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GH-46606: [Python] Do not require numpy when normalizing slice #46732

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Merged
raulcd merged 7 commits into from
Jun 10, 2025
Merged

GH-46606: [Python] Do not require numpy when normalizing slice #46732

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50f9ec1
Changed from numpy Array to list(range(...))
shu-kitamura Jun 6, 2025
0758cb0
add test
shu-kitamura Jun 7, 2025
70c876e
fix test case
shu-kitamura Jun 7, 2025
acda29b
move test case
shu-kitamura Jun 7, 2025
44260b8
Add handling for empty list
shu-kitamura Jun 8, 2025
25904e9
delete test_slicing_with_non_trivial_step()
shu-kitamura Jun 9, 2025
9b3cb60
Fixed test cases to not use np.arange
shu-kitamura Jun 9, 2025
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4 changes: 3 additions & 1 deletion python/pyarrow/array.pxi
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Original file line number Diff line number Diff line change
Expand Up @@ -584,7 +584,9 @@ def _normalize_slice(object arrow_obj, slice key):
start, stop, step = key.indices(n)

if step != 1:
indices = np.arange(start, stop, step)
indices = list(range(start, stop, step))
if len(indices) == 0:
return arrow_obj.slice(0, 0)
return arrow_obj.take(indices)
else:
length = max(stop - start, 0)
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11 changes: 5 additions & 6 deletions python/pyarrow/tests/test_array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -488,15 +488,14 @@ def test_array_slice():
assert res.to_numpy().tolist() == expected


@pytest.mark.numpy
def test_array_slice_negative_step():
# ARROW-2714
np_arr = np.arange(20)
arr = pa.array(np_arr)
values = list(range(20))
arr = pa.array(values)
chunked_arr = pa.chunked_array([arr])

cases = [
slice(None, None, -1),
slice(None, None, -1), # GH-46606
slice(None, 6, -2),
slice(10, 6, -2),
slice(8, None, -2),
Expand All @@ -510,15 +509,15 @@ def test_array_slice_negative_step():

for case in cases:
result = arr[case]
expected = pa.array(np_arr[case])
expected = pa.array(values[case], type=arr.type)
assert result.equals(expected)

result = pa.record_batch([arr], names=['f0'])[case]
expected = pa.record_batch([expected], names=['f0'])
assert result.equals(expected)

result = chunked_arr[case]
expected = pa.chunked_array([np_arr[case]])
expected = pa.chunked_array([values[case]], type=arr.type)
assert result.equals(expected)


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