zipline/tests/test_examples.py

#
# Copyright 2013 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from functools import partial
from operator import itemgetter
import tarfile

import matplotlib
from nose_parameterized import parameterized
import pandas as pd

from zipline import examples
from zipline.data.bundles import register, unregister
from zipline.testing import test_resource_path
from zipline.testing.fixtures import (
    WithTmpDir,
    ZiplineTestCase,
    read_checked_in_benchmark_data,
)
from zipline.testing.predicates import assert_equal
from zipline.utils.cache import dataframe_cache


# Otherwise the next line sometimes complains about being run too late.
_multiprocess_can_split_ = False

matplotlib.use('Agg')

EXAMPLE_MODULES = examples.load_example_modules()


class ExamplesTests(WithTmpDir, ZiplineTestCase):
    # some columns contain values with unique ids that will not be the same

    @classmethod
    def init_class_fixtures(cls):
        super(ExamplesTests, cls).init_class_fixtures()

        register('test', lambda *args: None)
        cls.add_class_callback(partial(unregister, 'test'))

        with tarfile.open(test_resource_path('example_data.tar.gz')) as tar:
            tar.extractall(cls.tmpdir.path)

        cls.expected_perf = dataframe_cache(
            cls.tmpdir.getpath(
                'example_data/expected_perf/%s' %
                pd.__version__.replace('.', '-'),
            ),
            serialization='pickle',
        )

        cls.benchmark_returns = read_checked_in_benchmark_data()

    @parameterized.expand(sorted(EXAMPLE_MODULES))
    def test_example(self, example_name):
        actual_perf = examples.run_example(
            EXAMPLE_MODULES,
            example_name,
            # This should match the invocation in
            # zipline/tests/resources/rebuild_example_data
            environ={
                'ZIPLINE_ROOT': self.tmpdir.getpath('example_data/root'),
            },
            benchmark_returns=self.benchmark_returns,
        )
        expected_perf = self.expected_perf[example_name]
        # Exclude positions column as the positions do not always have the
        # same order
        columns = [column for column in examples._cols_to_check
                   if column != 'positions']
        assert_equal(
            actual_perf[columns],
            expected_perf[columns],
            # There is a difference in the datetime columns in pandas
            # 0.16 and 0.17 because in 16 they are object and in 17 they are
            # datetime[ns, UTC]. We will just ignore the dtypes for now.
            check_dtype=False,
        )
        # Sort positions by SID before comparing
        assert_equal(
            expected_perf['positions'].apply(sorted, key=itemgetter('sid')),
            actual_perf['positions'].apply(sorted, key=itemgetter('sid')),
        )