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TYP: stricter typing of return value of to_numpy_dtype_inference helper function #62284

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Merged
merged 4 commits into from
Sep 8, 2025
Merged

TYP: stricter typing of return value of to_numpy_dtype_inference helper function #62284

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7841851
TYP: stricter typing of return value of to_numpy_dtype_inference help…
jorisvandenbossche Sep 7, 2025
7a8b93a
fixup
jorisvandenbossche Sep 8, 2025
0710ea4
add back ignore for numpy_dtype
jorisvandenbossche Sep 8, 2025
f72c7e6
input is always EA
jorisvandenbossche Sep 8, 2025
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40 changes: 21 additions & 19 deletions pandas/core/arrays/_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,49 +15,51 @@

if TYPE_CHECKING:
from pandas._typing import (
ArrayLike,
npt,
)

from pandas.core.arrays.base import ExtensionArray


def to_numpy_dtype_inference(
arr: ArrayLike, dtype: npt.DTypeLike | None, na_value, hasna: bool
) -> tuple[npt.DTypeLike, Any]:
arr: ExtensionArray, dtype: npt.DTypeLike | None, na_value, hasna: bool
) -> tuple[np.dtype | None, Any]:
result_dtype: np.dtype | None
inferred_numeric_dtype = False
if dtype is None and is_numeric_dtype(arr.dtype):
dtype_given = False
inferred_numeric_dtype = True
if hasna:
if arr.dtype.kind == "b":
dtype = np.dtype(np.object_)
result_dtype = np.dtype(np.object_)
else:
if arr.dtype.kind in "iu":
dtype = np.dtype(np.float64)
result_dtype = np.dtype(np.float64)
else:
dtype = arr.dtype.numpy_dtype # type: ignore[union-attr]
result_dtype = arr.dtype.numpy_dtype # type: ignore[attr-defined]
if na_value is lib.no_default:
na_value = np.nan
else:
dtype = arr.dtype.numpy_dtype # type: ignore[union-attr]
result_dtype = arr.dtype.numpy_dtype # type: ignore[attr-defined]
elif dtype is not None:
dtype = np.dtype(dtype)
dtype_given = True
result_dtype = np.dtype(dtype)
else:
dtype_given = True
result_dtype = None

if na_value is lib.no_default:
if dtype is None or not hasna:
if result_dtype is None or not hasna:
na_value = arr.dtype.na_value
elif dtype.kind == "f": # type: ignore[union-attr]
elif result_dtype.kind == "f":
na_value = np.nan
elif dtype.kind == "M": # type: ignore[union-attr]
elif result_dtype.kind == "M":
na_value = np.datetime64("nat")
elif dtype.kind == "m": # type: ignore[union-attr]
elif result_dtype.kind == "m":
na_value = np.timedelta64("nat")
else:
na_value = arr.dtype.na_value

if not dtype_given and hasna:
if inferred_numeric_dtype and hasna:
try:
np_can_hold_element(dtype, na_value) # type: ignore[arg-type]
np_can_hold_element(result_dtype, na_value) # type: ignore[arg-type]
except LossySetitemError:
dtype = np.dtype(np.object_)
return dtype, na_value
result_dtype = np.dtype(np.object_)
return result_dtype, na_value
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