mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 20:54:47 +08:00
Scott Sanderson
5e87bf2496
We need to call gc.collect before tearing down our class because we have a cycle between TradingAlgorithm and AlgorithmSimulator which ultimately holds a reference to the pipeline engine passed to the tests here. This means that we're not guaranteed to have deleted our disk-backed resource readers (e.g. SQLiteAdjustmentReader) before trying to delete the tempdir, which causes failures on Windows because Windows doesn't allow you to delete a file if someone still has an open handle to that file. The real fix for this is to break the cycle between TradingAlgorithm and AlgorithmSimulator, but that requires significant breaking API changes.
89 lines
3.2 KiB
Python
89 lines
3.2 KiB
Python
#
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# Copyright 2013 Quantopian, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from functools import partial
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import gc
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import tarfile
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import matplotlib
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from nose_parameterized import parameterized
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import pandas as pd
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from zipline import examples
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from zipline.data.bundles import register, unregister
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from zipline.testing import test_resource_path
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from zipline.testing.fixtures import WithTmpDir, ZiplineTestCase
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from zipline.testing.predicates import assert_equal
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from zipline.utils.cache import dataframe_cache
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# Otherwise the next line sometimes complains about being run too late.
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_multiprocess_can_split_ = False
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matplotlib.use('Agg')
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class ExamplesTests(WithTmpDir, ZiplineTestCase):
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# some columns contain values with unique ids that will not be the same
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@classmethod
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def init_class_fixtures(cls):
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super(ExamplesTests, cls).init_class_fixtures()
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register('test', lambda *args: None)
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cls.add_class_callback(partial(unregister, 'test'))
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with tarfile.open(test_resource_path('example_data.tar.gz')) as tar:
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tar.extractall(cls.tmpdir.path)
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cls.expected_perf = dataframe_cache(
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cls.tmpdir.getpath(
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'example_data/expected_perf/%s' %
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pd.__version__.replace('.', '-'),
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),
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serialization='pickle',
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)
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# We need to call gc.collect before tearing down our class because we
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# have a cycle between TradingAlgorithm and AlgorithmSimulator which
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# ultimately holds a reference to the pipeline engine passed to the
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# tests here.
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# This means that we're not guaranteed to have deleted our disk-backed
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# resource readers (e.g. SQLiteAdjustmentReader) before trying to
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# delete the tempdir, which causes failures on Windows because Windows
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# doesn't allow you to delete a file if someone still has an open
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# handle to that file.
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# :(
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cls.add_class_callback(gc.collect)
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@parameterized.expand(examples.EXAMPLE_MODULES)
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def test_example(self, example_name):
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actual_perf = examples.run_example(
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example_name,
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# This should match the invocation in
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# zipline/tests/resources/rebuild_example_data
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environ={
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'ZIPLINE_ROOT': self.tmpdir.getpath('example_data/root'),
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},
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)
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assert_equal(
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actual_perf[examples._cols_to_check],
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self.expected_perf[example_name][examples._cols_to_check],
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# There is a difference in the datetime columns in pandas
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# 0.16 and 0.17 because in 16 they are object and in 17 they are
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# datetime[ns, UTC]. We will just ignore the dtypes for now.
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check_dtype=False,
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)
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