mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-28 20:54:47 +08:00
Dale Jung
7892a6943f
on the number of per-tick update that occur since they were duplicated per each PerformancePeriod. Also opens up the path to cythonizing the entire object
107 lines
3.5 KiB
Python
107 lines
3.5 KiB
Python
#
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# Copyright 2015 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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import os
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import pandas
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import pickle
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from nose_parameterized import parameterized
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from unittest import TestCase
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from zipline.finance.blotter import Order
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from .serialization_cases import (
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object_serialization_cases,
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assert_dict_equal
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)
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base_state_dir = 'tests/resources/saved_state_archive'
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BASE_STATE_DIR = os.path.join(
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os.path.dirname(__file__),
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'resources',
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'saved_state_archive')
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class VersioningTestCase(TestCase):
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def load_state_from_disk(self, cls):
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state_dir = cls.__module__ + '.' + cls.__name__
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full_dir = BASE_STATE_DIR + '/' + state_dir
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state_files = \
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[f for f in os.listdir(full_dir) if 'State_Version_' in f]
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for f_name in state_files:
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f = open(full_dir + '/' + f_name, 'r')
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yield pickle.load(f)
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# Only test versioning in minutely mode right now
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@parameterized.expand(object_serialization_cases(skip_daily=True))
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def test_object_serialization(self,
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_,
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cls,
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initargs,
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di_vars,
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comparison_method='dict'):
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# The state generated under one version of pandas may not be
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# compatible with another. To ensure that tests pass under the travis
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# pandas version matrix, we only run versioning tests under the
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# current version of pandas. This will need to be updated once we
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# change the pandas version on prod.
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if pandas.__version__ != '0.12.0':
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return
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# Make reference object
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obj = cls(*initargs)
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for k, v in di_vars.items():
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setattr(obj, k, v)
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# Fetch state
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state_versions = self.load_state_from_disk(cls)
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for version in state_versions:
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# For each version inflate a new object and ensure that it
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# matches the original.
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newargs = version['newargs']
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initargs = version['initargs']
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state = version['obj_state']
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if newargs is not None:
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obj2 = cls.__new__(cls, *newargs)
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else:
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obj2 = cls.__new__(cls)
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if initargs is not None:
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obj2.__init__(*initargs)
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obj2.__setstate__(state)
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for k, v in di_vars.items():
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setattr(obj2, k, v)
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# The ObjectId generated on instantiation of Order will
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# not be the same as the one loaded from saved state.
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if cls == Order:
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obj.__dict__['id'] = obj2.__dict__['id']
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if comparison_method == 'repr':
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self.assertEqual(obj.__repr__(), obj2.__repr__())
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elif comparison_method == 'to_dict':
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assert_dict_equal(obj.to_dict(), obj2.to_dict())
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else:
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assert_dict_equal(obj.__dict__, obj2.__dict__)
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