343 lines
13 KiB
Python
343 lines
13 KiB
Python
# -*- coding: utf-8 -*-
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import nilmdb.server
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import nilmdb.client
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import nilmdb.client.numpyclient
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from nilmdb.utils.printf import *
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from nilmdb.utils import timestamper
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from nilmdb.client import ClientError, ServerError
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from nilmdb.utils import datetime_tz
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from nose.plugins.skip import SkipTest
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from nose.tools import *
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from nose.tools import assert_raises
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import itertools
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import distutils.version
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from testutil.helpers import *
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import numpy as np
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testdb = "tests/numpyclient-testdb"
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testurl = "http://localhost:32180/"
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def setup_module():
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global test_server, test_db
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# Clear out DB
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recursive_unlink(testdb)
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# Start web app on a custom port
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test_db = nilmdb.utils.serializer_proxy(nilmdb.server.NilmDB)(testdb)
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test_server = nilmdb.server.Server(test_db, host = "127.0.0.1",
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port = 32180, stoppable = False,
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fast_shutdown = True,
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force_traceback = True)
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test_server.start(blocking = False)
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def teardown_module():
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global test_server, test_db
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# Close web app
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test_server.stop()
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test_db.close()
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class TestNumpyClient(object):
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def test_numpyclient_01_basic(self):
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# Test basic connection
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client = nilmdb.client.numpyclient.NumpyClient(url = testurl)
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version = client.version()
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eq_(distutils.version.LooseVersion(version),
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distutils.version.LooseVersion(test_server.version))
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# Verify subclassing
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assert(isinstance(client, nilmdb.client.Client))
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# Layouts
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for layout in "int8_t", "something_8", "integer_1":
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with assert_raises(ValueError):
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for x in client.stream_extract_numpy("/foo", layout=layout):
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pass
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for layout in "int8_1", "uint8_30", "int16_20", "float64_100":
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with assert_raises(ClientError) as e:
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for x in client.stream_extract_numpy("/foo", layout=layout):
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pass
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in_("No such stream", str(e.exception))
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with assert_raises(ClientError) as e:
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for x in client.stream_extract_numpy("/foo"):
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pass
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in_("can't get layout for path", str(e.exception))
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client.close()
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def test_numpyclient_02_extract(self):
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client = nilmdb.client.numpyclient.NumpyClient(url = testurl)
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# Insert some data as text
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client.stream_create("/newton/prep", "float32_8")
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testfile = "tests/data/prep-20120323T1000"
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start = nilmdb.utils.time.parse_time("20120323T1000")
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rate = 120
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data = timestamper.TimestamperRate(testfile, start, rate)
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result = client.stream_insert("/newton/prep", data,
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start, start + 119999777)
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# Extract Numpy arrays
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array = None
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pieces = 0
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for chunk in client.stream_extract_numpy("/newton/prep", maxrows=1000):
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pieces += 1
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if array is not None:
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array = np.vstack((array, chunk))
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else:
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array = chunk
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eq_(array.shape, (14400, 9))
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eq_(pieces, 15)
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# Try structured
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s = list(client.stream_extract_numpy("/newton/prep", structured = True))
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assert(np.array_equal(np.c_[s[0]['timestamp'], s[0]['data']], array))
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# Compare. Will be close but not exact because the conversion
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# to and from ASCII was lossy.
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data = timestamper.TimestamperRate(testfile, start, rate)
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actual = np.fromstring(" ".join(data), sep=' ').reshape(14400, 9)
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assert(np.allclose(array, actual))
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client.close()
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def test_numpyclient_03_insert(self):
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client = nilmdb.client.numpyclient.NumpyClient(url = testurl)
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# Limit _max_data just to get better coverage
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old_max_data = nilmdb.client.numpyclient.StreamInserterNumpy._max_data
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nilmdb.client.numpyclient.StreamInserterNumpy._max_data = 100000
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client.stream_create("/test/1", "uint16_1")
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client.stream_insert_numpy("/test/1",
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np.array([[0, 1],
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[1, 2],
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[2, 3],
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[3, 4]]))
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# Wrong number of dimensions
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with assert_raises(ValueError) as e:
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client.stream_insert_numpy("/test/1",
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np.array([[[0, 1],
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[1, 2]],
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[[3, 4],
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[4, 5]]]))
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in_("wrong number of dimensions", str(e.exception))
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# Wrong number of fields
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with assert_raises(ValueError) as e:
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client.stream_insert_numpy("/test/1",
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np.array([[0, 1, 2],
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[1, 2, 3],
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[3, 4, 5],
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[4, 5, 6]]))
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in_("wrong number of fields", str(e.exception))
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# Unstructured
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client.stream_create("/test/2", "float32_8")
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client.stream_insert_numpy(
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"/test/2",
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client.stream_extract_numpy(
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"/newton/prep", structured = False, maxrows = 1000))
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# Structured, and specifying layout
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client.stream_create("/test/3", "float32_8")
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client.stream_insert_numpy(
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path = "/test/3", layout = "float32_8",
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data = client.stream_extract_numpy(
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"/newton/prep", structured = True, maxrows = 1000))
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# Structured, specifying wrong layout
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client.stream_create("/test/4", "float32_8")
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with assert_raises(ValueError) as e:
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client.stream_insert_numpy(
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"/test/4", layout = "uint16_1",
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data = client.stream_extract_numpy(
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"/newton/prep", structured = True, maxrows = 1000))
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in_("wrong dtype", str(e.exception))
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# Unstructured, and specifying wrong layout
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client.stream_create("/test/5", "float32_8")
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with assert_raises(ClientError) as e:
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client.stream_insert_numpy(
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"/test/5", layout = "uint16_8",
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data = client.stream_extract_numpy(
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"/newton/prep", structured = False, maxrows = 1000))
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# timestamps will be screwy here, because data will be parsed wrong
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in_("error parsing input data", str(e.exception))
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# Make sure the /newton/prep copies are identical
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a = np.vstack(client.stream_extract_numpy("/newton/prep"))
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b = np.vstack(client.stream_extract_numpy("/test/2"))
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c = np.vstack(client.stream_extract_numpy("/test/3"))
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assert(np.array_equal(a,b))
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assert(np.array_equal(a,c))
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nilmdb.client.numpyclient.StreamInserterNumpy._max_data = old_max_data
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client.close()
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def test_numpyclient_04_context(self):
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# Like test_client_context, but with Numpy data
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client = nilmdb.client.numpyclient.NumpyClient(testurl)
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client.stream_create("/context/test", "uint16_1")
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with client.stream_insert_numpy_context("/context/test") as ctx:
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# override _max_rows to trigger frequent server updates
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ctx._max_rows = 2
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ctx.insert([[1000, 1]])
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ctx.insert([[1010, 1], [1020, 1], [1030, 1]])
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ctx.insert([[1040, 1], [1050, 1]])
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ctx.finalize()
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ctx.insert([[1070, 1]])
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ctx.update_end(1080)
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ctx.finalize()
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ctx.update_start(1090)
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ctx.insert([[1100, 1]])
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ctx.insert([[1110, 1]])
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ctx.send()
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ctx.insert([[1120, 1], [1130, 1], [1140, 1]])
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ctx.update_end(1160)
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ctx.insert([[1150, 1]])
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ctx.update_end(1170)
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ctx.insert([[1160, 1]])
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ctx.update_end(1180)
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ctx.insert([[1170, 123456789.0]])
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ctx.finalize()
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ctx.insert(np.zeros((0,2)))
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with assert_raises(ClientError):
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with client.stream_insert_numpy_context("/context/test",
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1000, 2000) as ctx:
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ctx.insert([[1180, 1]])
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with assert_raises(ClientError):
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with client.stream_insert_numpy_context("/context/test",
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2000, 3000) as ctx:
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ctx._max_rows = 2
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ctx.insert([[3180, 1]])
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ctx.insert([[3181, 1]])
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with client.stream_insert_numpy_context("/context/test",
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2000, 3000) as ctx:
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# make sure our override wasn't permanent
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ne_(ctx._max_rows, 2)
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ctx.insert([[2250, 1]])
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ctx.finalize()
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with assert_raises(ClientError):
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with client.stream_insert_numpy_context("/context/test",
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3000, 4000) as ctx:
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ctx.insert([[3010, 1]])
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ctx.insert([[3020, 2]])
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ctx.insert([[3030, 3]])
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ctx.insert([[3040, 4]])
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ctx.insert([[3040, 4]]) # non-monotonic after a few lines
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ctx.finalize()
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eq_(list(client.stream_intervals("/context/test")),
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[ [ 1000, 1051 ],
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[ 1070, 1080 ],
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[ 1090, 1180 ],
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[ 2000, 3000 ] ])
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client.stream_remove("/context/test")
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client.stream_destroy("/context/test")
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client.close()
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def test_numpyclient_05_emptyintervals(self):
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# Like test_client_emptyintervals, with insert_numpy_context
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client = nilmdb.client.numpyclient.NumpyClient(testurl)
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client.stream_create("/empty/test", "uint16_1")
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def info():
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result = []
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for interval in list(client.stream_intervals("/empty/test")):
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result.append((client.stream_count("/empty/test", *interval),
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interval))
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return result
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eq_(info(), [])
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# Insert a region with just a few points
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with client.stream_insert_numpy_context("/empty/test") as ctx:
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ctx.update_start(100)
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ctx.insert([[140, 1]])
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ctx.insert([[150, 1]])
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ctx.insert([[160, 1]])
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ctx.update_end(200)
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ctx.finalize()
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eq_(info(), [(3, [100, 200])])
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# Delete chunk, which will leave one data point and two intervals
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client.stream_remove("/empty/test", 145, 175)
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eq_(info(), [(1, [100, 145]),
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(0, [175, 200])])
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# Try also creating a completely empty interval from scratch,
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# in a few different ways.
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client.stream_insert("/empty/test", "", 300, 350)
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client.stream_insert("/empty/test", [], 400, 450)
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with client.stream_insert_numpy_context("/empty/test", 500, 550):
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pass
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# If enough timestamps aren't provided, empty streams won't be created.
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client.stream_insert("/empty/test", [])
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with client.stream_insert_numpy_context("/empty/test"):
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pass
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client.stream_insert("/empty/test", [], start = 600)
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with client.stream_insert_numpy_context("/empty/test", start = 700):
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pass
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client.stream_insert("/empty/test", [], end = 850)
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with client.stream_insert_numpy_context("/empty/test", end = 950):
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pass
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# Try various things that might cause problems
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with client.stream_insert_numpy_context("/empty/test", 1000, 1050):
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ctx.finalize() # inserts [1000, 1050]
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ctx.finalize() # nothing
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ctx.finalize() # nothing
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ctx.insert([[1100, 1]])
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ctx.finalize() # inserts [1100, 1101]
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ctx.update_start(1199)
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ctx.insert([[1200, 1]])
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ctx.update_end(1250)
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ctx.finalize() # inserts [1199, 1250]
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ctx.update_start(1299)
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ctx.finalize() # nothing
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ctx.update_end(1350)
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ctx.finalize() # nothing
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ctx.update_start(1400)
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ctx.insert(np.zeros((0,2)))
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ctx.update_end(1450)
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ctx.finalize()
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ctx.update_start(1500)
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ctx.insert(np.zeros((0,2)))
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ctx.update_end(1550)
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ctx.finalize()
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ctx.insert(np.zeros((0,2)))
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ctx.insert(np.zeros((0,2)))
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ctx.insert(np.zeros((0,2)))
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ctx.finalize()
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# Check everything
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eq_(info(), [(1, [100, 145]),
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(0, [175, 200]),
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(0, [300, 350]),
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(0, [400, 450]),
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(0, [500, 550]),
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(0, [1000, 1050]),
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(1, [1100, 1101]),
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(1, [1199, 1250]),
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(0, [1400, 1450]),
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(0, [1500, 1550]),
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])
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# Clean up
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client.stream_remove("/empty/test")
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client.stream_destroy("/empty/test")
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client.close()
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