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TYP: misc fixes for numpy types #36098

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Sep 5, 2020
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TYP: misc fixes for numpy types #36098

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TYP: misc fixes for numpy types
simonjayhawkins Sep 3, 2020
5325e20
more fixes
simonjayhawkins Sep 3, 2020
db640fa
isort
simonjayhawkins Sep 3, 2020
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2 changes: 1 addition & 1 deletion pandas/_typing.py
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Expand Up @@ -62,7 +62,7 @@
# other

Dtype = Union[
"ExtensionDtype", str, np.dtype, Type[Union[str, float, int, complex, bool]]
"ExtensionDtype", str, np.dtype, Type[Union[str, float, int, complex, bool, object]]
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object here is for when we use object as a shorthand for np.dtype(object)?

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yep, but Dtype is also used to type the public facing api. ideally we don't want object here, but we don't want users to have false positives either. saying that we have not yet come to an agreement on how we will make the types public. see #28142

]
DtypeObj = Union[np.dtype, "ExtensionDtype"]
FilePathOrBuffer = Union[str, Path, IO[AnyStr], IOBase]
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7 changes: 3 additions & 4 deletions pandas/core/algorithms.py
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Expand Up @@ -6,7 +6,7 @@

import operator
from textwrap import dedent
from typing import TYPE_CHECKING, Dict, Optional, Tuple, Union
from typing import TYPE_CHECKING, Dict, Optional, Tuple, Union, cast
from warnings import catch_warnings, simplefilter, warn

import numpy as np
Expand Down Expand Up @@ -60,7 +60,7 @@
from pandas.core.indexers import validate_indices

if TYPE_CHECKING:
from pandas import DataFrame, Series
from pandas import Categorical, DataFrame, Series

_shared_docs: Dict[str, str] = {}

Expand Down Expand Up @@ -429,8 +429,7 @@ def isin(comps: AnyArrayLike, values: AnyArrayLike) -> np.ndarray:
if is_categorical_dtype(comps):
# TODO(extension)
# handle categoricals
# error: "ExtensionArray" has no attribute "isin" [attr-defined]
return comps.isin(values) # type: ignore[attr-defined]
return cast("Categorical", comps).isin(values)

comps, dtype = _ensure_data(comps)
values, _ = _ensure_data(values, dtype=dtype)
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2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Expand Up @@ -2316,7 +2316,7 @@ def _concat_same_type(self, to_concat):

return union_categoricals(to_concat)

def isin(self, values):
def isin(self, values) -> np.ndarray:
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so here we know that this returns a bool dtyped ndarray, is it worth somehow annotating this as such?

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IIRC there has been some discussion in numpy about making it viable to annotate something like np.ndarray[bool], but it is still hypothetical (cc @shoyer?)

"""
Check whether `values` are contained in Categorical.

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6 changes: 4 additions & 2 deletions pandas/core/construction.py
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Expand Up @@ -335,7 +335,7 @@ def array(
return result


def extract_array(obj, extract_numpy: bool = False):
def extract_array(obj: AnyArrayLike, extract_numpy: bool = False) -> ArrayLike:
"""
Extract the ndarray or ExtensionArray from a Series or Index.

Expand Down Expand Up @@ -383,7 +383,9 @@ def extract_array(obj, extract_numpy: bool = False):
if extract_numpy and isinstance(obj, ABCPandasArray):
obj = obj.to_numpy()

return obj
# error: Incompatible return value type (got "Index", expected "ExtensionArray")
# error: Incompatible return value type (got "Series", expected "ExtensionArray")
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Could we avoid this by assigning to a new name before returning?

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I'll look some more, but we are using ABC types here which always create issues with eliminating types so I just added the ignore for now so that the return types can be added.

return obj # type: ignore[return-value]


def sanitize_array(
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4 changes: 2 additions & 2 deletions pandas/core/dtypes/cast.py
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Expand Up @@ -1488,7 +1488,7 @@ def find_common_type(types: List[DtypeObj]) -> DtypeObj:
if has_bools:
for t in types:
if is_integer_dtype(t) or is_float_dtype(t) or is_complex_dtype(t):
return object
return np.dtype("object")

return np.find_common_type(types, [])

Expand Down Expand Up @@ -1550,7 +1550,7 @@ def construct_1d_arraylike_from_scalar(
elif isinstance(dtype, np.dtype) and dtype.kind in ("U", "S"):
# we need to coerce to object dtype to avoid
# to allow numpy to take our string as a scalar value
dtype = object
dtype = np.dtype("object")
if not isna(value):
value = ensure_str(value)

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