TYP: libs

pandas/_libs/join.pyi

@@ -1,51 +1,53 @@
 import numpy as np
 
+from pandas._typing import npt
+
 def inner_join(
     left: np.ndarray,  # const intp_t[:]
     right: np.ndarray,  # const intp_t[:]
     max_groups: int,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def left_outer_join(
     left: np.ndarray,  # const intp_t[:]
     right: np.ndarray,  # const intp_t[:]
     max_groups: int,
     sort: bool = True,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def full_outer_join(
     left: np.ndarray,  # const intp_t[:]
     right: np.ndarray,  # const intp_t[:]
     max_groups: int,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def ffill_indexer(
     indexer: np.ndarray,  # const intp_t[:]
-) -> np.ndarray: ...  # np.ndarray[np.intp]
+) -> npt.NDArray[np.intp]: ...
 def left_join_indexer_unique(
     left: np.ndarray,  # ndarray[join_t]
     right: np.ndarray,  # ndarray[join_t]
-) -> np.ndarray: ...  # np.ndarray[np.intp]
+) -> npt.NDArray[np.intp]: ...
 def left_join_indexer(
     left: np.ndarray,  # ndarray[join_t]
     right: np.ndarray,  # ndarray[join_t]
 ) -> tuple[
     np.ndarray,  # np.ndarray[join_t]
-    np.ndarray,  # np.ndarray[np.intp]
-    np.ndarray,  # np.ndarray[np.intp]
+    npt.NDArray[np.intp],
+    npt.NDArray[np.intp],
 ]: ...
 def inner_join_indexer(
     left: np.ndarray,  # ndarray[join_t]
     right: np.ndarray,  # ndarray[join_t]
 ) -> tuple[
     np.ndarray,  # np.ndarray[join_t]
-    np.ndarray,  # np.ndarray[np.intp]
-    np.ndarray,  # np.ndarray[np.intp]
+    npt.NDArray[np.intp],
+    npt.NDArray[np.intp],
 ]: ...
 def outer_join_indexer(
     left: np.ndarray,  # ndarray[join_t]
     right: np.ndarray,  # ndarray[join_t]
 ) -> tuple[
     np.ndarray,  # np.ndarray[join_t]
-    np.ndarray,  # np.ndarray[np.intp]
-    np.ndarray,  # np.ndarray[np.intp]
+    npt.NDArray[np.intp],
+    npt.NDArray[np.intp],
 ]: ...
 def asof_join_backward_on_X_by_Y(
     left_values: np.ndarray,  # asof_t[:]
@@ -54,38 +56,38 @@ def asof_join_backward_on_X_by_Y(
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_forward_on_X_by_Y(
     left_values: np.ndarray,  # asof_t[:]
     right_values: np.ndarray,  # asof_t[:]
     left_by_values: np.ndarray,  # by_t[:]
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_nearest_on_X_by_Y(
     left_values: np.ndarray,  # asof_t[:]
     right_values: np.ndarray,  # asof_t[:]
     left_by_values: np.ndarray,  # by_t[:]
     right_by_values: np.ndarray,  # by_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_backward(
     left_values: np.ndarray,  # asof_t[:]
     right_values: np.ndarray,  # asof_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_forward(
     left_values: np.ndarray,  # asof_t[:]
     right_values: np.ndarray,  # asof_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...
 def asof_join_nearest(
     left_values: np.ndarray,  # asof_t[:]
     right_values: np.ndarray,  # asof_t[:]
     allow_exact_matches: bool = True,
     tolerance=None,
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.intp]  # np.ndarray[np.intp]
+) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ...

pandas/_libs/lib.pyi

@@ -14,6 +14,7 @@ import numpy as np
 from pandas._typing import (
     ArrayLike,
     DtypeObj,
+    npt,
 )
 
 # placeholder until we can specify np.ndarray[object, ndim=2]
@@ -63,7 +64,7 @@ def map_infer(
 ) -> np.ndarray: ...
 @overload  # both convert_datetime and convert_to_nullable_integer False -> np.ndarray
 def maybe_convert_objects(
-    objects: np.ndarray,  # np.ndarray[object]
+    objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
@@ -76,7 +77,7 @@ def maybe_convert_objects(
 ) -> np.ndarray: ...
 @overload
 def maybe_convert_objects(
-    objects: np.ndarray,  # np.ndarray[object]
+    objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
@@ -89,7 +90,7 @@ def maybe_convert_objects(
 ) -> ArrayLike: ...
 @overload
 def maybe_convert_objects(
-    objects: np.ndarray,  # np.ndarray[object]
+    objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
@@ -102,7 +103,7 @@ def maybe_convert_objects(
 ) -> ArrayLike: ...
 @overload
 def maybe_convert_objects(
-    objects: np.ndarray,  # np.ndarray[object]
+    objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
@@ -115,7 +116,7 @@ def maybe_convert_objects(
 ) -> ArrayLike: ...
 @overload
 def maybe_convert_objects(
-    objects: np.ndarray,  # np.ndarray[object]
+    objects: npt.NDArray[np.object_],
     *,
     try_float: bool = ...,
     safe: bool = ...,
@@ -128,15 +129,15 @@ def maybe_convert_objects(
 ) -> ArrayLike: ...
 @overload
 def maybe_convert_numeric(
-    values: np.ndarray,  # np.ndarray[object]
+    values: npt.NDArray[np.object_],
     na_values: set,
     convert_empty: bool = True,
     coerce_numeric: bool = False,
     convert_to_masked_nullable: Literal[False] = ...,
 ) -> tuple[np.ndarray, None]: ...
 @overload
 def maybe_convert_numeric(
-    values: np.ndarray,  # np.ndarray[object]
+    values: npt.NDArray[np.object_],
     na_values: set,
     convert_empty: bool = True,
     coerce_numeric: bool = False,
@@ -151,32 +152,32 @@ def ensure_string_array(
     convert_na_value: bool = True,
     copy: bool = True,
     skipna: bool = True,
-) -> np.ndarray: ...  # np.ndarray[object]
+) -> npt.NDArray[np.object_]: ...
 def infer_datetimelike_array(
-    arr: np.ndarray,  # np.ndarray[object]
+    arr: npt.NDArray[np.object_],
 ) -> tuple[str, bool]: ...
 def astype_intsafe(
-    arr: np.ndarray,  # np.ndarray[object]
+    arr: npt.NDArray[np.object_],
     new_dtype: np.dtype,
 ) -> np.ndarray: ...
-def fast_zip(ndarrays: list) -> np.ndarray: ...  # np.ndarray[object]
+def fast_zip(ndarrays: list) -> npt.NDArray[np.object_]: ...
 
 # TODO: can we be more specific about rows?
 def to_object_array_tuples(rows: object) -> ndarray_obj_2d: ...
 def tuples_to_object_array(
-    tuples: np.ndarray,  # np.ndarray[object]
+    tuples: npt.NDArray[np.object_],
 ) -> ndarray_obj_2d: ...
 
 # TODO: can we be more specific about rows?
 def to_object_array(rows: object, min_width: int = 0) -> ndarray_obj_2d: ...
 def dicts_to_array(dicts: list, columns: list) -> ndarray_obj_2d: ...
 def maybe_booleans_to_slice(
-    mask: np.ndarray,  # ndarray[uint8_t]
-) -> slice | np.ndarray: ...  # np.ndarray[np.uint8]
+    mask: npt.NDArray[np.uint8],
+) -> slice | npt.NDArray[np.uint8]: ...
 def maybe_indices_to_slice(
-    indices: np.ndarray,  # np.ndarray[np.intp]
+    indices: npt.NDArray[np.intp],
     max_len: int,
-) -> slice | np.ndarray: ...  # np.ndarray[np.uint8]
+) -> slice | npt.NDArray[np.intp]: ...
 def is_all_arraylike(obj: list) -> bool: ...
 
 # -----------------------------------------------------------------
@@ -192,14 +193,14 @@ def map_infer_mask(
     dtype: np.dtype = ...,
 ) -> np.ndarray: ...
 def indices_fast(
-    index: np.ndarray,  # ndarray[intp_t]
+    index: npt.NDArray[np.intp],
     labels: np.ndarray,  # const int64_t[:]
     keys: list,
-    sorted_labels: list[np.ndarray],  # list[ndarray[np.int64]]
+    sorted_labels: list[npt.NDArray[np.int64]],
 ) -> dict: ...
 def generate_slices(
     labels: np.ndarray, ngroups: int  # const intp_t[:]
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.int64]  # np.ndarray[np.int64]
+) -> tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]: ...
 def count_level_2d(
     mask: np.ndarray,  # ndarray[uint8_t, ndim=2, cast=True],
     labels: np.ndarray,  # const intp_t[:]
@@ -211,7 +212,7 @@ def get_level_sorter(
     starts: np.ndarray,  # const intp_t[:]
 ) -> np.ndarray: ...  #  np.ndarray[np.intp, ndim=1]
 def generate_bins_dt64(
-    values: np.ndarray,  # np.ndarray[np.int64]
+    values: npt.NDArray[np.int64],
     binner: np.ndarray,  # const int64_t[:]
     closed: object = "left",
     hasnans: bool = False,
@@ -224,5 +225,5 @@ def has_infs(arr: np.ndarray) -> bool: ...  # const floating[:]
 def get_reverse_indexer(
     indexer: np.ndarray,  # const intp_t[:]
     length: int,
-) -> np.ndarray: ...  # np.ndarray[np.intp]
+) -> npt.NDArray[np.intp]: ...
 def is_bool_list(obj: list) -> bool: ...

pandas/_libs/ops.pyi

@@ -7,19 +7,21 @@ from typing import (
 
 import numpy as np
 
+from pandas._typing import npt
+
 _BinOp = Callable[[Any, Any], Any]
 _BoolOp = Callable[[Any, Any], bool]
 
 def scalar_compare(
     values: np.ndarray,  # object[:]
     val: object,
     op: _BoolOp,  # {operator.eq, operator.ne, ...}
-) -> np.ndarray: ...  # np.ndarray[bool]
+) -> npt.NDArray[np.bool_]: ...
 def vec_compare(
-    left: np.ndarray,  # np.ndarray[object]
-    right: np.ndarray,  # np.ndarray[object]
+    left: npt.NDArray[np.object_],
+    right: npt.NDArray[np.object_],
     op: _BoolOp,  # {operator.eq, operator.ne, ...}
-) -> np.ndarray: ...  # np.ndarray[bool]
+) -> npt.NDArray[np.bool_]: ...
 def scalar_binop(
     values: np.ndarray,  # object[:]
     val: object,
@@ -32,14 +34,14 @@ def vec_binop(
 ) -> np.ndarray: ...
 @overload
 def maybe_convert_bool(
-    arr: np.ndarray,  # np.ndarray[object]
+    arr: npt.NDArray[np.object_],
     true_values=...,
     false_values=...,
     convert_to_masked_nullable: Literal[False] = ...,
 ) -> tuple[np.ndarray, None]: ...
 @overload
 def maybe_convert_bool(
-    arr: np.ndarray,  # np.ndarray[object]
+    arr: npt.NDArray[np.object_],
     true_values=...,
     false_values=...,
     *,

pandas/_libs/parsers.pyi

@@ -8,12 +8,13 @@ import numpy as np
 from pandas._typing import (
     ArrayLike,
     Dtype,
+    npt,
 )
 
 STR_NA_VALUES: set[str]
 
 def sanitize_objects(
-    values: np.ndarray,  # ndarray[object]
+    values: npt.NDArray[np.object_],
     na_values: set,
     convert_empty: bool = ...,
 ) -> int: ...

pandas/_libs/reshape.pyi

@@ -1,5 +1,7 @@
 import numpy as np
 
+import pandas._tying as npt
+
 def unstack(
     values: np.ndarray,  # reshape_t[:, :]
     mask: np.ndarray,  # const uint8_t[:]
@@ -10,5 +12,5 @@ def unstack(
     new_mask: np.ndarray,  # uint8_t[:, :]
 ) -> None: ...
 def explode(
-    values: np.ndarray,  # np.ndarray[object]
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[object]  # np.ndarray[np.int64]
+    values: npt.NDArray[np.object_],
+) -> tuple[npt.NDArray[np.object_], npt.NDArray[np.int64]]: ...

pandas/_libs/tslib.pyi

@@ -2,19 +2,21 @@ from datetime import tzinfo
 
 import numpy as np
 
+from pandas._typing import npt
+
 def format_array_from_datetime(
-    values: np.ndarray,  # np.ndarray[np.int64]
+    values: npt.NDArray[np.int64],
     tz: tzinfo | None = ...,
     format: str | None = ...,
     na_rep: object = ...,
-) -> np.ndarray: ...  # np.ndarray[object]
+) -> npt.NDArray[np.object_]: ...
 def array_with_unit_to_datetime(
     values: np.ndarray,
     unit: str,
     errors: str = ...,
 ) -> tuple[np.ndarray, tzinfo | None]: ...
 def array_to_datetime(
-    values: np.ndarray,  # np.ndarray[object]
+    values: npt.NDArray[np.object_],
     errors: str = ...,
     dayfirst: bool = ...,
     yearfirst: bool = ...,

pandas/_libs/window/indexers.pyi

@@ -1,10 +1,12 @@
 import numpy as np
 
+from pandas._typing import npt
+
 def calculate_variable_window_bounds(
     num_values: int,  # int64_t
     window_size: int,  # int64_t
     min_periods,
     center: bool,
     closed: str | None,
     index: np.ndarray,  # const int64_t[:]
-) -> tuple[np.ndarray, np.ndarray,]: ...  # np.ndarray[np.int64]  # np.ndarray[np.int64]
+) -> tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]: ...