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TST: tweak Hypothesis configuration and idioms #23441

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Merged
merged 2 commits into from
Nov 1, 2018
Merged

TST: tweak Hypothesis configuration and idioms #23441

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12bbac0
Adjust Hypothesis timeout settings
Zac-HD Nov 1, 2018
bf05e07
Define strategy as function, not method
Zac-HD Nov 1, 2018
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8 changes: 5 additions & 3 deletions pandas/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,10 +14,12 @@
hypothesis.settings.register_profile(
"ci",
# Hypothesis timing checks are tuned for scalars by default, so we bump
# them from 200ms to 5 secs per test case as the global default. If this
# them from 200ms to 500ms per test case as the global default. If this
# is too short for a specific test, (a) try to make it faster, and (b)
# if it really is slow add `@settings(timeout=...)` with a working value.
timeout=5000,
# if it really is slow add `@settings(deadline=...)` with a working value,
# or `deadline=None` to entirely disable timeouts for that test.
deadline=500,
timeout=hypothesis.unlimited,
suppress_health_check=(hypothesis.HealthCheck.too_slow,)
)
hypothesis.settings.load_profile("ci")
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29 changes: 15 additions & 14 deletions pandas/tests/frame/test_apply.py
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Expand Up @@ -823,6 +823,20 @@ def zip_frames(frames, axis=1):
return pd.DataFrame(zipped)


@composite
def indices(draw, max_length=5):
date = draw(
dates(
min_value=Timestamp.min.ceil("D").to_pydatetime().date(),
max_value=Timestamp.max.floor("D").to_pydatetime().date(),
).map(Timestamp)
)
periods = draw(integers(0, max_length))
freq = draw(sampled_from(list("BDHTS")))
dr = date_range(date, periods=periods, freq=freq)
return pd.DatetimeIndex(list(dr))


class TestDataFrameAggregate():

def test_agg_transform(self, axis, float_frame):
Expand Down Expand Up @@ -1142,20 +1156,7 @@ def test_agg_cython_table_raises(self, df, func, expected, axis):
with pytest.raises(expected):
df.agg(func, axis=axis)

@composite
def indices(draw, max_length=5):
date = draw(
dates(
min_value=Timestamp.min.ceil("D").to_pydatetime().date(),
max_value=Timestamp.max.floor("D").to_pydatetime().date(),
).map(Timestamp)
)
periods = draw(integers(0, max_length))
freq = draw(sampled_from(list("BDHTS")))
dr = date_range(date, periods=periods, freq=freq)
return pd.DatetimeIndex(list(dr))

@given(index=indices(5), num_columns=integers(0, 5))
@given(index=indices(max_length=5), num_columns=integers(0, 5))
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Generally, we would prefer that separate changes go into separate PR's, but these are small enough that it should be okay.

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It's kinda related in that this is input to the test that was timing out, but point taken - I'll try to split future changes like this into multiple PRs 😄

def test_frequency_is_original(self, index, num_columns):
# GH 22150
original = index.copy()
Expand Down