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Merged
merged 5 commits into from
Mar 16, 2022
Merged

TST: Fix warnings & skip -> xfail #46370

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18dc4e3
TST: Fix warnings & skip -> xfail
mroeschke Mar 15, 2022
ca4293c
Remove uncessary super call
mroeschke Mar 15, 2022
6997b49
Address review
mroeschke Mar 15, 2022
29c3dcf
Add pytest asyncio
mroeschke Mar 15, 2022
a5f7706
Merge remote-tracking branch 'upstream/main' into tst/working
mroeschke Mar 15, 2022
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2 changes: 1 addition & 1 deletion pandas/tests/arrays/string_/test_string.py
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Expand Up @@ -523,7 +523,7 @@ def test_memory_usage(dtype):
# GH 33963

if dtype.storage == "pyarrow":
pytest.skip("not applicable")
pytest.skip(f"not applicable for {dtype.storage}")
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this is a never-expected-to-change thing, i.e. shouldnt be an xfail?

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I assume so since I think that would require a pyarrow API to get memory usage (didn't see one quickly skimming)


series = pd.Series(["a", "b", "c"], dtype=dtype)

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2 changes: 1 addition & 1 deletion pandas/tests/extension/base/ops.py
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Expand Up @@ -124,7 +124,7 @@ def test_direct_arith_with_ndframe_returns_not_implemented(self, data, box):
result = data.__add__(other)
assert result is NotImplemented
else:
raise pytest.skip(f"{type(data).__name__} does not implement add")
pytest.skip(f"{type(data).__name__} does not implement add")


class BaseComparisonOpsTests(BaseOpsUtil):
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4 changes: 2 additions & 2 deletions pandas/tests/extension/json/test_json.py
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Expand Up @@ -155,10 +155,10 @@ def test_contains(self, data):


class TestConstructors(BaseJSON, base.BaseConstructorsTests):
@pytest.mark.skip(reason="not implemented constructor from dtype")
@pytest.mark.xfail(reason="not implemented constructor from dtype")
def test_from_dtype(self, data):
# construct from our dtype & string dtype
pass
super(self).test_from_dtype(data)

@pytest.mark.xfail(reason="RecursionError, GH-33900")
def test_series_constructor_no_data_with_index(self, dtype, na_value):
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18 changes: 4 additions & 14 deletions pandas/tests/extension/test_categorical.py
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Expand Up @@ -50,7 +50,7 @@ def data():
"""Length-100 array for this type.
* data[0] and data[1] should both be non missing
* data[0] and data[1] should not gbe equal
* data[0] and data[1] should not be equal
"""
return Categorical(make_data())

Expand Down Expand Up @@ -86,7 +86,7 @@ class TestDtype(base.BaseDtypeTests):


class TestInterface(base.BaseInterfaceTests):
@pytest.mark.skip(reason="Memory usage doesn't match")
@pytest.mark.xfail(reason="Memory usage doesn't match")
def test_memory_usage(self, data):
# Is this deliberate?
super().test_memory_usage(data)
Expand Down Expand Up @@ -149,21 +149,15 @@ class TestIndex(base.BaseIndexTests):


class TestMissing(base.BaseMissingTests):
@pytest.mark.skip(reason="Not implemented")
def test_fillna_limit_pad(self, data_missing):
super().test_fillna_limit_pad(data_missing)

@pytest.mark.skip(reason="Not implemented")
def test_fillna_limit_backfill(self, data_missing):
super().test_fillna_limit_backfill(data_missing)
pass


class TestReduce(base.BaseNoReduceTests):
pass


class TestMethods(base.BaseMethodsTests):
@pytest.mark.skip(reason="Unobserved categories included")
@pytest.mark.xfail(reason="Unobserved categories included")
def test_value_counts(self, all_data, dropna):
return super().test_value_counts(all_data, dropna)

Expand All @@ -184,10 +178,6 @@ def test_combine_add(self, data_repeated):
expected = pd.Series([a + val for a in list(orig_data1)])
self.assert_series_equal(result, expected)

@pytest.mark.skip(reason="Not Applicable")
def test_fillna_length_mismatch(self, data_missing):
super().test_fillna_length_mismatch(data_missing)


class TestCasting(base.BaseCastingTests):
@pytest.mark.parametrize("cls", [Categorical, CategoricalIndex])
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4 changes: 1 addition & 3 deletions pandas/tests/extension/test_datetime.py
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Expand Up @@ -175,9 +175,7 @@ class TestMissing(BaseDatetimeTests, base.BaseMissingTests):


class TestReshaping(BaseDatetimeTests, base.BaseReshapingTests):
@pytest.mark.skip(reason="We have DatetimeTZBlock")
def test_concat(self, data, in_frame):
pass
pass


class TestSetitem(BaseDatetimeTests, base.BaseSetitemTests):
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24 changes: 13 additions & 11 deletions pandas/tests/extension/test_interval.py
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Expand Up @@ -121,9 +121,9 @@ def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):


class TestMethods(BaseInterval, base.BaseMethodsTests):
@pytest.mark.skip(reason="addition is not defined for intervals")
@pytest.mark.xfail(reason="addition is not defined for intervals")
def test_combine_add(self, data_repeated):
pass
super().test_combine_add(data_repeated)

@pytest.mark.xfail(
reason="Raises with incorrect message bc it disallows *all* listlikes "
Expand All @@ -134,29 +134,31 @@ def test_fillna_length_mismatch(self, data_missing):


class TestMissing(BaseInterval, base.BaseMissingTests):
# Index.fillna only accepts scalar `value`, so we have to skip all
# Index.fillna only accepts scalar `value`, so we have to xfail all
# non-scalar fill tests.
unsupported_fill = pytest.mark.skip("Unsupported fillna option.")
unsupported_fill = pytest.mark.xfail(
reason="Unsupported fillna option for Interval."
)

@unsupported_fill
def test_fillna_limit_pad(self):
pass
super().test_fillna_limit_pad()

@unsupported_fill
def test_fillna_series_method(self):
pass
super().test_fillna_series_method()

@unsupported_fill
def test_fillna_limit_backfill(self):
pass
super().test_fillna_limit_backfill()

@unsupported_fill
def test_fillna_no_op_returns_copy(self):
pass
super().test_fillna_no_op_returns_copy()

@unsupported_fill
def test_fillna_series(self):
pass
super().test_fillna_series()

def test_fillna_non_scalar_raises(self, data_missing):
msg = "can only insert Interval objects and NA into an IntervalArray"
Expand All @@ -173,9 +175,9 @@ class TestSetitem(BaseInterval, base.BaseSetitemTests):


class TestPrinting(BaseInterval, base.BasePrintingTests):
@pytest.mark.skip(reason="custom repr")
@pytest.mark.xfail(reason="Interval has custom repr")
def test_array_repr(self, data, size):
pass
super().test_array_repr()


class TestParsing(BaseInterval, base.BaseParsingTests):
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10 changes: 2 additions & 8 deletions pandas/tests/extension/test_numpy.py
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Expand Up @@ -208,10 +208,9 @@ def test_series_constructor_scalar_with_index(self, data, dtype):


class TestDtype(BaseNumPyTests, base.BaseDtypeTests):
@pytest.mark.skip(reason="Incorrect expected.")
# we unsurprisingly clash with a NumPy name.
@pytest.mark.skip(reason="PandasArray expectedly clashes with a NumPy name.")
def test_check_dtype(self, data):
pass
super().test_check_dtype(data)


class TestGetitem(BaseNumPyTests, base.BaseGetitemTests):
Expand Down Expand Up @@ -345,11 +344,6 @@ def test_fillna_frame(self, data_missing):


class TestReshaping(BaseNumPyTests, base.BaseReshapingTests):
@pytest.mark.skip(reason="Incorrect expected.")
def test_merge(self, data, na_value):
# Fails creating expected (key column becomes a PandasDtype because)
super().test_merge(data, na_value)

@pytest.mark.parametrize(
"in_frame",
[
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10 changes: 3 additions & 7 deletions pandas/tests/extension/test_string.py
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Expand Up @@ -26,7 +26,7 @@

def split_array(arr):
if arr.dtype.storage != "pyarrow":
pytest.skip("chunked array n/a")
pytest.skip("only applicable for pyarrow chunked array n/a")

def _split_array(arr):
import pyarrow as pa
Expand Down Expand Up @@ -156,13 +156,9 @@ def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):


class TestMethods(base.BaseMethodsTests):
@pytest.mark.skip(reason="returns nullable")
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yah really ought to pull the trigger on #44692 and just get internal consistency here

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Added that issue ref to this xfail

def test_value_counts(self, all_data, dropna):
return super().test_value_counts(all_data, dropna)

@pytest.mark.skip(reason="returns nullable")
@pytest.mark.xfail(reason="returns nullable")
def test_value_counts_with_normalize(self, data):
pass
super().test_value_counts_with_normalize(data)


class TestCasting(base.BaseCastingTests):
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7 changes: 3 additions & 4 deletions pandas/tests/plotting/frame/test_frame.py
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Expand Up @@ -146,12 +146,11 @@ def test_nullable_int_plot(self):
df = DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": [1.0, 2.0, 3.0, 4.0, 5.0],
"C": [7, 5, np.nan, 3, 2],
"B": [1, 2, 3, 4, 5],
"C": np.array([7, 5, np.nan, 3, 2], dtype=object),
"D": pd.to_datetime(dates, format="%Y").view("i8"),
"E": pd.to_datetime(dates, format="%Y", utc=True).view("i8"),
},
dtype=np.int64,
}
)

_check_plot_works(df.plot, x="A", y="B")
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2 changes: 1 addition & 1 deletion pandas/tests/plotting/test_converter.py
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Expand Up @@ -327,7 +327,7 @@ def test_conversion(self):

rs = self.pc.convert(
np.array(
["2012-01-01 00:00:00+0000", "2012-01-02 00:00:00+0000"],
["2012-01-01 00:00:00", "2012-01-02 00:00:00"],
dtype="datetime64[ns]",
),
None,
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1 change: 1 addition & 0 deletions pyproject.toml
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Expand Up @@ -56,6 +56,7 @@ markers = [
"arm_slow: mark a test as slow for arm64 architecture",
"arraymanager: mark a test to run with ArrayManager enabled",
]
asyncio_mode = "strict"
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where do we use asyncio?

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We have some tab completion tests that use this

(pandas-dev) ...  % grep --include="*.py" "async def" pandas/tests -r
pandas/tests/resample/test_resampler_grouper.py:async def test_tab_complete_ipython6_warning(ip):
pandas/tests/frame/test_api.py:    async def test_tab_complete_warning(self, ip, frame_or_series):
pandas/tests/arrays/categorical/test_warnings.py:    async def test_tab_complete_warning(self, ip):
pandas/tests/indexes/test_base.py:    async def test_tab_complete_warning(self, ip):


[tool.mypy]
# Import discovery
Expand Down