REF: Parametrize value_counts tests #28537
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Not sure about reducing the number of cases. Looking into the history of
the test may shed some light.
…On Thu, Sep 19, 2019 at 3:03 PM Daniel Saxton ***@***.***> wrote:
Parametrizes the for loop in test_series_groupby_value_counts. As a side
note, this test seems to run for a pretty long time (a minute and a half);
should it operate on less data perhaps?
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#28537
Commit Summary
- REF: Parametrize value_counts tests
File Changes
- *M* pandas/tests/groupby/test_value_counts.py
<https://github.com/pandas-dev/pandas/pull/28537/files#diff-0> (35)
Patch Links:
- https://github.com/pandas-dev/pandas/pull/28537.patch
- https://github.com/pandas-dev/pandas/pull/28537.diff
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Yea a minute and a half for one test is too much. Is there a way to get it down to a few seconds and still get the same measurement? |
WillAyd
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Testing
WillAyd
requested changes
Sep 20, 2019
| @@ -52,29 +52,28 @@ def seed_df(seed_nans, n, m): | |||
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| @pytest.mark.slow | |||
| @pytest.mark.parametrize("df, keys, bins, n, m", binned, ids=ids) | |||
| def test_series_groupby_value_counts(df, keys, bins, n, m): | |||
| @pytest.mark.parametrize( | |||
| "isort, normalize, sort, ascending, dropna", list(product((False, True), repeat=5)) | |||
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Not really a fan of using itertools to generate parametrization. Could you instead write this as:
@pytest.mark.parametrize("isort", [True, False])
@pytest.mark.parametrize("normalize", [True, False])
...Equivalent at the end of the day but I think clearer and match the rest of the codebase
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this is a comprehensive test and is marked as slow, so perf is ok, other than @WillAyd comment lgtm. |
WillAyd
approved these changes
Sep 20, 2019
|
Thanks @dsaxton |
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Parametrizes the for loop in
test_series_groupby_value_counts. As a side note, this test seems to run for a pretty long time (a minute and a half); should it operate on less data perhaps?