TYP: numpy._NoValue
#29170
Merged
TYP: numpy._NoValue
#29170
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Diff from mypy_primer, showing the effect of this PR on type check results on a corpus of open source code: spark (https://github.com/apache/spark)
+ python/pyspark/pandas/series.py:1170: error: Unused "type: ignore" comment [unused-ignore]
+ python/pyspark/pandas/series.py:1170: error: No overload variant of "__getitem__" of "Series" matches argument type "_NoValueType" [call-overload]
+ python/pyspark/pandas/series.py:1170: note: Error code "call-overload" not covered by "type: ignore" comment
+ python/pyspark/pandas/series.py:1170: note: Possible overload variants:
+ python/pyspark/pandas/series.py:1170: note: def __getitem__(self, list[str] | Index[Any] | Series[float] | slice[Any, Any, Any] | Series[builtins.bool] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | tuple[Hashable | slice[Any, Any, Any], ...], /) -> Series[float]
+ python/pyspark/pandas/series.py:1170: note: def __getitem__(self, str | bytes | date | datetime | timedelta | <7 more items> | complex | integer[Any] | floating[Any] | complexfloating[Any, Any], /) -> float
+ python/pyspark/pandas/series.py:1172: error: Unused "type: ignore" comment [unused-ignore]
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Here's the tmp_val = arg[np._NoValue] # type: ignore[attr-defined]
# Remove in case it's set in defaultdict.
del arg[np._NoValue] # type: ignore[attr-defined]The new error (and the two resolved ones) make sense to me (since a |
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Thanks Joren. |
This was referenced Jun 12, 2025
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This adds implicit re-exports for
numpy._globals._NoValueand_CopyModeto__init__.pyi. They're available at runtime, so the stubs should reflect that (even though it's not public API), IMO.This gets rid of a bunch of red sguigglies in the internal python codebase, e.g. in
lib/_function_base_impl.pythere are references to_NoValue.