.425610e+03 2.888030e+03 7.761140e+02 3.786360e+03
2.589690e+05 2.240690e+05 3.832610e+03 3.001980e+03 7.979260e+03 3.182310e+03 5.271600e+01 2.874800e+03
2.549460e+05 2.220350e+05 5.317880e+03 2.139800e+03 9.103140e+03 3.955610e+03 1.235170e+03 2.394150e+03
2.586760e+05 2.212050e+05 6.594910e+03 5.053440e+02 9.423360e+03 4.562470e+03 2.913740e+03 2.892350e+03
2.621250e+05 2.235660e+05 5.116750e+03 1.773600e+03 8.082200e+03 4.776370e+03 2.386390e+03 3.659730e+03
2.578350e+05 2.259180e+05 3.714300e+03 3.477080e+03 7.205370e+03 4.554610e+03 7.115390e+02 3.878420e+03
2.536600e+05 2.243710e+05 5.022450e+03 2.592430e+03 8.277200e+03 4.119370e+03 4.865080e+02 3.666740e+03
2.595030e+05 2.220610e+05 6.589950e+03 6.599360e+02 9.596920e+03 3.598100e+03 1.702490e+03 3.036600e+03
2.654950e+05 2.228430e+05 5.541850e+03 1.728430e+03 8.459960e+03 4.492000e+03 2.231970e+03 2.430620e+03
2.609290e+05 2.249960e+05 4.000950e+03 3.745990e+03 6.983790e+03 5.430860e+03 1.855260e+03 2.533380e+03
2.527160e+05 2.243350e+05 5.086560e+03 3.401150e+03 7.597970e+03 5.196120e+03 1.755720e+03 3.079760e+03
2.541100e+05 2.231110e+05 6.822190e+03 1.229080e+03 9.164340e+03 3.761230e+03 1.679390e+03 3.584880e+03
2.599690e+05 2.246930e+05 6.183950e+03 1.538500e+03 9.222080e+03 3.139170e+03 9.499020e+02 3.180800e+03
2.590780e+05 2.269130e+05 4.388890e+03 3.694820e+03 8.195020e+03 3.933000e+03 4.260800e+02 2.388450e+03
2.545630e+05 2.247600e+05 5.168440e+03 4.020940e+03 8.450270e+03 4.758910e+03 1.458900e+03 2.286430e+03
2.580590e+05 2.212170e+05 6.883460e+03 1.649530e+03 9.232780e+03 4.457650e+03 3.057820e+03 3.031950e+03
2.646670e+05 2.211770e+05 6.218510e+03 1.645730e+03 8.657180e+03 3.663500e+03 2.528280e+03 3.978340e+03
2.629250e+05 2.243820e+05 4.627500e+03 3.635930e+03 7.892800e+03 3.431320e+03 6.045090e+02 3.901370e+03
2.547080e+05 2.254480e+05 4.408250e+03 4.461040e+03 8.197170e+03 3.953750e+03 -4.453460e+01 3.154870e+03
2.537020e+05 2.246350e+05 5.825770e+03 2.577050e+03 9.590050e+03 4.569250e+03 1.460270e+03 2.785170e+03
2.602060e+05 2.241400e+05 5.387980e+03 1.951160e+03 8.789510e+03 5.131660e+03 2.706380e+03 2.972480e+03
2.612400e+05 2.247370e+05 3.860810e+03 3.418310e+03 7.414530e+03 5.284520e+03 2.271380e+03 3.183150e+03
2.561400e+05 2.232520e+05 3.850010e+03 3.957140e+03 7.262650e+03 4.964640e+03 1.499510e+03 3.453130e+03
2.561160e+05 2.213490e+05 5.594480e+03 2.054400e+03 8.835130e+03 3.662010e+03 1.485510e+03 3.613010e+03

View File

@@ -1,120 +1,120 @@
251774.000000 224241.000000 5688.100098 1915.530029 9329.219727 4183.709961 1212.349976 2641.790039
259567.000000 222698.000000 6207.600098 678.671997 9380.230469 4575.580078 2830.610107 2688.629883
263073.000000 223304.000000 4961.640137 2197.120117 7687.310059 4861.859863 2732.780029 3008.540039
257614.000000 223323.000000 5003.660156 3525.139893 7165.310059 4685.620117 1715.380005 3440.479980
255780.000000 221915.000000 6357.310059 2145.290039 8426.969727 3775.350098 1475.390015 3797.239990
260166.000000 223008.000000 6702.589844 1484.959961 9288.099609 3330.830078 1228.500000 3214.320068
261231.000000 226426.000000 4980.060059 2982.379883 8499.629883 4267.669922 994.088989 2292.889893
255117.000000 226642.000000 4584.410156 4656.439941 7860.149902 5317.310059 1473.599976 2111.689941
253300.000000 223554.000000 6455.089844 3036.649902 8869.750000 4986.310059 2607.360107 2839.590088
261061.000000 221263.000000 6951.979980 1500.239990 9386.099609 3791.679932 2677.010010 3980.629883
266503.000000 223198.000000 5189.609863 2594.560059 8571.530273 3175.000000 919.840027 3792.010010
260692.000000 225184.000000 3782.479980 4642.879883 7662.959961 3917.790039 -251.097000 2907.060059
253963.000000 225081.000000 5123.529785 3839.550049 8669.030273 4877.819824 943.723999 2527.449951
256555.000000 224169.000000 5930.600098 2298.540039 8906.709961 5331.680176 2549.909912 3053.560059
260889.000000 225010.000000 4681.129883 2971.870117 7900.040039 4874.080078 2322.429932 3649.120117
257944.000000 224923.000000 3291.139893 4357.089844 7131.589844 4385.560059 1077.050049 3664.040039
255009.000000 223018.000000 4584.819824 2864.000000 8469.490234 3625.580078 985.557007 3504.229980
260114.000000 221947.000000 5676.189941 1210.339966 9393.780273 3390.239990 1654.020020 3018.699951
264277.000000 224438.000000 4446.620117 2176.719971 8142.089844 4584.879883 2327.830078 2615.800049
259221.000000 226471.000000 2734.439941 4182.759766 6389.549805 5540.520020 1958.880005 2720.120117
252650.000000 224831.000000 4163.640137 2989.989990 7179.200195 5213.060059 1929.550049 3457.659912
257083.000000 222048.000000 5759.040039 702.440979 8566.549805 3552.020020 1832.939941 3956.189941
263130.000000 222967.000000 5141.140137 1166.119995 8666.959961 2720.370117 971.374023 3479.729980
260236.000000 225265.000000 3425.139893 3339.080078 7853.609863 3674.949951 525.908020 2443.310059
253503.000000 224527.000000 4398.129883 2927.429932 8110.279785 4842.470215 1513.869995 2467.100098
256126.000000 222693.000000 6043.529785 656.223999 8797.559570 4832.410156 2832.370117 3426.139893
261677.000000 223608.000000 5830.459961 1033.910034 8123.939941 3980.689941 1927.959961 4092.719971
259457.000000 225536.000000 4015.570068 2995.989990 7135.439941 3713.550049 307.220001 3849.429932
253352.000000 224216.000000 4650.560059 3196.620117 8131.279785 3586.159912 70.832298 3074.179932
256124.000000 221513.000000 6100.479980 821.979980 9757.540039 3474.510010 1647.520020 2559.860107
263024.000000 221559.000000 5789.959961 699.416992 9129.740234 4153.080078 2829.250000 2677.270020
261720.000000 224015.000000 4358.500000 2645.360107 7414.109863 4810.669922 2225.989990 3185.989990
254756.000000 224240.000000 4857.379883 3229.679932 7539.310059 4769.140137 1507.130005 3668.260010
256889.000000 222658.000000 6473.419922 1214.109985 9010.759766 3848.729980 1303.839966 3778.500000
264208.000000 223316.000000 5700.450195 1116.560059 9087.610352 3846.679932 1293.589966 2891.560059
263310.000000 225719.000000 3936.120117 3252.360107 7552.850098 4897.859863 1156.630005 2037.160034
255079.000000 225086.000000 4536.450195 3960.110107 7454.589844 5479.069824 1596.359985 2190.800049
254487.000000 222508.000000 6635.859863 1758.849976 8732.969727 4466.970215 2650.360107 3139.310059
261241.000000 222432.000000 6702.270020 1085.130005 8989.230469 3112.989990 1933.560059 3828.409912
262119.000000 225587.000000 4714.950195 2892.360107 8107.819824 2961.310059 239.977997 3273.719971
254999.000000 226514.000000 4532.089844 4126.899902 8200.129883 3872.590088 56.089001 2370.580078
254289.000000 224033.000000 6538.810059 2251.439941 9419.429688 4564.450195 2077.810059 2508.169922
261890.000000 221960.000000 6846.089844 1475.270020 9125.589844 4598.290039 3299.219971 3475.419922
264502.000000 223085.000000 5066.379883 3270.560059 7933.169922 4173.709961 1908.910034 3867.459961
257889.000000 223656.000000 4201.660156 4473.640137 7688.339844 4161.580078 687.578979 3653.689941
254270.000000 223151.000000 5715.140137 2752.139893 9273.320312 3772.949951 896.403992 3256.060059
258257.000000 224217.000000 6114.310059 1856.859985 9604.320312 4200.490234 1764.380005 2939.219971
260020.000000 226868.000000 4237.529785 3605.879883 8066.220215 5430.250000 2138.580078 2696.709961
255083.000000 225924.000000 3350.310059 4853.069824 7045.819824 5925.200195 1893.609985 2897.340088
254453.000000 222127.000000 5271.330078 2491.500000 8436.679688 5032.080078 2436.050049 3724.590088
262588.000000 219950.000000 5994.620117 789.273987 9029.650391 3515.739990 1953.569946 4014.520020
265610.000000 223333.000000 4391.410156 2400.959961 8146.459961 3536.959961 530.231995 3133.919922
257470.000000 226977.000000 2975.320068 4633.529785 7278.560059 4640.100098 -50.150200 2024.959961
250687.000000 226331.000000 4517.859863 3183.800049 8072.600098 5281.660156 1605.140015 2335.139893
255563.000000 224495.000000 5551.000000 1101.300049 8461.490234 4725.700195 2726.669922 3480.540039
261335.000000 224645.000000 4764.680176 1557.020020 7833.350098 3524.810059 1577.410034 4038.620117
260269.000000 224008.000000 3558.030029 2987.610107 7362.439941 3279.229980 562.442017 3786.550049
257435.000000 221777.000000 4972.600098 2166.879883 8481.440430 3328.719971 1037.130005 3271.370117
261046.000000 221550.000000 5816.180176 590.216980 9120.929688 3895.399902 2382.669922 2824.169922
262766.000000 224473.000000 4835.049805 1785.770020 7880.759766 4745.620117 2443.659912 3229.550049
256509.000000 226413.000000 3758.870117 3461.199951 6743.770020 4928.959961 1536.619995 3546.689941
250793.000000 224372.000000 5218.490234 2865.260010 7803.959961 4351.089844 1333.819946 3680.489990
256319.000000 222066.000000 6403.970215 732.344971 9627.759766 3089.300049 1516.780029 3653.689941
263343.000000 223235.000000 5200.430176 1388.579956 9372.849609 3371.229980 1450.390015 2678.909912
260903.000000 225110.000000 3722.580078 3246.659912 7876.540039 4716.810059 1498.439941 2116.520020
254416.000000 223769.000000 4841.649902 2956.399902 8115.919922 5392.359863 2142.810059 2652.320068
256698.000000 222172.000000 6471.229980 970.395996 8834.980469 4816.839844 2376.629883 3605.860107
261841.000000 223537.000000 5500.740234 1189.660034 8365.730469 4016.469971 1042.270020 3821.199951
259503.000000 225840.000000 3827.929932 3088.840088 7676.140137 3978.310059 -357.006989 3016.419922
253457.000000 224636.000000 4914.609863 3097.449951 8224.900391 4321.439941 171.373993 2412.360107
256029.000000 222221.000000 6841.799805 1028.500000 9252.299805 4387.569824 2418.139893 2510.100098
262840.000000 222550.000000 6210.250000 1410.729980 8538.900391 4152.580078 3009.300049 3219.760010
261633.000000 225065.000000 4284.529785 3357.209961 7282.169922 3823.590088 1402.839966 3644.669922
254591.000000 225109.000000 4693.160156 3647.739990 7745.160156 3686.379883 490.161011 3448.860107
254780.000000 223599.000000 6527.379883 1569.869995 9438.429688 3456.580078 1162.520020 3252.010010
260639.000000 224107.000000 6531.049805 1633.050049 9283.719727 4174.020020 2089.550049 2775.750000
261108.000000 225472.000000 4968.259766 3527.850098 7692.870117 5137.100098 2207.389893 2436.659912
255775.000000 223708.000000 4963.450195 4017.370117 7701.419922 5269.649902 2284.399902 2842.080078
257398.000000 220947.000000 6767.500000 1645.709961 9107.070312 4000.179932 2548.860107 3624.770020
264924.000000 221559.000000 6471.459961 1110.329956 9459.650391 3108.169922 1696.969971 3893.439941
265339.000000 225733.000000 4348.799805 3459.510010 8475.299805 4031.239990 573.346985 2910.270020
256814.000000 226995.000000 3479.540039 4949.790039 7499.910156 5624.709961 751.656006 2347.709961
253316.000000 225161.000000 5147.060059 3218.429932 8460.160156 5869.299805 2336.320068 2987.959961
259360.000000 223101.000000 5549.120117 1869.949951 8740.759766 4668.939941 2457.909912 3758.820068
262012.000000 224016.000000 4173.609863 3004.129883 8157.040039 3704.729980 987.963989 3652.750000
257176.000000 224420.000000 3517.300049 4118.750000 7822.240234 3718.229980 37.264900 2953.679932
255146.000000 223322.000000 4923.979980 2330.679932 9095.910156 3792.399902 1013.070007 2711.239990
260524.000000 223651.000000 5413.629883 1146.209961 8817.169922 4419.649902 2446.649902 2832.050049
262098.000000 225752.000000 4262.979980 2270.969971 7135.479980 5067.120117 2294.679932 3376.620117
256889.000000 225379.000000 3606.459961 3568.189941 6552.649902 4970.270020 1516.380005 3662.570068
253948.000000 222631.000000 5511.700195 2066.300049 7952.660156 4019.909912 1513.140015 3752.629883
259799.000000 222067.000000 5873.500000 608.583984 9253.780273 2870.739990 1348.239990 3344.199951
262547.000000 224901.000000 4346.080078 1928.099976 8590.969727 3455.459961 904.390991 2379.270020
256137.000000 226761.000000 3423.560059 3379.080078 7471.149902 4894.169922 1153.540039 2031.410034
250326.000000 225013.000000 5519.979980 2423.969971 7991.759766 5117.950195 2098.790039 3099.239990
255454.000000 222992.000000 6547.950195 496.496002 8751.339844 3900.560059 2132.290039 4076.810059
261286.000000 223489.000000 5152.850098 1501.510010 8425.610352 2888.030029 776.114014 3786.360107
258969.000000 224069.000000 3832.610107 3001.979980 7979.259766 3182.310059 52.716000 2874.800049
254946.000000 222035.000000 5317.879883 2139.800049 9103.139648 3955.610107 1235.170044 2394.149902
258676.000000 221205.000000 6594.910156 505.343994 9423.360352 4562.470215 2913.739990 2892.350098
262125.000000 223566.000000 5116.750000 1773.599976 8082.200195 4776.370117 2386.389893 3659.729980
257835.000000 225918.000000 3714.300049 3477.080078 7205.370117 4554.609863 711.539001 3878.419922
253660.000000 224371.000000 5022.450195 2592.429932 8277.200195 4119.370117 486.507996 3666.739990
259503.000000 222061.000000 6589.950195 659.935974 9596.919922 3598.100098 1702.489990 3036.600098
265495.000000 222843.000000 5541.850098 1728.430054 8459.959961 4492.000000 2231.969971 2430.620117
260929.000000 224996.000000 4000.949951 3745.989990 6983.790039 5430.859863 1855.260010 2533.379883
252716.000000 224335.000000 5086.560059 3401.149902 7597.970215 5196.120117 1755.719971 3079.760010
254110.000000 223111.000000 6822.189941 1229.079956 9164.339844 3761.229980 1679.390015 3584.879883
259969.000000 224693.000000 6183.950195 1538.500000 9222.080078 3139.169922 949.901978 3180.800049
259078.000000 226913.000000 4388.890137 3694.820068 8195.019531 3933.000000 426.079987 2388.449951
254563.000000 224760.000000 5168.439941 4020.939941 8450.269531 4758.910156 1458.900024 2286.429932
258059.000000 221217.000000 6883.459961 1649.530029 9232.780273 4457.649902 3057.820068 3031.949951
264667.000000 221177.000000 6218.509766 1645.729980 8657.179688 3663.500000 2528.280029 3978.340088
262925.000000 224382.000000 4627.500000 3635.929932 7892.799805 3431.320068 604.508972 3901.370117
254708.000000 225448.000000 4408.250000 4461.040039 8197.169922 3953.750000 -44.534599 3154.870117
253702.000000 224635.000000 5825.770020 2577.050049 9590.049805 4569.250000 1460.270020 2785.169922
260206.000000 224140.000000 5387.979980 1951.160034 8789.509766 5131.660156 2706.379883 2972.479980
261240.000000 224737.000000 3860.810059 3418.310059 7414.529785 5284.520020 2271.379883 3183.149902
256140.000000 223252.000000 3850.010010 3957.139893 7262.649902 4964.640137 1499.510010 3453.129883
256116.000000 221349.000000 5594.479980 2054.399902 8835.129883 3662.010010 1485.510010 3613.010010
2.517740e+05 2.242410e+05 5.688100e+03 1.915530e+03 9.329220e+03 4.183710e+03 1.212350e+03 2.641790e+03
2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03
2.576140e+05 2.233230e+05 5.003660e+03 3.525140e+03 7.165310e+03 4.685620e+03 1.715380e+03 3.440480e+03
2.557800e+05 2.219150e+05 6.357310e+03 2.145290e+03 8.426970e+03 3.775350e+03 1.475390e+03 3.797240e+03
2.601660e+05 2.230080e+05 6.702590e+03 1.484960e+03 9.288100e+03 3.330830e+03 1.228500e+03 3.214320e+03
2.612310e+05 2.264260e+05 4.980060e+03 2.982380e+03 8.499630e+03 4.267670e+03 9.940890e+02 2.292890e+03
2.551170e+05 2.266420e+05 4.584410e+03 4.656440e+03 7.860150e+03 5.317310e+03 1.473600e+03 2.111690e+03
2.533000e+05 2.235540e+05 6.455090e+03 3.036650e+03 8.869750e+03 4.986310e+03 2.607360e+03 2.839590e+03
2.610610e+05 2.212630e+05 6.951980e+03 1.500240e+03 9.386100e+03 3.791680e+03 2.677010e+03 3.980630e+03
2.665030e+05 2.231980e+05 5.189610e+03 2.594560e+03 8.571530e+03 3.175000e+03 9.198400e+02 3.792010e+03
2.606920e+05 2.251840e+05 3.782480e+03 4.642880e+03 7.662960e+03 3.917790e+03 -2.510970e+02 2.907060e+03
2.539630e+05 2.250810e+05 5.123530e+03 3.839550e+03 8.669030e+03 4.877820e+03 9.437240e+02 2.527450e+03
2.565550e+05 2.241690e+05 5.930600e+03 2.298540e+03 8.906710e+03 5.331680e+03 2.549910e+03 3.053560e+03
2.608890e+05 2.250100e+05 4.681130e+03 2.971870e+03 7.900040e+03 4.874080e+03 2.322430e+03 3.649120e+03
2.579440e+05 2.249230e+05 3.291140e+03 4.357090e+03 7.131590e+03 4.385560e+03 1.077050e+03 3.664040e+03
2.550090e+05 2.230180e+05 4.584820e+03 2.864000e+03 8.469490e+03 3.625580e+03 9.855570e+02 3.504230e+03
2.601140e+05 2.219470e+05 5.676190e+03 1.210340e+03 9.393780e+03 3.390240e+03 1.654020e+03 3.018700e+03
2.642770e+05 2.244380e+05 4.446620e+03 2.176720e+03 8.142090e+03 4.584880e+03 2.327830e+03 2.615800e+03
2.592210e+05 2.264710e+05 2.734440e+03 4.182760e+03 6.389550e+03 5.540520e+03 1.958880e+03 2.720120e+03
2.526500e+05 2.248310e+05 4.163640e+03 2.989990e+03 7.179200e+03 5.213060e+03 1.929550e+03 3.457660e+03
2.570830e+05 2.220480e+05 5.759040e+03 7.024410e+02 8.566550e+03 3.552020e+03 1.832940e+03 3.956190e+03
2.631300e+05 2.229670e+05 5.141140e+03 1.166120e+03 8.666960e+03 2.720370e+03 9.713740e+02 3.479730e+03
2.602360e+05 2.252650e+05 3.425140e+03 3.339080e+03 7.853610e+03 3.674950e+03 5.259080e+02 2.443310e+03
2.535030e+05 2.245270e+05 4.398130e+03 2.927430e+03 8.110280e+03 4.842470e+03 1.513870e+03 2.467100e+03
2.561260e+05 2.226930e+05 6.043530e+03 6.562240e+02 8.797560e+03 4.832410e+03 2.832370e+03 3.426140e+03
2.616770e+05 2.236080e+05 5.830460e+03 1.033910e+03 8.123940e+03 3.980690e+03 1.927960e+03 4.092720e+03
2.594570e+05 2.255360e+05 4.015570e+03 2.995990e+03 7.135440e+03 3.713550e+03 3.072200e+02 3.849430e+03
2.533520e+05 2.242160e+05 4.650560e+03 3.196620e+03 8.131280e+03 3.586160e+03 7.083230e+01 3.074180e+03
2.561240e+05 2.215130e+05 6.100480e+03 8.219800e+02 9.757540e+03 3.474510e+03 1.647520e+03 2.559860e+03
2.630240e+05 2.215590e+05 5.789960e+03 6.994170e+02 9.129740e+03 4.153080e+03 2.829250e+03 2.677270e+03
2.617200e+05 2.240150e+05 4.358500e+03 2.645360e+03 7.414110e+03 4.810670e+03 2.225990e+03 3.185990e+03
2.547560e+05 2.242400e+05 4.857380e+03 3.229680e+03 7.539310e+03 4.769140e+03 1.507130e+03 3.668260e+03
2.568890e+05 2.226580e+05 6.473420e+03 1.214110e+03 9.010760e+03 3.848730e+03 1.303840e+03 3.778500e+03
2.642080e+05 2.233160e+05 5.700450e+03 1.116560e+03 9.087610e+03 3.846680e+03 1.293590e+03 2.891560e+03
2.633100e+05 2.257190e+05 3.936120e+03 3.252360e+03 7.552850e+03 4.897860e+03 1.156630e+03 2.037160e+03
2.550790e+05 2.250860e+05 4.536450e+03 3.960110e+03 7.454590e+03 5.479070e+03 1.596360e+03 2.190800e+03
2.544870e+05 2.225080e+05 6.635860e+03 1.758850e+03 8.732970e+03 4.466970e+03 2.650360e+03 3.139310e+03
2.612410e+05 2.224320e+05 6.702270e+03 1.085130e+03 8.989230e+03 3.112990e+03 1.933560e+03 3.828410e+03
2.621190e+05 2.255870e+05 4.714950e+03 2.892360e+03 8.107820e+03 2.961310e+03 2.399780e+02 3.273720e+03
2.549990e+05 2.265140e+05 4.532090e+03 4.126900e+03 8.200130e+03 3.872590e+03 5.608900e+01 2.370580e+03
2.542890e+05 2.240330e+05 6.538810e+03 2.251440e+03 9.419430e+03 4.564450e+03 2.077810e+03 2.508170e+03
2.618900e+05 2.219600e+05 6.846090e+03 1.475270e+03 9.125590e+03 4.598290e+03 3.299220e+03 3.475420e+03
2.645020e+05 2.230850e+05 5.066380e+03 3.270560e+03 7.933170e+03 4.173710e+03 1.908910e+03 3.867460e+03
2.578890e+05 2.236560e+05 4.201660e+03 4.473640e+03 7.688340e+03 4.161580e+03 6.875790e+02 3.653690e+03
2.542700e+05 2.231510e+05 5.715140e+03 2.752140e+03 9.273320e+03 3.772950e+03 8.964040e+02 3.256060e+03
2.582570e+05 2.242170e+05 6.114310e+03 1.856860e+03 9.604320e+03 4.200490e+03 1.764380e+03 2.939220e+03
2.600200e+05 2.268680e+05 4.237530e+03 3.605880e+03 8.066220e+03 5.430250e+03 2.138580e+03 2.696710e+03
2.550830e+05 2.259240e+05 3.350310e+03 4.853070e+03 7.045820e+03 5.925200e+03 1.893610e+03 2.897340e+03
2.544530e+05 2.221270e+05 5.271330e+03 2.491500e+03 8.436680e+03 5.032080e+03 2.436050e+03 3.724590e+03
2.625880e+05 2.199500e+05 5.994620e+03 7.892740e+02 9.029650e+03 3.515740e+03 1.953570e+03 4.014520e+03
2.656100e+05 2.233330e+05 4.391410e+03 2.400960e+03 8.146460e+03 3.536960e+03 5.302320e+02 3.133920e+03
2.574700e+05 2.269770e+05 2.975320e+03 4.633530e+03 7.278560e+03 4.640100e+03 -5.015020e+01 2.024960e+03
2.506870e+05 2.263310e+05 4.517860e+03 3.183800e+03 8.072600e+03 5.281660e+03 1.605140e+03 2.335140e+03
2.555630e+05 2.244950e+05 5.551000e+03 1.101300e+03 8.461490e+03 4.725700e+03 2.726670e+03 3.480540e+03
2.613350e+05 2.246450e+05 4.764680e+03 1.557020e+03 7.833350e+03 3.524810e+03 1.577410e+03 4.038620e+03
2.602690e+05 2.240080e+05 3.558030e+03 2.987610e+03 7.362440e+03 3.279230e+03 5.624420e+02 3.786550e+03
2.574350e+05 2.217770e+05 4.972600e+03 2.166880e+03 8.481440e+03 3.328720e+03 1.037130e+03 3.271370e+03
2.610460e+05 2.215500e+05 5.816180e+03 5.902170e+02 9.120930e+03 3.895400e+03 2.382670e+03 2.824170e+03
2.627660e+05 2.244730e+05 4.835050e+03 1.785770e+03 7.880760e+03 4.745620e+03 2.443660e+03 3.229550e+03
2.565090e+05 2.264130e+05 3.758870e+03 3.461200e+03 6.743770e+03 4.928960e+03 1.536620e+03 3.546690e+03
2.507930e+05 2.243720e+05 5.218490e+03 2.865260e+03 7.803960e+03 4.351090e+03 1.333820e+03 3.680490e+03
2.563190e+05 2.220660e+05 6.403970e+03 7.323450e+02 9.627760e+03 3.089300e+03 1.516780e+03 3.653690e+03
2.633430e+05 2.232350e+05 5.200430e+03 1.388580e+03 9.372850e+03 3.371230e+03 1.450390e+03 2.678910e+03
2.609030e+05 2.251100e+05 3.722580e+03 3.246660e+03 7.876540e+03 4.716810e+03 1.498440e+03 2.116520e+03
2.544160e+05 2.237690e+05 4.841650e+03 2.956400e+03 8.115920e+03 5.392360e+03 2.142810e+03 2.652320e+03
2.566980e+05 2.221720e+05 6.471230e+03 9.703960e+02 8.834980e+03 4.816840e+03 2.376630e+03 3.605860e+03
2.618410e+05 2.235370e+05 5.500740e+03 1.189660e+03 8.365730e+03 4.016470e+03 1.042270e+03 3.821200e+03
2.595030e+05 2.258400e+05 3.827930e+03 3.088840e+03 7.676140e+03 3.978310e+03 -3.570070e+02 3.016420e+03
2.534570e+05 2.246360e+05 4.914610e+03 3.097450e+03 8.224900e+03 4.321440e+03 1.713740e+02 2.412360e+03
2.560290e+05 2.222210e+05 6.841800e+03 1.028500e+03 9.252300e+03 4.387570e+03 2.418140e+03 2.510100e+03
2.628400e+05 2.225500e+05 6.210250e+03 1.410730e+03 8.538900e+03 4.152580e+03 3.009300e+03 3.219760e+03
2.616330e+05 2.250650e+05 4.284530e+03 3.357210e+03 7.282170e+03 3.823590e+03 1.402840e+03 3.644670e+03
2.545910e+05 2.251090e+05 4.693160e+03 3.647740e+03 7.745160e+03 3.686380e+03 4.901610e+02 3.448860e+03
2.547800e+05 2.235990e+05 6.527380e+03 1.569870e+03 9.438430e+03 3.456580e+03 1.162520e+03 3.252010e+03
2.606390e+05 2.241070e+05 6.531050e+03 1.633050e+03 9.283720e+03 4.174020e+03 2.089550e+03 2.775750e+03
2.611080e+05 2.254720e+05 4.968260e+03 3.527850e+03 7.692870e+03 5.137100e+03 2.207390e+03 2.436660e+03
2.557750e+05 2.237080e+05 4.963450e+03 4.017370e+03 7.701420e+03 5.269650e+03 2.284400e+03 2.842080e+03
2.573980e+05 2.209470e+05 6.767500e+03 1.645710e+03 9.107070e+03 4.000180e+03 2.548860e+03 3.624770e+03
2.649240e+05 2.215590e+05 6.471460e+03 1.110330e+03 9.459650e+03 3.108170e+03 1.696970e+03 3.893440e+03
2.653390e+05 2.257330e+05 4.348800e+03 3.459510e+03 8.475300e+03 4.031240e+03 5.733470e+02 2.910270e+03
2.568140e+05 2.269950e+05 3.479540e+03 4.949790e+03 7.499910e+03 5.624710e+03 7.516560e+02 2.347710e+03
2.533160e+05 2.251610e+05 5.147060e+03 3.218430e+03 8.460160e+03 5.869300e+03 2.336320e+03 2.987960e+03
2.593600e+05 2.231010e+05 5.549120e+03 1.869950e+03 8.740760e+03 4.668940e+03 2.457910e+03 3.758820e+03
2.620120e+05 2.240160e+05 4.173610e+03 3.004130e+03 8.157040e+03 3.704730e+03 9.879640e+02 3.652750e+03
2.571760e+05 2.244200e+05 3.517300e+03 4.118750e+03 7.822240e+03 3.718230e+03 3.726490e+01 2.953680e+03
2.551460e+05 2.233220e+05 4.923980e+03 2.330680e+03 9.095910e+03 3.792400e+03 1.013070e+03 2.711240e+03
2.605240e+05 2.236510e+05 5.413630e+03 1.146210e+03 8.817170e+03 4.419650e+03 2.446650e+03 2.832050e+03
2.620980e+05 2.257520e+05 4.262980e+03 2.270970e+03 7.135480e+03 5.067120e+03 2.294680e+03 3.376620e+03
2.568890e+05 2.253790e+05 3.606460e+03 3.568190e+03 6.552650e+03 4.970270e+03 1.516380e+03 3.662570e+03
2.539480e+05 2.226310e+05 5.511700e+03 2.066300e+03 7.952660e+03 4.019910e+03 1.513140e+03 3.752630e+03
2.597990e+05 2.220670e+05 5.873500e+03 6.085840e+02 9.253780e+03 2.870740e+03 1.348240e+03 3.344200e+03
2.625470e+05 2.249010e+05 4.346080e+03 1.928100e+03 8.590970e+03 3.455460e+03 9.043910e+02 2.379270e+03
2.561370e+05 2.267610e+05 3.423560e+03 3.379080e+03 7.471150e+03 4.894170e+03 1.153540e+03 2.031410e+03
2.503260e+05 2.250130e+05 5.519980e+03 2.423970e+03 7.991760e+03 5.117950e+03 2.098790e+03 3.099240e+03
2.554540e+05 2.229920e+05 6.547950e+03 4.964960e+02 8.751340e+03 3.900560e+03 2.132290e+03 4.076810e+03
2.612860e+05 2.234890e+05 5.152850e+03 1.501510e+03 8.425610e+03 2.888030e+03 7.761140e+02 3.786360e+03
2.589690e+05 2.240690e+05 3.832610e+03 3.001980e+03 7.979260e+03 3.182310e+03 5.271600e+01 2.874800e+03
2.549460e+05 2.220350e+05 5.317880e+03 2.139800e+03 9.103140e+03 3.955610e+03 1.235170e+03 2.394150e+03
2.586760e+05 2.212050e+05 6.594910e+03 5.053440e+02 9.423360e+03 4.562470e+03 2.913740e+03 2.892350e+03
2.621250e+05 2.235660e+05 5.116750e+03 1.773600e+03 8.082200e+03 4.776370e+03 2.386390e+03 3.659730e+03
2.578350e+05 2.259180e+05 3.714300e+03 3.477080e+03 7.205370e+03 4.554610e+03 7.115390e+02 3.878420e+03
2.536600e+05 2.243710e+05 5.022450e+03 2.592430e+03 8.277200e+03 4.119370e+03 4.865080e+02 3.666740e+03
2.595030e+05 2.220610e+05 6.589950e+03 6.599360e+02 9.596920e+03 3.598100e+03 1.702490e+03 3.036600e+03
2.654950e+05 2.228430e+05 5.541850e+03 1.728430e+03 8.459960e+03 4.492000e+03 2.231970e+03 2.430620e+03
2.609290e+05 2.249960e+05 4.000950e+03 3.745990e+03 6.983790e+03 5.430860e+03 1.855260e+03 2.533380e+03
2.527160e+05 2.243350e+05 5.086560e+03 3.401150e+03 7.597970e+03 5.196120e+03 1.755720e+03 3.079760e+03
2.541100e+05 2.231110e+05 6.822190e+03 1.229080e+03 9.164340e+03 3.761230e+03 1.679390e+03 3.584880e+03
2.599690e+05 2.246930e+05 6.183950e+03 1.538500e+03 9.222080e+03 3.139170e+03 9.499020e+02 3.180800e+03
2.590780e+05 2.269130e+05 4.388890e+03 3.694820e+03 8.195020e+03 3.933000e+03 4.260800e+02 2.388450e+03
2.545630e+05 2.247600e+05 5.168440e+03 4.020940e+03 8.450270e+03 4.758910e+03 1.458900e+03 2.286430e+03
2.580590e+05 2.212170e+05 6.883460e+03 1.649530e+03 9.232780e+03 4.457650e+03 3.057820e+03 3.031950e+03
2.646670e+05 2.211770e+05 6.218510e+03 1.645730e+03 8.657180e+03 3.663500e+03 2.528280e+03 3.978340e+03
2.629250e+05 2.243820e+05 4.627500e+03 3.635930e+03 7.892800e+03 3.431320e+03 6.045090e+02 3.901370e+03
2.547080e+05 2.254480e+05 4.408250e+03 4.461040e+03 8.197170e+03 3.953750e+03 -4.453460e+01 3.154870e+03
2.537020e+05 2.246350e+05 5.825770e+03 2.577050e+03 9.590050e+03 4.569250e+03 1.460270e+03 2.785170e+03
2.602060e+05 2.241400e+05 5.387980e+03 1.951160e+03 8.789510e+03 5.131660e+03 2.706380e+03 2.972480e+03
2.612400e+05 2.247370e+05 3.860810e+03 3.418310e+03 7.414530e+03 5.284520e+03 2.271380e+03 3.183150e+03
2.561400e+05 2.232520e+05 3.850010e+03 3.957140e+03 7.262650e+03 4.964640e+03 1.499510e+03 3.453130e+03
2.561160e+05 2.213490e+05 5.594480e+03 2.054400e+03 8.835130e+03 3.662010e+03 1.485510e+03 3.613010e+03

124
tests/data/extract-7 Normal file
View File

@@ -0,0 +1,124 @@
# path: /newton/prep
# layout: float32_8
# start: 1332496830000000
# end: 1332496830999000
1332496830000000 2.517740e+05 2.242410e+05 5.688100e+03 1.915530e+03 9.329220e+03 4.183710e+03 1.212350e+03 2.641790e+03
1332496830008333 2.595670e+05 2.226980e+05 6.207600e+03 6.786720e+02 9.380230e+03 4.575580e+03 2.830610e+03 2.688630e+03
1332496830016667 2.630730e+05 2.233040e+05 4.961640e+03 2.197120e+03 7.687310e+03 4.861860e+03 2.732780e+03 3.008540e+03
1332496830025000 2.576140e+05 2.233230e+05 5.003660e+03 3.525140e+03 7.165310e+03 4.685620e+03 1.715380e+03 3.440480e+03
1332496830033333 2.557800e+05 2.219150e+05 6.357310e+03 2.145290e+03 8.426970e+03 3.775350e+03 1.475390e+03 3.797240e+03
1332496830041667 2.601660e+05 2.230080e+05 6.702590e+03 1.484960e+03 9.288100e+03 3.330830e+03 1.228500e+03 3.214320e+03
1332496830050000 2.612310e+05 2.264260e+05 4.980060e+03 2.982380e+03 8.499630e+03 4.267670e+03 9.940890e+02 2.292890e+03
1332496830058333 2.551170e+05 2.266420e+05 4.584410e+03 4.656440e+03 7.860150e+03 5.317310e+03 1.473600e+03 2.111690e+03
1332496830066667 2.533000e+05 2.235540e+05 6.455090e+03 3.036650e+03 8.869750e+03 4.986310e+03 2.607360e+03 2.839590e+03
1332496830075000 2.610610e+05 2.212630e+05 6.951980e+03 1.500240e+03 9.386100e+03 3.791680e+03 2.677010e+03 3.980630e+03
1332496830083333 2.665030e+05 2.231980e+05 5.189610e+03 2.594560e+03 8.571530e+03 3.175000e+03 9.198400e+02 3.792010e+03
1332496830091667 2.606920e+05 2.251840e+05 3.782480e+03 4.642880e+03 7.662960e+03 3.917790e+03 -2.510970e+02 2.907060e+03
1332496830100000 2.539630e+05 2.250810e+05 5.123530e+03 3.839550e+03 8.669030e+03 4.877820e+03 9.437240e+02 2.527450e+03
1332496830108333 2.565550e+05 2.241690e+05 5.930600e+03 2.298540e+03 8.906710e+03 5.331680e+03 2.549910e+03 3.053560e+03
1332496830116667 2.608890e+05 2.250100e+05 4.681130e+03 2.971870e+03 7.900040e+03 4.874080e+03 2.322430e+03 3.649120e+03
1332496830125000 2.579440e+05 2.249230e+05 3.291140e+03 4.357090e+03 7.131590e+03 4.385560e+03 1.077050e+03 3.664040e+03
1332496830133333 2.550090e+05 2.230180e+05 4.584820e+03 2.864000e+03 8.469490e+03 3.625580e+03 9.855570e+02 3.504230e+03
1332496830141667 2.601140e+05 2.219470e+05 5.676190e+03 1.210340e+03 9.393780e+03 3.390240e+03 1.654020e+03 3.018700e+03
1332496830150000 2.642770e+05 2.244380e+05 4.446620e+03 2.176720e+03 8.142090e+03 4.584880e+03 2.327830e+03 2.615800e+03
1332496830158333 2.592210e+05 2.264710e+05 2.734440e+03 4.182760e+03 6.389550e+03 5.540520e+03 1.958880e+03 2.720120e+03
1332496830166667 2.526500e+05 2.248310e+05 4.163640e+03 2.989990e+03 7.179200e+03 5.213060e+03 1.929550e+03 3.457660e+03
1332496830175000 2.570830e+05 2.220480e+05 5.759040e+03 7.024410e+02 8.566550e+03 3.552020e+03 1.832940e+03 3.956190e+03
1332496830183333 2.631300e+05 2.229670e+05 5.141140e+03 1.166120e+03 8.666960e+03 2.720370e+03 9.713740e+02 3.479730e+03
1332496830191667 2.602360e+05 2.252650e+05 3.425140e+03 3.339080e+03 7.853610e+03 3.674950e+03 5.259080e+02 2.443310e+03
1332496830200000 2.535030e+05 2.245270e+05 4.398130e+03 2.927430e+03 8.110280e+03 4.842470e+03 1.513870e+03 2.467100e+03
1332496830208333 2.561260e+05 2.226930e+05 6.043530e+03 6.562240e+02 8.797560e+03 4.832410e+03 2.832370e+03 3.426140e+03
1332496830216667 2.616770e+05 2.236080e+05 5.830460e+03 1.033910e+03 8.123940e+03 3.980690e+03 1.927960e+03 4.092720e+03
1332496830225000 2.594570e+05 2.255360e+05 4.015570e+03 2.995990e+03 7.135440e+03 3.713550e+03 3.072200e+02 3.849430e+03
1332496830233333 2.533520e+05 2.242160e+05 4.650560e+03 3.196620e+03 8.131280e+03 3.586160e+03 7.083230e+01 3.074180e+03
1332496830241667 2.561240e+05 2.215130e+05 6.100480e+03 8.219800e+02 9.757540e+03 3.474510e+03 1.647520e+03 2.559860e+03
1332496830250000 2.630240e+05 2.215590e+05 5.789960e+03 6.994170e+02 9.129740e+03 4.153080e+03 2.829250e+03 2.677270e+03
1332496830258333 2.617200e+05 2.240150e+05 4.358500e+03 2.645360e+03 7.414110e+03 4.810670e+03 2.225990e+03 3.185990e+03
1332496830266667 2.547560e+05 2.242400e+05 4.857380e+03 3.229680e+03 7.539310e+03 4.769140e+03 1.507130e+03 3.668260e+03
1332496830275000 2.568890e+05 2.226580e+05 6.473420e+03 1.214110e+03 9.010760e+03 3.848730e+03 1.303840e+03 3.778500e+03
1332496830283333 2.642080e+05 2.233160e+05 5.700450e+03 1.116560e+03 9.087610e+03 3.846680e+03 1.293590e+03 2.891560e+03
1332496830291667 2.633100e+05 2.257190e+05 3.936120e+03 3.252360e+03 7.552850e+03 4.897860e+03 1.156630e+03 2.037160e+03
1332496830300000 2.550790e+05 2.250860e+05 4.536450e+03 3.960110e+03 7.454590e+03 5.479070e+03 1.596360e+03 2.190800e+03
1332496830308333 2.544870e+05 2.225080e+05 6.635860e+03 1.758850e+03 8.732970e+03 4.466970e+03 2.650360e+03 3.139310e+03
1332496830316667 2.612410e+05 2.224320e+05 6.702270e+03 1.085130e+03 8.989230e+03 3.112990e+03 1.933560e+03 3.828410e+03
1332496830325000 2.621190e+05 2.255870e+05 4.714950e+03 2.892360e+03 8.107820e+03 2.961310e+03 2.399780e+02 3.273720e+03
1332496830333333 2.549990e+05 2.265140e+05 4.532090e+03 4.126900e+03 8.200130e+03 3.872590e+03 5.608900e+01 2.370580e+03
1332496830341667 2.542890e+05 2.240330e+05 6.538810e+03 2.251440e+03 9.419430e+03 4.564450e+03 2.077810e+03 2.508170e+03
1332496830350000 2.618900e+05 2.219600e+05 6.846090e+03 1.475270e+03 9.125590e+03 4.598290e+03 3.299220e+03 3.475420e+03
1332496830358333 2.645020e+05 2.230850e+05 5.066380e+03 3.270560e+03 7.933170e+03 4.173710e+03 1.908910e+03 3.867460e+03
1332496830366667 2.578890e+05 2.236560e+05 4.201660e+03 4.473640e+03 7.688340e+03 4.161580e+03 6.875790e+02 3.653690e+03
1332496830375000 2.542700e+05 2.231510e+05 5.715140e+03 2.752140e+03 9.273320e+03 3.772950e+03 8.964040e+02 3.256060e+03
1332496830383333 2.582570e+05 2.242170e+05 6.114310e+03 1.856860e+03 9.604320e+03 4.200490e+03 1.764380e+03 2.939220e+03
1332496830391667 2.600200e+05 2.268680e+05 4.237530e+03 3.605880e+03 8.066220e+03 5.430250e+03 2.138580e+03 2.696710e+03
1332496830400000 2.550830e+05 2.259240e+05 3.350310e+03 4.853070e+03 7.045820e+03 5.925200e+03 1.893610e+03 2.897340e+03
1332496830408333 2.544530e+05 2.221270e+05 5.271330e+03 2.491500e+03 8.436680e+03 5.032080e+03 2.436050e+03 3.724590e+03
1332496830416667 2.625880e+05 2.199500e+05 5.994620e+03 7.892740e+02 9.029650e+03 3.515740e+03 1.953570e+03 4.014520e+03
1332496830425000 2.656100e+05 2.233330e+05 4.391410e+03 2.400960e+03 8.146460e+03 3.536960e+03 5.302320e+02 3.133920e+03
1332496830433333 2.574700e+05 2.269770e+05 2.975320e+03 4.633530e+03 7.278560e+03 4.640100e+03 -5.015020e+01 2.024960e+03
1332496830441667 2.506870e+05 2.263310e+05 4.517860e+03 3.183800e+03 8.072600e+03 5.281660e+03 1.605140e+03 2.335140e+03
1332496830450000 2.555630e+05 2.244950e+05 5.551000e+03 1.101300e+03 8.461490e+03 4.725700e+03 2.726670e+03 3.480540e+03
1332496830458333 2.613350e+05 2.246450e+05 4.764680e+03 1.557020e+03 7.833350e+03 3.524810e+03 1.577410e+03 4.038620e+03
1332496830466667 2.602690e+05 2.240080e+05 3.558030e+03 2.987610e+03 7.362440e+03 3.279230e+03 5.624420e+02 3.786550e+03
1332496830475000 2.574350e+05 2.217770e+05 4.972600e+03 2.166880e+03 8.481440e+03 3.328720e+03 1.037130e+03 3.271370e+03
1332496830483333 2.610460e+05 2.215500e+05 5.816180e+03 5.902170e+02 9.120930e+03 3.895400e+03 2.382670e+03 2.824170e+03
1332496830491667 2.627660e+05 2.244730e+05 4.835050e+03 1.785770e+03 7.880760e+03 4.745620e+03 2.443660e+03 3.229550e+03
1332496830500000 2.565090e+05 2.264130e+05 3.758870e+03 3.461200e+03 6.743770e+03 4.928960e+03 1.536620e+03 3.546690e+03
1332496830508333 2.507930e+05 2.243720e+05 5.218490e+03 2.865260e+03 7.803960e+03 4.351090e+03 1.333820e+03 3.680490e+03
1332496830516667 2.563190e+05 2.220660e+05 6.403970e+03 7.323450e+02 9.627760e+03 3.089300e+03 1.516780e+03 3.653690e+03
1332496830525000 2.633430e+05 2.232350e+05 5.200430e+03 1.388580e+03 9.372850e+03 3.371230e+03 1.450390e+03 2.678910e+03
1332496830533333 2.609030e+05 2.251100e+05 3.722580e+03 3.246660e+03 7.876540e+03 4.716810e+03 1.498440e+03 2.116520e+03
1332496830541667 2.544160e+05 2.237690e+05 4.841650e+03 2.956400e+03 8.115920e+03 5.392360e+03 2.142810e+03 2.652320e+03
1332496830550000 2.566980e+05 2.221720e+05 6.471230e+03 9.703960e+02 8.834980e+03 4.816840e+03 2.376630e+03 3.605860e+03
1332496830558333 2.618410e+05 2.235370e+05 5.500740e+03 1.189660e+03 8.365730e+03 4.016470e+03 1.042270e+03 3.821200e+03
1332496830566667 2.595030e+05 2.258400e+05 3.827930e+03 3.088840e+03 7.676140e+03 3.978310e+03 -3.570070e+02 3.016420e+03
1332496830575000 2.534570e+05 2.246360e+05 4.914610e+03 3.097450e+03 8.224900e+03 4.321440e+03 1.713740e+02 2.412360e+03
1332496830583333 2.560290e+05 2.222210e+05 6.841800e+03 1.028500e+03 9.252300e+03 4.387570e+03 2.418140e+03 2.510100e+03
1332496830591667 2.628400e+05 2.225500e+05 6.210250e+03 1.410730e+03 8.538900e+03 4.152580e+03 3.009300e+03 3.219760e+03
1332496830600000 2.616330e+05 2.250650e+05 4.284530e+03 3.357210e+03 7.282170e+03 3.823590e+03 1.402840e+03 3.644670e+03
1332496830608333 2.545910e+05 2.251090e+05 4.693160e+03 3.647740e+03 7.745160e+03 3.686380e+03 4.901610e+02 3.448860e+03
1332496830616667 2.547800e+05 2.235990e+05 6.527380e+03 1.569870e+03 9.438430e+03 3.456580e+03 1.162520e+03 3.252010e+03
1332496830625000 2.606390e+05 2.241070e+05 6.531050e+03 1.633050e+03 9.283720e+03 4.174020e+03 2.089550e+03 2.775750e+03
1332496830633333 2.611080e+05 2.254720e+05 4.968260e+03 3.527850e+03 7.692870e+03 5.137100e+03 2.207390e+03 2.436660e+03
1332496830641667 2.557750e+05 2.237080e+05 4.963450e+03 4.017370e+03 7.701420e+03 5.269650e+03 2.284400e+03 2.842080e+03
1332496830650000 2.573980e+05 2.209470e+05 6.767500e+03 1.645710e+03 9.107070e+03 4.000180e+03 2.548860e+03 3.624770e+03
1332496830658333 2.649240e+05 2.215590e+05 6.471460e+03 1.110330e+03 9.459650e+03 3.108170e+03 1.696970e+03 3.893440e+03
1332496830666667 2.653390e+05 2.257330e+05 4.348800e+03 3.459510e+03 8.475300e+03 4.031240e+03 5.733470e+02 2.910270e+03
1332496830675000 2.568140e+05 2.269950e+05 3.479540e+03 4.949790e+03 7.499910e+03 5.624710e+03 7.516560e+02 2.347710e+03
1332496830683333 2.533160e+05 2.251610e+05 5.147060e+03 3.218430e+03 8.460160e+03 5.869300e+03 2.336320e+03 2.987960e+03
1332496830691667 2.593600e+05 2.231010e+05 5.549120e+03 1.869950e+03 8.740760e+03 4.668940e+03 2.457910e+03 3.758820e+03
1332496830700000 2.620120e+05 2.240160e+05 4.173610e+03 3.004130e+03 8.157040e+03 3.704730e+03 9.879640e+02 3.652750e+03
1332496830708333 2.571760e+05 2.244200e+05 3.517300e+03 4.118750e+03 7.822240e+03 3.718230e+03 3.726490e+01 2.953680e+03
1332496830716667 2.551460e+05 2.233220e+05 4.923980e+03 2.330680e+03 9.095910e+03 3.792400e+03 1.013070e+03 2.711240e+03
1332496830725000 2.605240e+05 2.236510e+05 5.413630e+03 1.146210e+03 8.817170e+03 4.419650e+03 2.446650e+03 2.832050e+03
1332496830733333 2.620980e+05 2.257520e+05 4.262980e+03 2.270970e+03 7.135480e+03 5.067120e+03 2.294680e+03 3.376620e+03
1332496830741667 2.568890e+05 2.253790e+05 3.606460e+03 3.568190e+03 6.552650e+03 4.970270e+03 1.516380e+03 3.662570e+03
1332496830750000 2.539480e+05 2.226310e+05 5.511700e+03 2.066300e+03 7.952660e+03 4.019910e+03 1.513140e+03 3.752630e+03
1332496830758333 2.597990e+05 2.220670e+05 5.873500e+03 6.085840e+02 9.253780e+03 2.870740e+03 1.348240e+03 3.344200e+03
1332496830766667 2.625470e+05 2.249010e+05 4.346080e+03 1.928100e+03 8.590970e+03 3.455460e+03 9.043910e+02 2.379270e+03
1332496830775000 2.561370e+05 2.267610e+05 3.423560e+03 3.379080e+03 7.471150e+03 4.894170e+03 1.153540e+03 2.031410e+03
1332496830783333 2.503260e+05 2.250130e+05 5.519980e+03 2.423970e+03 7.991760e+03 5.117950e+03 2.098790e+03 3.099240e+03
1332496830791667 2.554540e+05 2.229920e+05 6.547950e+03 4.964960e+02 8.751340e+03 3.900560e+03 2.132290e+03 4.076810e+03
1332496830800000 2.612860e+05 2.234890e+05 5.152850e+03 1.501510e+03 8.425610e+03 2.888030e+03 7.761140e+02 3.786360e+03
1332496830808333 2.589690e+05 2.240690e+05 3.832610e+03 3.001980e+03 7.979260e+03 3.182310e+03 5.271600e+01 2.874800e+03
1332496830816667 2.549460e+05 2.220350e+05 5.317880e+03 2.139800e+03 9.103140e+03 3.955610e+03 1.235170e+03 2.394150e+03
1332496830825000 2.586760e+05 2.212050e+05 6.594910e+03 5.053440e+02 9.423360e+03 4.562470e+03 2.913740e+03 2.892350e+03
1332496830833333 2.621250e+05 2.235660e+05 5.116750e+03 1.773600e+03 8.082200e+03 4.776370e+03 2.386390e+03 3.659730e+03
1332496830841667 2.578350e+05 2.259180e+05 3.714300e+03 3.477080e+03 7.205370e+03 4.554610e+03 7.115390e+02 3.878420e+03
1332496830850000 2.536600e+05 2.243710e+05 5.022450e+03 2.592430e+03 8.277200e+03 4.119370e+03 4.865080e+02 3.666740e+03
1332496830858333 2.595030e+05 2.220610e+05 6.589950e+03 6.599360e+02 9.596920e+03 3.598100e+03 1.702490e+03 3.036600e+03
1332496830866667 2.654950e+05 2.228430e+05 5.541850e+03 1.728430e+03 8.459960e+03 4.492000e+03 2.231970e+03 2.430620e+03
1332496830875000 2.609290e+05 2.249960e+05 4.000950e+03 3.745990e+03 6.983790e+03 5.430860e+03 1.855260e+03 2.533380e+03
1332496830883333 2.527160e+05 2.243350e+05 5.086560e+03 3.401150e+03 7.597970e+03 5.196120e+03 1.755720e+03 3.079760e+03
1332496830891667 2.541100e+05 2.231110e+05 6.822190e+03 1.229080e+03 9.164340e+03 3.761230e+03 1.679390e+03 3.584880e+03
1332496830900000 2.599690e+05 2.246930e+05 6.183950e+03 1.538500e+03 9.222080e+03 3.139170e+03 9.499020e+02 3.180800e+03
1332496830908333 2.590780e+05 2.269130e+05 4.388890e+03 3.694820e+03 8.195020e+03 3.933000e+03 4.260800e+02 2.388450e+03
1332496830916667 2.545630e+05 2.247600e+05 5.168440e+03 4.020940e+03 8.450270e+03 4.758910e+03 1.458900e+03 2.286430e+03
1332496830925000 2.580590e+05 2.212170e+05 6.883460e+03 1.649530e+03 9.232780e+03 4.457650e+03 3.057820e+03 3.031950e+03
1332496830933333 2.646670e+05 2.211770e+05 6.218510e+03 1.645730e+03 8.657180e+03 3.663500e+03 2.528280e+03 3.978340e+03
1332496830941667 2.629250e+05 2.243820e+05 4.627500e+03 3.635930e+03 7.892800e+03 3.431320e+03 6.045090e+02 3.901370e+03
1332496830950000 2.547080e+05 2.254480e+05 4.408250e+03 4.461040e+03 8.197170e+03 3.953750e+03 -4.453460e+01 3.154870e+03
1332496830958333 2.537020e+05 2.246350e+05 5.825770e+03 2.577050e+03 9.590050e+03 4.569250e+03 1.460270e+03 2.785170e+03
1332496830966667 2.602060e+05 2.241400e+05 5.387980e+03 1.951160e+03 8.789510e+03 5.131660e+03 2.706380e+03 2.972480e+03
1332496830975000 2.612400e+05 2.247370e+05 3.860810e+03 3.418310e+03 7.414530e+03 5.284520e+03 2.271380e+03 3.183150e+03
1332496830983333 2.561400e+05 2.232520e+05 3.850010e+03 3.957140e+03 7.262650e+03 4.964640e+03 1.499510e+03 3.453130e+03
1332496830991667 2.561160e+05 2.213490e+05 5.594480e+03 2.054400e+03 8.835130e+03 3.662010e+03 1.485510e+03 3.613010e+03

28
tests/data/extract-8 Normal file
View File

@@ -0,0 +1,28 @@
# interval-start 1332496919900000
1332496919900000 2.523050e+05 2.254020e+05 4.779410e+03 3.638030e+03 8.138070e+03 4.334460e+03 1.083780e+03 3.743730e+03
1332496919908333 2.551190e+05 2.237870e+05 5.965640e+03 2.076350e+03 9.468790e+03 3.693880e+03 1.247860e+03 3.393680e+03
1332496919916667 2.616370e+05 2.247980e+05 4.848970e+03 2.315620e+03 9.323300e+03 4.225460e+03 1.805780e+03 2.593050e+03
1332496919925000 2.606460e+05 2.251300e+05 3.061360e+03 3.951840e+03 7.662910e+03 5.341410e+03 1.986520e+03 2.276780e+03
1332496919933333 2.559710e+05 2.235030e+05 4.096030e+03 3.296970e+03 7.827080e+03 5.452120e+03 2.492520e+03 2.929450e+03
1332496919941667 2.579260e+05 2.217080e+05 5.472320e+03 1.555700e+03 8.495760e+03 4.491140e+03 2.379780e+03 3.741710e+03
1332496919950000 2.610180e+05 2.242350e+05 4.669770e+03 1.876190e+03 8.366680e+03 3.677510e+03 9.021690e+02 3.549040e+03
1332496919958333 2.569150e+05 2.274650e+05 2.785070e+03 3.751930e+03 7.440320e+03 3.964860e+03 -3.227860e+02 2.460890e+03
1332496919966667 2.509510e+05 2.262000e+05 3.772710e+03 3.131950e+03 8.159860e+03 4.539860e+03 7.375190e+02 2.126750e+03
1332496919975000 2.556710e+05 2.223720e+05 5.826200e+03 8.715560e+02 9.120240e+03 4.545110e+03 2.804310e+03 2.721000e+03
1332496919983333 2.649730e+05 2.214860e+05 5.839130e+03 4.659180e+02 8.628300e+03 3.934870e+03 2.972490e+03 3.773730e+03
1332496919991667 2.652170e+05 2.233920e+05 3.718770e+03 2.834970e+03 7.209900e+03 3.460260e+03 1.324930e+03 4.075960e+03
# interval-end 1332496919991668
# interval-start 1332496920000000
1332496920000000 2.564370e+05 2.244300e+05 4.011610e+03 3.475340e+03 7.495890e+03 3.388940e+03 2.613970e+02 3.731260e+03
1332496920008333 2.539630e+05 2.241670e+05 5.621070e+03 1.548010e+03 9.165170e+03 3.522930e+03 1.058930e+03 2.996960e+03
1332496920016667 2.585080e+05 2.249300e+05 6.011400e+03 8.188660e+02 9.039950e+03 4.482440e+03 2.490390e+03 2.679340e+03
1332496920025000 2.596270e+05 2.260220e+05 4.474500e+03 2.423020e+03 7.414190e+03 5.071970e+03 2.439380e+03 2.962960e+03
1332496920033333 2.551870e+05 2.246320e+05 4.738570e+03 3.398040e+03 7.395120e+03 4.726450e+03 1.839030e+03 3.393530e+03
1332496920041667 2.571020e+05 2.216230e+05 6.144130e+03 1.441090e+03 8.756480e+03 3.495320e+03 1.869940e+03 3.752530e+03
1332496920050000 2.636530e+05 2.217700e+05 6.221770e+03 7.389620e+02 9.547600e+03 2.666820e+03 1.462660e+03 3.332570e+03
1332496920058333 2.636130e+05 2.252560e+05 4.477120e+03 2.437450e+03 8.510210e+03 3.855630e+03 9.594420e+02 2.387180e+03
1332496920066667 2.553500e+05 2.262640e+05 4.283720e+03 3.923940e+03 7.912470e+03 5.466520e+03 1.284990e+03 2.093720e+03
1332496920075000 2.527270e+05 2.246090e+05 5.851930e+03 2.491980e+03 8.540630e+03 5.623050e+03 2.339780e+03 3.007140e+03
1332496920083333 2.584750e+05 2.235780e+05 5.924870e+03 1.394480e+03 8.779620e+03 4.544180e+03 2.132030e+03 3.849760e+03
1332496920091667 2.615630e+05 2.246090e+05 4.336140e+03 2.455750e+03 8.055380e+03 3.469110e+03 6.278730e+02 3.664200e+03
# interval-end 1332496920100000

View File

@@ -1,3 +1,4 @@
# comments are cool?
2.66568e+05 2.24029e+05 5.16140e+03 2.52517e+03 8.35084e+03 3.72470e+03 1.35534e+03 2.03900e+03
2.57914e+05 2.27183e+05 4.30368e+03 4.13080e+03 7.25535e+03 4.89047e+03 1.63859e+03 1.93496e+03
2.51717e+05 2.26047e+05 5.99445e+03 3.49363e+03 8.07250e+03 5.08267e+03 2.26917e+03 2.86231e+03

View File

@@ -0,0 +1,19 @@
2.56437e+05 2.24430e+05 4.01161e+03 3.47534e+03 7.49589e+03 3.38894e+03 2.61397e+02 3.73126e+03
2.53963e+05 2.24167e+05 5.62107e+03 1.54801e+03 9.16517e+03 3.52293e+03 1.05893e+03 2.99696e+03
2.58508e+05 2.24930e+05 6.01140e+03 8.18866e+02 9.03995e+03 4.48244e+03 2.49039e+03 2.67934e+03
2.59627e+05 2.26022e+05 4.47450e+03 2.42302e+03 7.41419e+03 5.07197e+03 2.43938e+03 2.96296e+03
2.55187e+05 2.24632e+05 4.73857e+03 3.39804e+03 7.39512e+03 4.72645e+03 1.83903e+03 3.39353e+03
2.57102e+05 2.21623e+05 6.14413e+03 1.44109e+03 8.75648e+03 3.49532e+03 1.86994e+03 3.75253e+03
2.63653e+05 2.21770e+05 6.22177e+03 7.38962e+02 9.54760e+03 2.66682e+03 1.46266e+03 3.33257e+03
2.63613e+05 2.25256e+05 4.47712e+03 2.43745e+03 8.51021e+03 3.85563e+03 9.59442e+02 2.38718e+03
2.55350e+05 2.26264e+05 4.28372e+03 3.92394e+03 7.91247e+03 5.46652e+03 1.28499e+03 2.09372e+03
2.52727e+05 2.24609e+05 5.85193e+03 2.49198e+03 8.54063e+03 5.62305e+03 2.33978e+03 3.00714e+03
2.58475e+05 2.23578e+05 5.92487e+03 1.39448e+03 8.77962e+03 4.54418e+03 2.13203e+03 3.84976e+03
2.61563e+05 2.24609e+05 4.33614e+03 2.45575e+03 8.05538e+03 3.46911e+03 6.27873e+02 3.66420e+03
2.56401e+05 2.24441e+05 4.18715e+03 3.45717e+03 7.90669e+03 3.53355e+03 -5.84482e+00 2.96687e+03
2.54745e+05 2.22644e+05 6.02005e+03 1.94721e+03 9.28939e+03 3.80020e+03 1.34820e+03 2.37785e+03
2.60723e+05 2.22660e+05 6.69719e+03 1.03048e+03 9.26124e+03 4.34917e+03 2.84530e+03 2.73619e+03
2.63089e+05 2.25711e+05 4.77887e+03 2.60417e+03 7.39660e+03 4.59811e+03 2.17472e+03 3.40729e+03
2.55843e+05 2.27128e+05 4.02413e+03 4.39323e+03 6.79336e+03 4.62535e+03 7.52009e+02 3.44647e+03
2.51904e+05 2.24868e+05 5.82289e+03 3.02127e+03 8.46160e+03 3.80298e+03 8.07212e+02 3.53468e+03
2.57670e+05 2.22974e+05 6.73436e+03 1.60956e+03 9.92960e+03 2.98028e+03 1.44168e+03 3.05351e+03

View File

@@ -0,0 +1,11 @@
1332497040000000 2.56439e+05 2.24775e+05 2.92897e+03 4.66646e+03 7.58491e+03 3.57351e+03 -4.34171e+02 2.98819e+03
1332497040010000 2.51903e+05 2.23202e+05 4.23696e+03 3.49363e+03 8.53493e+03 4.29416e+03 8.49573e+02 2.38189e+03
1332497040020000 2.57625e+05 2.20247e+05 5.47017e+03 1.35872e+03 9.18903e+03 4.56136e+03 2.65599e+03 2.60912e+03
1332497040030000 2.63375e+05 2.20706e+05 4.51842e+03 1.80758e+03 8.17208e+03 4.17463e+03 2.57884e+03 3.32848e+03
1332497040040000 2.59221e+05 2.22346e+05 2.98879e+03 3.66264e+03 6.87274e+03 3.94223e+03 1.25928e+03 3.51786e+03
1332497040050000 2.51918e+05 2.22281e+05 4.22677e+03 2.84764e+03 7.78323e+03 3.81659e+03 8.04944e+02 3.46314e+03
1332497040050000 2.54478e+05 2.21701e+05 5.61366e+03 1.02262e+03 9.26581e+03 3.50152e+03 1.29331e+03 3.07271e+03
1332497040060000 2.59568e+05 2.22945e+05 4.97190e+03 1.28250e+03 8.62081e+03 4.06316e+03 1.85717e+03 2.61990e+03
1332497040070000 2.57269e+05 2.23697e+05 3.60527e+03 3.05749e+03 7.22363e+03 4.90330e+03 1.93736e+03 2.35357e+03
1332497040080000 2.52274e+05 2.21438e+05 5.01228e+03 2.86309e+03 7.87115e+03 4.80448e+03 2.18291e+03 2.93397e+03
1332497040090000 2.56468e+05 2.19205e+05 6.29804e+03 8.09467e+02 9.12895e+03 3.52055e+03 2.16980e+03 3.88739e+03

File diff suppressed because it is too large Load Diff

8
tests/data/timestamped Normal file
View File

@@ -0,0 +1,8 @@
-10000000000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
-100000000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
-100000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
-1000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
1 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
1000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
1000000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03
1000000000 2.61246e+05 2.22735e+05 4.60340e+03 2.58221e+03 8.42804e+03 3.41890e+03 9.57898e+02 4.00585e+03

49
tests/runtests.py Executable file
View File

@@ -0,0 +1,49 @@
#!/usr/bin/python
import nose
import os
import sys
import glob
from collections import OrderedDict
# Change into parent dir
os.chdir(os.path.dirname(os.path.realpath(__file__)) + "/..")
class JimOrderPlugin(nose.plugins.Plugin):
"""When searching for tests and encountering a directory that
contains a 'test.order' file, run tests listed in that file, in the
order that they're listed. Globs are OK in that file and duplicates
are removed."""
name = 'jimorder'
score = 10000
def prepareTestLoader(self, loader):
def wrap(func):
def wrapper(name, *args, **kwargs):
addr = nose.selector.TestAddress(
name, workingDir=loader.workingDir)
try:
order = os.path.join(addr.filename, "test.order")
except Exception:
order = None
if order and os.path.exists(order):
files = []
for line in open(order):
line = line.split('#')[0].strip()
if not line:
continue
fn = os.path.join(addr.filename, line.strip())
files.extend(sorted(glob.glob(fn)) or [fn])
files = list(OrderedDict.fromkeys(files))
tests = [ wrapper(fn, *args, **kwargs) for fn in files ]
return loader.suiteClass(tests)
return func(name, *args, **kwargs)
return wrapper
loader.loadTestsFromName = wrap(loader.loadTestsFromName)
return loader
# Use setup.cfg for most of the test configuration. Adding
# --with-jimorder here means that a normal "nosetests" run will
# still work, it just won't support test.order.
nose.main(addplugins = [ JimOrderPlugin() ],
argv = sys.argv + ["--with-jimorder"])

18
tests/test.order Normal file
View File

@@ -0,0 +1,18 @@
test_printf.py
test_threadsafety.py
test_lrucache.py
test_mustclose.py
test_serializer.py
test_timestamper.py
test_rbtree.py
test_interval.py
test_bulkdata.py
test_nilmdb.py
test_client.py
test_numpyclient.py
test_cmdline.py
test_*.py

121
tests/test_bulkdata.py Normal file
View File

@@ -0,0 +1,121 @@
# -*- coding: utf-8 -*-
import nilmdb
from nilmdb.utils.printf import *
from nose.tools import *
from nose.tools import assert_raises
import itertools
from testutil.helpers import *
testdb = "tests/bulkdata-testdb"
import nilmdb.server.bulkdata
from nilmdb.server.bulkdata import BulkData
class TestBulkData(object):
def test_bulkdata(self):
for (size, files, db) in [ ( 0, 0, testdb ),
( 25, 1000, testdb ),
( 1000, 3, testdb.decode("utf-8") ) ]:
recursive_unlink(db)
os.mkdir(db)
self.do_basic(db, size, files)
def do_basic(self, db, size, files):
"""Do the basic test with variable file_size and files_per_dir"""
if not size or not files:
data = BulkData(db)
else:
data = BulkData(db, file_size = size, files_per_dir = files)
# Try opening it again (should result in locking error)
with assert_raises(IOError) as e:
data2 = BulkData(db)
in_("already locked by another process", str(e.exception))
# create empty
with assert_raises(ValueError):
data.create("/foo", "uint16_8")
with assert_raises(ValueError):
data.create("foo/bar", "uint16_8")
data.create("/foo/bar", "uint16_8")
data.create(u"/foo/baz/quux", "float64_16")
with assert_raises(ValueError):
data.create("/foo/bar/baz", "uint16_8")
with assert_raises(ValueError):
data.create("/foo/baz", "float64_16")
# get node -- see if caching works
nodes = []
for i in range(5000):
nodes.append(data.getnode("/foo/bar"))
nodes.append(data.getnode("/foo/baz/quux"))
del nodes
def get_node_slice(key):
if isinstance(key, slice):
return [ node.get_data(x, x+1) for x in
xrange(*key.indices(node.nrows)) ]
return node.get_data(key, key+1)
# Test node
node = data.getnode("/foo/bar")
with assert_raises(IndexError):
x = get_node_slice(0)
with assert_raises(IndexError):
x = node[0] # timestamp
raw = []
for i in range(1000):
raw.append("%d 1 2 3 4 5 6 7 8\n" % (10000 + i))
node.append_data("".join(raw[0:1]), 0, 50000)
node.append_data("".join(raw[1:100]), 0, 50000)
node.append_data("".join(raw[100:]), 0, 50000)
misc_slices = [ 0, 100, slice(None), slice(0), slice(10),
slice(5,10), slice(3,None), slice(3,-3),
slice(20,10), slice(200,100,-1), slice(None,0,-1),
slice(100,500,5) ]
# Extract slices
for s in misc_slices:
eq_(get_node_slice(s), raw[s])
# Extract misc slices while appending, to make sure the
# data isn't being added in the middle of the file
for s in [2, slice(1,5), 2, slice(1,5)]:
node.append_data("0 0 0 0 0 0 0 0 0\n", 0, 50000)
raw.append("0 0 0 0 0 0 0 0 0\n")
eq_(get_node_slice(s), raw[s])
# Get some coverage of remove; remove is more fully tested
# in cmdline
with assert_raises(IndexError):
node.remove(9999,9998)
# close, reopen
# reopen
data.close()
if not size or not files:
data = BulkData(db)
else:
data = BulkData(db, file_size = size, files_per_dir = files)
node = data.getnode("/foo/bar")
# Extract slices
for s in misc_slices:
eq_(get_node_slice(s), raw[s])
# destroy
with assert_raises(ValueError):
data.destroy("/foo")
with assert_raises(ValueError):
data.destroy("/foo/baz")
with assert_raises(ValueError):
data.destroy("/foo/qwerty")
data.destroy("/foo/baz/quux")
data.destroy("/foo/bar")
# close
data.close()

Some files were not shown because too many files have changed in this diff Show More