Sync Fork from Upstream Repo

.pre-commit-config.yaml

@@ -206,3 +206,8 @@ repos:
         files: ^pandas/core/
         exclude: ^pandas/core/api\.py$
         types: [python]
+    -   id: no-bool-in-core-generic
+        name: Use bool_t instead of bool in pandas/core/generic.py
+        entry: python scripts/no_bool_in_generic.py
+        language: python
+        files: ^pandas/core/generic\.py$

LICENSES/PYUPGRADE_LICENSE

@@ -0,0 +1,19 @@
+Copyright (c) 2017 Anthony Sottile
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

pandas/_libs/algos.pyi

@@ -0,0 +1,293 @@
+# Note: this covers algos.pyx and algos_common_helper but NOT algos_take_helper
+from typing import Any
+
+import numpy as np
+
+class Infinity:
+    """
+    Provide a positive Infinity comparison method for ranking.
+    """
+    def __eq__(self, other) -> bool: ...
+    def __ne__(self, other) -> bool: ...
+    def __lt__(self, other) -> bool: ...
+    def __le__(self, other) -> bool: ...
+    def __gt__(self, other) -> bool: ...
+    def __ge__(self, other) -> bool: ...
+
+
+class NegInfinity:
+    """
+    Provide a negative Infinity comparison method for ranking.
+    """
+    def __eq__(self, other) -> bool: ...
+    def __ne__(self, other) -> bool: ...
+    def __lt__(self, other) -> bool: ...
+    def __le__(self, other) -> bool: ...
+    def __gt__(self, other) -> bool: ...
+    def __ge__(self, other) -> bool: ...
+
+
+def unique_deltas(
+    arr: np.ndarray,  # const int64_t[:]
+) -> np.ndarray: ...  # np.ndarray[np.int64, ndim=1]
+
+
+def is_lexsorted(list_of_arrays: list[np.ndarray]) -> bool: ...
+
+
+def groupsort_indexer(
+    index: np.ndarray,  # const int64_t[:]
+    ngroups: int,
+) -> tuple[
+    np.ndarray,  # ndarray[int64_t, ndim=1]
+    np.ndarray,  # ndarray[int64_t, ndim=1]
+]:
+    ...
+
+
+def kth_smallest(
+    a: np.ndarray,  # numeric[:]
+    k: int,
+) -> Any: ...       # numeric
+
+
+# ----------------------------------------------------------------------
+# Pairwise correlation/covariance
+
+
+
+def nancorr(
+    mat: np.ndarray,  # const float64_t[:, :]
+    cov: bool = False,
+    minp=None,
+) -> np.ndarray:  # np.ndarray[float64_t, ndim=2]
+    ...
+
+
+def nancorr_spearman(
+    mat: np.ndarray,  # ndarray[float64_t, ndim=2]
+    minp: int = 1,
+) -> np.ndarray:  # np.ndarray[np.float64, ndim=2]
+    ...
+
+
+def nancorr_kendall(
+    mat: np.ndarray,  # ndarray[float64_t, ndim=2]
+    minp: int = 1,
+) -> np.ndarray:  # np.ndarray[float64, ndim=2]
+    ...
+
+# ----------------------------------------------------------------------
+
+# ctypedef fused algos_t:
+#    float64_t
+#    float32_t
+#    object
+#    int64_t
+#    int32_t
+#    int16_t
+#    int8_t
+#    uint64_t
+#    uint32_t
+#    uint16_t
+#    uint8_t
+
+
+def validate_limit(nobs: int | None, limit=None) -> int: ...
+
+
+def pad(
+    old: np.ndarray,   # ndarray[algos_t]
+    new: np.ndarray,   # ndarray[algos_t]
+    limit=None,
+) -> np.ndarray: ...  # np.ndarray[np.intp, ndim=1]
+
+
+def pad_inplace(
+    values: np.ndarray,  # algos_t[:]
+    mask: np.ndarray,    # uint8_t[:]
+    limit=None,
+) -> None: ...
+
+
+def pad_2d_inplace(
+    values: np.ndarray,  # algos_t[:, :]
+    mask: np.ndarray,    # const uint8_t[:, :]
+    limit=None,
+) -> None:
+    ...
+
+
+def backfill(
+    old: np.ndarray,  # ndarray[algos_t]
+    new: np.ndarray,  # ndarray[algos_t]
+    limit=None,
+) -> np.ndarray:  # np.ndarray[np.intp, ndim=1]
+    ...
+
+def backfill_inplace(
+    values: np.ndarray,  # algos_t[:]
+    mask: np.ndarray,    # uint8_t[:]
+    limit=None,
+) -> None: ...
+
+
+def backfill_2d_inplace(
+    values: np.ndarray,  # algos_t[:, :]
+    mask: np.ndarray,    # const uint8_t[:, :]
+    limit=None,
+) -> None: ...
+
+
+def is_monotonic(
+    arr: np.ndarray,  # ndarray[algos_t, ndim=1]
+    timelike: bool
+) -> tuple[bool, bool, bool]:
+    ...
+
+# ----------------------------------------------------------------------
+# rank_1d, rank_2d
+# ----------------------------------------------------------------------
+
+# ctypedef fused rank_t:
+#    object
+#    float64_t
+#    uint64_t
+#    int64_t
+
+
+def rank_1d(
+    values: np.ndarray,  # ndarray[rank_t, ndim=1]
+    labels: np.ndarray,  # const int64_t[:]
+    is_datetimelike: bool = ...,
+    ties_method=...,
+    ascending: bool = ...,
+    pct: bool = ...,
+    na_option=...,
+) -> np.ndarray: ...  # np.ndarray[float64_t, ndim=1]
+
+
+def rank_2d(
+    in_arr: np.ndarray,  # ndarray[rank_t, ndim=2]
+    axis: int = ...,
+    is_datetimelike: bool = ...,
+    ties_method=...,
+    ascending: bool = ...,
+    na_option=...,
+    pct: bool = ...,
+) -> np.ndarray: ...  # np.ndarray[float64_t, ndim=1]
+
+
+def diff_2d(
+    arr: np.ndarray,  # ndarray[diff_t, ndim=2]
+    out: np.ndarray,  # ndarray[out_t, ndim=2]
+    periods: int,
+    axis: int,
+    datetimelike: bool = ...,
+) -> None: ...
+
+
+def ensure_platform_int(arr: object) -> np.ndarray: ...
+
+def ensure_object(arr: object) -> np.ndarray: ...
+
+def ensure_float64(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_float32(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_int8(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_int16(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_int32(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_int64(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_uint8(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_uint16(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_uint32(arr: object, copy=True) -> np.ndarray: ...
+
+def ensure_uint64(arr: object, copy=True) -> np.ndarray: ...
+
+
+def take_1d_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_1d_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+
+def take_2d_axis0_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis0_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+
+def take_2d_axis1_int8_int8(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int8_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int8_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int8_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int16_int16(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int16_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int16_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int16_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int32_int32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int32_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int64_int64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_int64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_float32_float32(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_float32_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_float64_float64(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_object_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_bool_bool(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_axis1_bool_object(values: np.ndarray, indexer: np.ndarray, out: np.ndarray, fill_value=...) -> None: ...
+
+def take_2d_multi_int8_int8(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int8_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int8_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int8_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int16_int16(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int16_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int16_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int16_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int32_int32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int32_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int32_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int64_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_float32_float32(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_float32_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_float64_float64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_object_object(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_bool_bool(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_bool_object(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...
+def take_2d_multi_int64_int64(values: np.ndarray, indexer, out: np.ndarray, fill_value=...) -> None: ...

pandas/_libs/algos.pyx

@@ -563,7 +563,7 @@ ctypedef fused algos_t:
     uint8_t
 
 
-def validate_limit(nobs: int, limit=None) -> int:
+def validate_limit(nobs: int | None, limit=None) -> int:
     """
     Check that the `limit` argument is a positive integer.
 

pandas/_libs/internals.pyi

@@ -6,7 +6,10 @@ from typing import (
 
 import numpy as np
 
-from pandas._typing import ArrayLike
+from pandas._typing import (
+    ArrayLike,
+    T,
+)
 
 def slice_len(slc: slice, objlen: int = ...) -> int: ...
 
@@ -50,9 +53,16 @@ class BlockPlacement:
     def append(self, others: list[BlockPlacement]) -> BlockPlacement: ...
 
 
-class Block:
+class SharedBlock:
     _mgr_locs: BlockPlacement
     ndim: int
     values: ArrayLike
 
     def __init__(self, values: ArrayLike, placement: BlockPlacement, ndim: int): ...
+
+class NumpyBlock(SharedBlock):
+    values: np.ndarray
+    def getitem_block_index(self: T, slicer: slice) -> T: ...
+
+class Block(SharedBlock):
+    ...