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BUG: avoid triggering numpy deprecation warning in assert functions for nested array with empty array/list #59778

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Sep 12, 2024
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BUG: avoid triggering numpy deprecation warning in assert functions for nested array with empty array/list #59778

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8e58fa6
BUG: avoid triggering numpy deprecation warning in assert functions f…
jorisvandenbossche Sep 11, 2024
591a455
remove expected warnings in tests
jorisvandenbossche Sep 11, 2024
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2 changes: 2 additions & 0 deletions pandas/_libs/lib.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -600,6 +600,8 @@ def array_equivalent_object(ndarray left, ndarray right) -> bool:
if not array_equivalent(x, y):
return False

elif PyArray_Check(x) or PyArray_Check(y):
return False
Comment on lines +603 to +604
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Below we would essentially do bool(left == right) which raises an error for arrays/lists of size > 1 (and that error would then be caught below, turned into return False. So for now, just directly returning False here when left or right is a numpy array and the other not.

That then avoids doing this bool(left == right) for empty array/list case, which triggers the warning.

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So for now, just directly returning False here when left or right is a numpy array and the other not.

Did you mean to use xor instead of or?

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The first if just before is if PyArray_Check(x) and PyArray_Check(y), so the or is sufficient

elif (x is C_NA) ^ (y is C_NA):
return False
elif not (
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12 changes: 1 addition & 11 deletions pandas/tests/dtypes/test_missing.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
from contextlib import nullcontext
from datetime import datetime
from decimal import Decimal

Expand All @@ -7,7 +6,6 @@

from pandas._libs import missing as libmissing
from pandas._libs.tslibs import iNaT
from pandas.compat.numpy import np_version_gte1p25

from pandas.core.dtypes.common import (
is_float,
Expand Down Expand Up @@ -458,15 +456,7 @@ def test_array_equivalent_dti(dtype_equal):
)
def test_array_equivalent_series(val):
arr = np.array([1, 2])
msg = "elementwise comparison failed"
cm = (
# stacklevel is chosen to make sense when called from .equals
tm.assert_produces_warning(FutureWarning, match=msg, check_stacklevel=False)
if isinstance(val, str) and not np_version_gte1p25
else nullcontext()
)
with cm:
assert not array_equivalent(Series([arr, arr]), Series([arr, val]))
assert not array_equivalent(Series([arr, arr]), Series([arr, val]))


def test_array_equivalent_array_mismatched_shape():
Expand Down
12 changes: 1 addition & 11 deletions pandas/tests/series/methods/test_equals.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,9 @@
from contextlib import nullcontext
import copy

import numpy as np
import pytest

from pandas._libs.missing import is_matching_na
from pandas.compat.numpy import np_version_gte1p25

from pandas.core.dtypes.common import is_float

Expand All @@ -14,7 +12,6 @@
MultiIndex,
Series,
)
import pandas._testing as tm


@pytest.mark.parametrize(
Expand Down Expand Up @@ -48,14 +45,7 @@ def test_equals_list_array(val):
assert s1.equals(s2)

s1[1] = val

cm = (
tm.assert_produces_warning(FutureWarning, check_stacklevel=False)
if isinstance(val, str) and not np_version_gte1p25
else nullcontext()
)
with cm:
assert not s1.equals(s2)
assert not s1.equals(s2)


def test_equals_false_negative():
Expand Down
4 changes: 4 additions & 0 deletions pandas/tests/util/test_assert_almost_equal.py
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Expand Up @@ -534,6 +534,10 @@ def test_assert_almost_equal_iterable_values_mismatch():
np.array([np.array([1, 2, 3]), np.array([4, 5])], dtype=object),
np.array([[1, 2, 3], [4, 5]], dtype=object),
),
(
np.array([np.array([], dtype=object), None], dtype=object),
np.array([[], None], dtype=object),
),
(
np.array(
[
Expand Down
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