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COMPAT: Use actual isinstance check for pyarrow.Array instead of hasattr(.. 'type') duck typing #52830

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Merged
merged 10 commits into from
Jun 2, 2023
Merged

COMPAT: Use actual isinstance check for pyarrow.Array instead of hasattr(.. 'type') duck typing #52830

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b501de7
Use actual isinstance check for pyarrow.Array instead of hasattr(.. '…
jorisvandenbossche Apr 21, 2023
0ffc29b
Merge remote-tracking branch 'upstream/main' into pyarrow-compat
jorisvandenbossche Apr 21, 2023
6ec3d34
fix import
jorisvandenbossche Apr 21, 2023
7bff616
Merge remote-tracking branch 'upstream/main' into pyarrow-compat
jorisvandenbossche Apr 28, 2023
3c88833
move to cython
jorisvandenbossche Apr 28, 2023
2448fd6
add docstring
jorisvandenbossche Apr 28, 2023
564c912
try TypeGuard
jorisvandenbossche Apr 28, 2023
2e92c5a
Merge remote-tracking branch 'upstream/main' into pyarrow-compat
jorisvandenbossche May 8, 2023
6999bec
Merge remote-tracking branch 'upstream/main' into pyarrow-compat
jorisvandenbossche May 31, 2023
c8aa952
remove ArrowArrayTypeGuard
jorisvandenbossche May 31, 2023
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2 changes: 2 additions & 0 deletions pandas/_libs/lib.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@ from pandas._libs.interval import Interval
from pandas._libs.tslibs import Period
from pandas._typing import (
ArrayLike,
ArrowArrayTypeGuard,
DtypeObj,
TypeGuard,
npt,
Expand All @@ -42,6 +43,7 @@ def infer_dtype(value: object, skipna: bool = ...) -> str: ...
def is_iterator(obj: object) -> bool: ...
def is_scalar(val: object) -> bool: ...
def is_list_like(obj: object, allow_sets: bool = ...) -> bool: ...
def is_pyarrow_array(obj: object) -> ArrowArrayTypeGuard: ...
def is_period(val: object) -> TypeGuard[Period]: ...
def is_interval(val: object) -> TypeGuard[Interval]: ...
def is_decimal(val: object) -> TypeGuard[Decimal]: ...
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23 changes: 23 additions & 0 deletions pandas/_libs/lib.pyx
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Expand Up @@ -145,6 +145,16 @@ i8max = <int64_t>INT64_MAX
u8max = <uint64_t>UINT64_MAX


cdef bint PYARROW_INSTALLED = False

try:
import pyarrow as pa

PYARROW_INSTALLED = True
except ImportError:
pa = None


@cython.wraparound(False)
@cython.boundscheck(False)
def memory_usage_of_objects(arr: object[:]) -> int64_t:
Expand Down Expand Up @@ -1173,6 +1183,19 @@ cdef bint c_is_list_like(object obj, bint allow_sets) except -1:
)


def is_pyarrow_array(obj):
"""
Return True if given object is a pyarrow Array or ChunkedArray.

Returns
-------
bool
"""
if PYARROW_INSTALLED:
return isinstance(obj, (pa.Array, pa.ChunkedArray))
return False


_TYPE_MAP = {
"categorical": "categorical",
"category": "categorical",
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11 changes: 11 additions & 0 deletions pandas/_typing.py
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Expand Up @@ -93,10 +93,21 @@
from typing import Self
else:
from typing_extensions import Self # pyright: reportUnusedImport = false

try:
from pyarrow import (
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IIUC we expect optional dependencies to be present for mypy checks, but not sure. who would know?

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Yes, that's also fine with me, that would just simplify this a bit.

Array,
ChunkedArray,
)

ArrowArrayTypeGuard = TypeGuard[Union[Array, ChunkedArray]]
except ImportError:
ArrowArrayTypeGuard = bool
else:
npt: Any = None
Self: Any = None
TypeGuard: Any = None
ArrowArrayTypeGuard = bool

HashableT = TypeVar("HashableT", bound=Hashable)

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2 changes: 1 addition & 1 deletion pandas/core/arrays/string_.py
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Expand Up @@ -356,7 +356,7 @@ def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy: bool = Fal
result[na_values] = libmissing.NA

else:
if hasattr(scalars, "type"):
if lib.is_pyarrow_array(scalars):
# pyarrow array; we cannot rely on the "to_numpy" check in
# ensure_string_array because calling scalars.to_numpy would set
# zero_copy_only to True which caused problems see GH#52076
Expand Down