some helpers for working with pandas data frames in a conda environment
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""" Stub file for testing the project
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There are three predefined ways to run tests:
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make test:
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runs only unit tests, that are not marked with "fun" (for functional test)
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in a random order. If a test failed before, only the failed tests will be
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run. This is intended to be the default testing method while developing.
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make testall:
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runs unit tests and functional tests in random order. Will give a complete
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overview of the test suite.
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make coverage:
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runs only tests marked with "fun" (for functional tests) and generates a
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coverage report for the test run. The idea is to check the test coverage
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only on functinal tests to see if a) everything is as much covered as
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possible and b) to find dead code that is not called in end-to-end tests.
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all three test strategies will run "make lint" before to catch easily made
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mistakes.
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"""
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def test_api():
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from conda_helpers import (
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add_exposure_info, # noqa: F401
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iter_uniques, # noqa: F401
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linear_regression, # noqa: F401
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normalize, # noqa: F401
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select, # noqa: F401
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)
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