DOC: set __module__ on remaining top-level functions

pandas/_config/config.py

@@ -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"

pandas/_libs/lib.pyx

@@ -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
 
 import_datetime()
 
@@ -154,6 +155,7 @@ def memory_usage_of_objects(arr: object[:]) -> int64_t:
 # ----------------------------------------------------------------------
 
 
+@set_module("pandas.api.types")
 def is_scalar(val: object) -> bool:
     """
     Return True if given object is scalar.
@@ -255,6 +257,7 @@ cdef int64_t get_itemsize(object val):
         return -1
 
 
+@set_module("pandas.api.types")
 def is_iterator(obj: object) -> bool:
     """
     Check if the object is an iterator.
@@ -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:
     """
     Return True if given object is float.
@@ -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.
@@ -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.
@@ -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.
@@ -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.
@@ -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.

pandas/_testing/asserters.py

@@ -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,
@@ -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,
@@ -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,
@@ -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,
@@ -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,

pandas/core/accessor.py

@@ -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:
@@ -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
@@ -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
@@ -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

pandas/core/algorithms.py

@@ -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 (
@@ -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.
@@ -649,6 +653,7 @@ def factorize_array(
     return codes, uniques
 
 
+@set_module("pandas")
 @doc(
     values=dedent(
         """\
@@ -1111,6 +1116,7 @@ def rank(
 # ---- #
 
 
+@set_module("pandas.api.extensions")
 def take(
     arr,
     indices: TakeIndexer,

pandas/core/col.py

@@ -9,6 +9,8 @@
     Any,
 )
 
+from pandas.util._decorators import set_module
+
 from pandas.core.series import Series
 
 if TYPE_CHECKING:
@@ -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.

pandas/core/computation/eval.py

@@ -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
 
@@ -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",

pandas/core/construction.py

@@ -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 (
@@ -72,6 +73,7 @@
     )
 
 
+@set_module("pandas")
 def array(
     data: Sequence[object] | AnyArrayLike,
     dtype: Dtype | None = None,

pandas/core/dtypes/base.py

@@ -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,
@@ -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.