TYP: fix ignores #40389
TYP: fix ignores #40389
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Thanks @jbrockmendel will push a merge master since there are still mypy errors here to resolve.
| vals = vals.to_numpy( # type: ignore[attr-defined] | ||
| dtype=float, na_value=np.nan | ||
| ) | ||
| if isinstance(vals, ExtensionArray): |
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the function signature has vals: np.ndarray. also needs updating
| @@ -2271,28 +2271,18 @@ def pre_processor(vals: np.ndarray) -> Tuple[np.ndarray, Optional[Type]]: | |||
| "'quantile' cannot be performed against 'object' dtypes!" | |||
| ) | |||
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| inference = None | |||
| inference: Optional[np.dtype] = None | |||
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the return type is Tuple[np.ndarray, Optional[Type]] in the function signature. so that can also now be narrowed.
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was needed anyway for mypy fixup
pandas/core/reshape/reshape.py
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| @@ -166,7 +170,7 @@ def _make_selectors(self): | |||
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| comp_index = ensure_platform_int(comp_index) | |||
| stride = self.index.levshape[self.level] + self.lift | |||
| self.full_shape = ngroups, stride | |||
| self.full_shape = ngroups, int(stride) # int() for mypy | |||
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we probably don't want to be casting numpy integer types to python ints just to appease mypy. We probably need an int-like alias to use where we currently use int in type annotations.
I think better to leave this unchanged until we've had that discussion.
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sounds good, will revert
| def _reorder_for_extension_array_stack(arr, n_rows: int, n_columns: int): | ||
| def _reorder_for_extension_array_stack( | ||
| arr: ExtensionArray, n_rows: int, n_columns: int | ||
| ) -> ExtensionArray: |
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probably should be a typevar. but also ok to leave as is for now if not needed as this is internal
| @@ -52,7 +51,7 @@ def get_indexer_indexer( | |||
| na_position: str, | |||
| sort_remaining: bool, | |||
| key: IndexKeyFunc, | |||
| ) -> Optional[np.array]: # type: ignore[valid-type] | |||
| ) -> Optional[np.ndarray]: | |||
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you found the bonus low hanger! 😄
pandas/core/tools/datetimes.py
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| @@ -534,25 +534,19 @@ def _to_datetime_with_unit(arg, unit, name, tz, errors: Optional[str]) -> Index: | |||
| # GH#30050 pass an ndarray to tslib.array_with_unit_to_datetime | |||
| # because it expects an ndarray argument | |||
| if isinstance(arg, IntegerArray): | |||
| result = arg.astype(f"datetime64[{unit}]") | |||
| res = arg.astype(f"datetime64[{unit}]") | |||
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nitpick: res-> arr (I think once the type is added for arg in the signature, we will get an Incompatible types in assignment in arg = getattr(arg, "_values", arg) anyway.
| # error: Incompatible types in assignment (expression has type "TimedeltaIndex", | ||
| # variable has type "ndarray") | ||
| value = TimedeltaIndex(value, unit="ns", name=name) # type: ignore[assignment] | ||
| value = TimedeltaIndex(td64arr, unit="ns", name=name) |
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could also return TimedeltaIndex ... without the intermediate assignment, but the td64arr naming is also an improvement anyway.
i get a bunch of noise in my local mypy output, so will have to see what the CI says