ARROW-4181: [Python] Fixes for Numpy struct array conversion#3614
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pitrou wants to merge 1 commit intoapache:masterfrom
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ARROW-4181: [Python] Fixes for Numpy struct array conversion#3614pitrou wants to merge 1 commit intoapache:masterfrom
pitrou wants to merge 1 commit intoapache:masterfrom
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This fixes two issues: - object fields inside numpy structs should be allowed - buggy ndarray indexing if stride % itemsize != 0
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@pitrou You can test edge cases with hypothesis, like the following: import hypothesis as h
import hypothesis.extra.numpy as npst
supported_scalar_dtypes = (npst.boolean_dtypes() |
npst.integer_dtypes() |
npst.unsigned_integer_dtypes() |
npst.floating_dtypes() |
npst.datetime64_dtypes())
@h.given(
npst.arrays(npst.nested_dtypes(supported_scalar_dtypes), shape=(5,))
)
def test_nested_struct_array_from_numpy(numpy_array):
pa.array(numpy_array)
Or to test converting to pylist: import hypothesis as h
import pyarrow.tests.strategies as past
@h.given(
past.arrays(past.nested_struct_types())
)
def test_nested_pyarrow_array_to_pylist(pyarrow_array):
pyarrow_array.to_pylist()And run with: pytest -sv --enable-hypothesis --hypothesis-show-statistics --hypothesis-profile=devor to print the generated examples: pytest -sv --enable-hypothesis --hypothesis-show-statistics --hypothesis-profile=debug |
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Author
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When fixing a specific bug, I think I'd rather rely on manual testing and know exactly what's being tested. |
Member
|
Agree, just wanted to inform You about a handy way to discover bugs :) |
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This fixes two issues: