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fix(python): Handle generalized ufunc edge cases better #16086
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e0b505f
Tests for expected behavior in generalized ufunc edge cases.
pythonspeed 04afbeb
Disallow calling generalized ufuncs if data is missing.
pythonspeed 782998a
WIP sketch of supporting output size different than input.
pythonspeed ff80578
ufunc tests pass again.
pythonspeed ab4f0a1
Bit more testing.
pythonspeed 144192e
Lint fixes.
pythonspeed fe58184
Delete copy/paste error.
pythonspeed 70194b0
Add Numba as a dependency.
pythonspeed d9e555d
Switch to ComputeError.
pythonspeed 3672eac
A bit more testing.
pythonspeed 8ff6106
Reformat.
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Original file line number | Diff line number | Diff line change |
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""" | ||
Infrastructure for testing Numba. | ||
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Numba releases often lag for a few months after Python releases, so we don't | ||
want Numba to be a blocker for Python 3.X support. So this minimally emulates | ||
the Numba module, while allowing for the fact that Numba may not be installed. | ||
""" | ||
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import pytest | ||
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try: | ||
from numba import float64, guvectorize # type: ignore[import-untyped] | ||
except ImportError: | ||
float64 = [] | ||
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def guvectorize(_a, _b): # type: ignore[no-untyped-def] | ||
"""When Numba is unavailable, skip tests using the decorated function.""" | ||
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def decorator(_): # type: ignore[no-untyped-def] | ||
def skip(*_args, **_kwargs): # type: ignore[no-untyped-def] | ||
pytest.skip("Numba not available") | ||
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return skip | ||
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return decorator | ||
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__all__ = ["guvectorize", "float64"] |
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It's not really testing Expr.array_ufunc if you use map_batches. I was thinking tests like
df.select(gufunc_mean(pl.col('s')).alias('result')
That said, I don't think you need to put those tests in this PR as it's only tangentially related.There was a problem hiding this comment.
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OK.