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DOC: set __module__ on remaining top-level functions #2

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8 changes: 8 additions & 0 deletions pandas/_config/config.py
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Expand Up @@ -944,3 +944,11 @@ def is_callable(obj: object) -> bool:
if not callable(obj):
raise ValueError("Value must be a callable")
return True


# import set_module here would cause circular import
get_option.__module__ = "pandas"
set_option.__module__ = "pandas"
describe_option.__module__ = "pandas"
reset_option.__module__ = "pandas"
option_context.__module__ = "pandas"
Comment on lines +949 to +954
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@q-dev-gamma-pdx-interstellar q-dev-gamma-pdx-interstellar bot Oct 30, 2025

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The changes made here are setting the __module__ attribute for several functions to "pandas". This is a good practice for ensuring that these functions are correctly associated with the pandas package. However, we should consider using the @set_module decorator for consistency and maintainability.

Suggested change
# import set_module here would cause circular import
get_option.__module__ = "pandas"
set_option.__module__ = "pandas"
describe_option.__module__ = "pandas"
reset_option.__module__ = "pandas"
option_context.__module__ = "pandas"
from pandas.util._decorators import set_module
@set_module("pandas")
def get_option(pat: str) -> Any:
...
@set_module("pandas")
def set_option(*args) -> None:
...
@set_module("pandas")
def describe_option(pat: str = "", _print_desc: bool = True) -> str | None:
...
@set_module("pandas")
def reset_option(pat: str) -> None:
...
@set_module("pandas")
def option_context(*args) -> Generator[None]:
...

9 changes: 9 additions & 0 deletions pandas/_libs/lib.pyx
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Expand Up @@ -41,6 +41,7 @@ from cython cimport (
from pandas._config import using_string_dtype

from pandas._libs.missing import check_na_tuples_nonequal
from pandas.util._decorators import set_module
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Good addition of the set_module import. This will help in setting the correct module for the decorated functions. However, we should consider applying this decorator consistently to all relevant functions in this file.


import_datetime()

Expand Down Expand Up @@ -154,6 +155,7 @@ def memory_usage_of_objects(arr: object[:]) -> int64_t:
# ----------------------------------------------------------------------


@set_module("pandas.api.types")
def is_scalar(val: object) -> bool:
Comment on lines +158 to 159
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The @set_module("pandas.api.types") decorator is correctly applied to the is_scalar function. This ensures that the function is properly associated with the pandas.api.types module. Consider applying this decorator consistently to all relevant functions in this file that should be part of the public API.

"""
Return True if given object is scalar.
Expand Down Expand Up @@ -255,6 +257,7 @@ cdef int64_t get_itemsize(object val):
return -1


@set_module("pandas.api.types")
def is_iterator(obj: object) -> bool:
Comment on lines +260 to 261
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The @set_module("pandas.api.types") decorator is correctly applied to the is_iterator function. This is consistent with the previous application to is_scalar. Ensure that all functions intended to be part of the public API are decorated similarly.

"""
Check if the object is an iterator.
Expand Down Expand Up @@ -1095,6 +1098,7 @@ def indices_fast(ndarray[intp_t, ndim=1] index, const int64_t[:] labels, list ke

# core.common import for fast inference checks

@set_module("pandas.api.types")
def is_float(obj: object) -> bool:
Comment on lines +1101 to 1102
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The @set_module("pandas.api.types") decorator is consistently applied to the is_float function here, and to other functions like is_integer, is_bool, is_complex, is_list_like, and infer_dtype in the subsequent changes. This is good practice and ensures these functions are correctly associated with the pandas.api.types module.

Consider reviewing the entire file to ensure all relevant functions that should be part of the public API are decorated appropriately. If there are functions intentionally left without the decorator, it might be helpful to add a comment explaining why they are not part of the public API.

"""
Return True if given object is float.
Expand Down Expand Up @@ -1128,6 +1132,7 @@ def is_float(obj: object) -> bool:
return util.is_float_object(obj)


@set_module("pandas.api.types")
def is_integer(obj: object) -> bool:
"""
Return True if given object is integer.
Expand Down Expand Up @@ -1172,6 +1177,7 @@ def is_int_or_none(obj) -> bool:
return obj is None or util.is_integer_object(obj)


@set_module("pandas.api.types")
def is_bool(obj: object) -> bool:
"""
Return True if given object is boolean.
Expand Down Expand Up @@ -1202,6 +1208,7 @@ def is_bool(obj: object) -> bool:
return util.is_bool_object(obj)


@set_module("pandas.api.types")
def is_complex(obj: object) -> bool:
"""
Return True if given object is complex.
Expand Down Expand Up @@ -1237,6 +1244,7 @@ cpdef bint is_decimal(object obj):
return isinstance(obj, Decimal)


@set_module("pandas.api.types")
def is_list_like(obj: object, allow_sets: bool = True) -> bool:
"""
Check if the object is list-like.
Expand Down Expand Up @@ -1520,6 +1528,7 @@ cdef object _try_infer_map(object dtype):
return None


@set_module("pandas.api.types")
def infer_dtype(value: object, skipna: bool = True) -> str:
"""
Return a string label of the type of the elements in a list-like input.
Expand Down
9 changes: 8 additions & 1 deletion pandas/_testing/asserters.py
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Expand Up @@ -17,7 +17,10 @@
import pandas._libs.testing as _testing
from pandas._libs.tslibs.np_datetime import compare_mismatched_resolutions
from pandas.errors import Pandas4Warning
from pandas.util._decorators import deprecate_kwarg
from pandas.util._decorators import (
deprecate_kwarg,
set_module,
)

from pandas.core.dtypes.common import (
is_bool,
Expand Down Expand Up @@ -181,6 +184,7 @@ def assert_dict_equal(left, right, compare_keys: bool = True) -> None:
_testing.assert_dict_equal(left, right, compare_keys=compare_keys)


@set_module("pandas.testing")
def assert_index_equal(
left: Index,
right: Index,
Expand Down Expand Up @@ -695,6 +699,7 @@ def _raise(left, right, err_msg) -> NoReturn:
assert_attr_equal("dtype", left, right, obj=obj)


@set_module("pandas.testing")
def assert_extension_array_equal(
left,
right,
Expand Down Expand Up @@ -850,6 +855,7 @@ def assert_extension_array_equal(


# This could be refactored to use the NDFrame.equals method
@set_module("pandas.testing")
@deprecate_kwarg(Pandas4Warning, "check_datetimelike_compat", new_arg_name=None)
def assert_series_equal(
left,
Expand Down Expand Up @@ -1143,6 +1149,7 @@ def assert_series_equal(


# This could be refactored to use the NDFrame.equals method
@set_module("pandas.testing")
@deprecate_kwarg(Pandas4Warning, "check_datetimelike_compat", new_arg_name=None)
def assert_frame_equal(
left,
Expand Down
8 changes: 7 additions & 1 deletion pandas/core/accessor.py
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Expand Up @@ -14,7 +14,10 @@
)
import warnings

from pandas.util._decorators import doc
from pandas.util._decorators import (
doc,
set_module,
)
from pandas.util._exceptions import find_stack_level

if TYPE_CHECKING:
Expand Down Expand Up @@ -323,6 +326,7 @@ def decorator(accessor: TypeT) -> TypeT:
dtype: int64"""


@set_module("pandas.api.extensions")
@doc(_register_accessor, klass="DataFrame", examples=_register_df_examples)
def register_dataframe_accessor(name: str) -> Callable[[TypeT], TypeT]:
from pandas import DataFrame
Expand Down Expand Up @@ -354,6 +358,7 @@ def register_dataframe_accessor(name: str) -> Callable[[TypeT], TypeT]:
np.int64(6)"""


@set_module("pandas.api.extensions")
@doc(_register_accessor, klass="Series", examples=_register_series_examples)
def register_series_accessor(name: str) -> Callable[[TypeT], TypeT]:
from pandas import Series
Expand Down Expand Up @@ -388,6 +393,7 @@ def register_series_accessor(name: str) -> Callable[[TypeT], TypeT]:
[2, 8]"""


@set_module("pandas.api.extensions")
@doc(_register_accessor, klass="Index", examples=_register_index_examples)
def register_index_accessor(name: str) -> Callable[[TypeT], TypeT]:
from pandas import Index
Expand Down
8 changes: 7 additions & 1 deletion pandas/core/algorithms.py
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Expand Up @@ -35,7 +35,10 @@
TakeIndexer,
npt,
)
from pandas.util._decorators import doc
from pandas.util._decorators import (
doc,
set_module,
)
from pandas.util._exceptions import find_stack_level

from pandas.core.dtypes.cast import (
Expand Down Expand Up @@ -325,6 +328,7 @@ def unique(values: T) -> T: ...
def unique(values: np.ndarray | Series) -> np.ndarray: ...


@set_module("pandas")
def unique(values):
"""
Return unique values based on a hash table.
Expand Down Expand Up @@ -649,6 +653,7 @@ def factorize_array(
return codes, uniques


@set_module("pandas")
@doc(
values=dedent(
"""\
Expand Down Expand Up @@ -1111,6 +1116,7 @@ def rank(
# ---- #


@set_module("pandas.api.extensions")
def take(
arr,
indices: TakeIndexer,
Expand Down
3 changes: 3 additions & 0 deletions pandas/core/col.py
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Expand Up @@ -9,6 +9,8 @@
Any,
)

from pandas.util._decorators import set_module

from pandas.core.series import Series

if TYPE_CHECKING:
Expand Down Expand Up @@ -222,6 +224,7 @@ def wrapper(*args: Any, **kwargs: Any) -> Expression:
return wrapper


@set_module("pandas")
def col(col_name: Hashable) -> Expression:
"""
Generate deferred object representing a column of a DataFrame.
Expand Down
2 changes: 2 additions & 0 deletions pandas/core/computation/eval.py
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Expand Up @@ -11,6 +11,7 @@
)
import warnings

from pandas.util._decorators import set_module
from pandas.util._exceptions import find_stack_level
from pandas.util._validators import validate_bool_kwarg

Expand Down Expand Up @@ -174,6 +175,7 @@ def _check_for_locals(expr: str, stack_level: int, parser: str) -> None:
raise SyntaxError(msg)


@set_module("pandas")
def eval(
expr: str | BinOp, # we leave BinOp out of the docstr bc it isn't for users
parser: str = "pandas",
Expand Down
2 changes: 2 additions & 0 deletions pandas/core/construction.py
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Expand Up @@ -23,6 +23,7 @@
get_supported_dtype,
is_supported_dtype,
)
from pandas.util._decorators import set_module

from pandas.core.dtypes.base import ExtensionDtype
from pandas.core.dtypes.cast import (
Expand Down Expand Up @@ -72,6 +73,7 @@
)


@set_module("pandas")
def array(
data: Sequence[object] | AnyArrayLike,
dtype: Dtype | None = None,
Expand Down
2 changes: 2 additions & 0 deletions pandas/core/dtypes/base.py
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Expand Up @@ -19,6 +19,7 @@
from pandas._libs.hashtable import object_hash
from pandas._libs.properties import cache_readonly
from pandas.errors import AbstractMethodError
from pandas.util._decorators import set_module

from pandas.core.dtypes.generic import (
ABCDataFrame,
Expand Down Expand Up @@ -480,6 +481,7 @@ def na_value(self) -> libmissing.NAType:
return libmissing.NA


@set_module("pandas.api.extensions")
def register_extension_dtype(cls: type_t[ExtensionDtypeT]) -> type_t[ExtensionDtypeT]:
"""
Register an ExtensionType with pandas as class decorator.
Expand Down
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