[Data] - Handle BaseMaskedDtype -> pa type in schema#57176
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alexeykudinkin merged 2 commits intoray-project:masterfrom Oct 6, 2025
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Signed-off-by: Goutam V. <goutam@anyscale.com>
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This pull request correctly addresses the conversion of pd.Int64Dtype to a pyarrow type. However, the implementation has a side effect that could lead to incorrect type conversion for other pandas masked dtypes like pd.BooleanDtype. I've provided a suggestion to make the conversion logic more robust by using duck typing and prioritizing the pyarrow_dtype attribute, which also avoids importing from a private pandas module. I've also suggested adding a test case to cover this scenario and prevent future regressions.
Signed-off-by: Goutam V. <goutam@anyscale.com>
iamjustinhsu
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| elif isinstance(dtype, pd.StringDtype): | ||
| # StringDtype is not a BaseMaskedDtype, handle separately | ||
| return pa.string() | ||
| elif isinstance(dtype, BaseMaskedDtype): | ||
| dtype = dtype.numpy_dtype | ||
| return pa.from_numpy_dtype(dtype) |
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Is this not handled by from_numpy_dtype
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No pd.ExtensionDtypes aren't handled by from_numpy_dtype
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In [1]: import pandas as pd
In [2]: x = pd.Float64Dtype()
In [3]: import pyarrow as pa
In [4]: pa.from_numpy_dtype(x)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[4], line 1
----> 1 pa.from_numpy_dtype(x)
File ~/Documents/ray/.venv/lib/python3.11/site-packages/pyarrow/types.pxi:5963, in pyarrow.lib.from_numpy_dtype()
TypeError: Cannot interpret 'Float64Dtype()' as a data type
In [5]: pa.from_numpy_dtype(x.numpy_dtype)
Out[5]: DataType(double)
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String example:
In [7]: x = pd.StringDtype()
In [8]: pa.from_numpy_dtype(x.numpy_dtype)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[8], line 1
----> 1 pa.from_numpy_dtype(x.numpy_dtype)
AttributeError: 'StringDtype' object has no attribute 'numpy_dtype'
alexeykudinkin
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Why are these changes needed?
If schema has
pd.Int64Dtype()thenpa.from_numpy_dtypefails. So in this change we extract the underlying numpy dtype from pandas then let pyarrow take over from there.Related issue number
Checks
git commit -s) in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.