__all__ = [
    "Block",
    "CategoricalBlock",
    "NumericBlock",
    "DatetimeTZBlock",
    "ExtensionBlock",
    "ObjectBlock",
    "make_block",

            

Reported by Pylint.

              from pandas.core.internals.api import make_block
from pandas.core.internals.array_manager import (
    ArrayManager,
    SingleArrayManager,
)
from pandas.core.internals.base import (
    DataManager,
    SingleDataManager,
)

            

Reported by Pylint.

              

def __getattr__(name: str):
    import warnings

    if name == "CategoricalBlock":
        warnings.warn(
            "CategoricalBlock is deprecated and will be removed in a future version. "
            "Use ExtensionBlock instead.",

            

Reported by Pylint.

                          DeprecationWarning,
            stacklevel=2,
        )
        from pandas.core.internals.blocks import CategoricalBlock

        return CategoricalBlock

    raise AttributeError(f"module 'pandas.core.internals' has no attribute '{name}'")

            

Reported by Pylint.

              import operator

import numpy as np
import pytest

import pandas._testing as tm
from pandas.core.ops.array_ops import (
    comparison_op,
    na_logical_op,

            

Reported by Pylint.

              import operator

import numpy as np
import pytest

import pandas._testing as tm
from pandas.core.ops.array_ops import (
    comparison_op,
    na_logical_op,

            

Reported by Pylint.

              )


def test_na_logical_op_2d():
    left = np.arange(8).reshape(4, 2)
    right = left.astype(object)
    right[0, 0] = np.nan

    # Check that we fall back to the vec_binop branch

            

Reported by Pylint.

                  tm.assert_numpy_array_equal(result, expected)


def test_object_comparison_2d():
    left = np.arange(9).reshape(3, 3).astype(object)
    right = left.T

    result = comparison_op(left, right, operator.eq)
    expected = np.eye(3).astype(bool)

            

Reported by Pylint.

              
import numpy as np

from pandas._libs import lib
from pandas._typing import ArrayLike

is_bool = lib.is_bool

is_integer = lib.is_integer

            

Reported by Pylint.

              
    """
    try:
        from dataclasses import is_dataclass

        return is_dataclass(item) and not isinstance(item, type)
    except ImportError:
        return False


            

Reported by Pylint.

              
    """
    try:
        from dataclasses import is_dataclass

        return is_dataclass(item) and not isinstance(item, type)
    except ImportError:
        return False


            

Reported by Pylint.

                      return False

    dtype = arr.dtype
    if dtype == np.dtype(bool):
        return True
    elif dtype == np.dtype("object"):
        return lib.is_bool_array(arr.ravel("K"))
    return False

            

Reported by Pylint.

              from datetime import datetime

import numpy as np
import pytest

from pandas.core.dtypes.cast import maybe_box_native

from pandas import (
    Interval,

            

Reported by Pylint.

              from datetime import datetime

import numpy as np
import pytest

from pandas.core.dtypes.cast import maybe_box_native

from pandas import (
    Interval,

            

Reported by Pylint.

                      (Timedelta(1, "D"), Timedelta),
        (Interval(0, 1), Interval),
        (Period("4Q2005"), Period),
    ],
)
def test_maybe_box_native(obj, expected_dtype):
    boxed_obj = maybe_box_native(obj)
    result_dtype = type(boxed_obj)
    assert result_dtype is expected_dtype

            

Reported by Pylint.

              def test_maybe_box_native(obj, expected_dtype):
    boxed_obj = maybe_box_native(obj)
    result_dtype = type(boxed_obj)
    assert result_dtype is expected_dtype

            

Reported by Bandit.

              from __future__ import annotations

import numpy as np

from pandas.core.algorithms import unique1d
from pandas.core.arrays.categorical import (
    Categorical,
    CategoricalDtype,
    recode_for_categories,

            

Reported by Pylint.

              from pandas.core.indexes.api import CategoricalIndex


def recode_for_groupby(
    c: Categorical, sort: bool, observed: bool
) -> tuple[Categorical, Categorical | None]:
    """
    Code the categories to ensure we can groupby for categoricals.


            

Reported by Pylint.

                  return c.reorder_categories(cat.categories), None


def recode_from_groupby(
    c: Categorical, sort: bool, ci: CategoricalIndex
) -> CategoricalIndex:
    """
    Reverse the codes_to_groupby to account for sort / observed.


            

Reported by Pylint.

                  return c.reorder_categories(cat.categories), None


def recode_from_groupby(
    c: Categorical, sort: bool, ci: CategoricalIndex
) -> CategoricalIndex:
    """
    Reverse the codes_to_groupby to account for sort / observed.


            

Reported by Pylint.

              import numpy as np
import pytest

import pandas as pd
import pandas._testing as tm


@pytest.mark.parametrize("na", [None, np.nan, pd.NA])
def test_setitem_missing_values(na):

            

Reported by Pylint.

              import numpy as np
import pytest

import pandas as pd
import pandas._testing as tm


@pytest.mark.parametrize("na", [None, np.nan, pd.NA])
def test_setitem_missing_values(na):

            

Reported by Pylint.

              

@pytest.mark.parametrize("na", [None, np.nan, pd.NA])
def test_setitem_missing_values(na):
    arr = pd.array([True, False, None], dtype="boolean")
    expected = pd.array([True, None, None], dtype="boolean")
    arr[1] = na
    tm.assert_extension_array_equal(arr, expected)

            

Reported by Pylint.

              

@pytest.mark.parametrize("na", [None, np.nan, pd.NA])
def test_setitem_missing_values(na):
    arr = pd.array([True, False, None], dtype="boolean")
    expected = pd.array([True, None, None], dtype="boolean")
    arr[1] = na
    tm.assert_extension_array_equal(arr, expected)

            

Reported by Pylint.

              
    if (!status) {
        /* handle inf/-inf infinity/-infinity */
        if (strlen(data) == 3) {
            if (0 == strcasecmp(data, "inf")) {
                *result = HUGE_VAL;
                *maybe_int = 0;
            } else {
                goto parsingerror;

            

Reported by FlawFinder.

                          } else {
                goto parsingerror;
            }
        } else if (strlen(data) == 4) {
            if (0 == strcasecmp(data, "-inf")) {
                *result = -HUGE_VAL;
                *maybe_int = 0;
            } else if (0 == strcasecmp(data, "+inf")) {
                *result = HUGE_VAL;

            

Reported by FlawFinder.

                          } else {
                goto parsingerror;
            }
        } else if (strlen(data) == 8) {
            if (0 == strcasecmp(data, "infinity")) {
                *result = HUGE_VAL;
                *maybe_int = 0;
            } else {
                goto parsingerror;

            

Reported by FlawFinder.

                          } else {
                goto parsingerror;
            }
        } else if (strlen(data) == 9) {
            if (0 == strcasecmp(data, "-infinity")) {
                *result = -HUGE_VAL;
                *maybe_int = 0;
            } else if (0 == strcasecmp(data, "+infinity")) {
                *result = HUGE_VAL;

            

Reported by FlawFinder.

                          retval = getattr(retval, self.name)._getitem_axis(key, axis=i)
            # We should never have retval.ndim < self.ndim, as that should
            #  be handled by the _getitem_lowerdim call above.
            assert retval.ndim == self.ndim

        return retval

    def _getitem_lowerdim(self, tup: tuple):


            

Reported by Bandit.

                      Setitem column-wise.
        """
        # Above we only set take_split_path to True for 2D cases
        assert self.ndim == 2

        if not isinstance(indexer, tuple):
            indexer = _tuplify(self.ndim, indexer)
        if len(indexer) > self.ndim:
            raise IndexError("too many indices for array")

            

Reported by Bandit.

                  @property
    def _axes_are_unique(self) -> bool:
        # Only relevant for self.ndim == 2
        assert self.ndim == 2
        return self.obj.index.is_unique and self.obj.columns.is_unique

    def __getitem__(self, key):

        if self.ndim == 2 and not self._axes_are_unique:

            

Reported by Bandit.

              
        if not value:
            for ax in obj.axes:
                ax._maybe_check_unique()

        self._allows_duplicate_labels = value

    def __getitem__(self, key):
        if key not in self._keys:

            

Reported by Pylint.

              import weakref


class Flags:
    """
    Flags that apply to pandas objects.

    .. versionadded:: 1.2.0


            

Reported by Pylint.

                          raise ValueError("This flag's object has been deleted.")

        if not value:
            for ax in obj.axes:
                ax._maybe_check_unique()

        self._allows_duplicate_labels = value

    def __getitem__(self, key):

            

Reported by Pylint.

              """ define generic base classes for pandas objects """
from __future__ import annotations

from typing import (
    TYPE_CHECKING,
    Type,
    cast,
)


            

Reported by Pylint.

                  # https://github.com/python/mypy/issues/1006
    # error: 'classmethod' used with a non-method
    @classmethod  # type: ignore[misc]
    def _check(cls, inst) -> bool:
        return getattr(inst, attr, "_typ") in comp

    dct = {"__instancecheck__": _check, "__subclasscheck__": _check}
    meta = type("ABCBase", (type,), dct)
    return meta(name, (), dct)

            

Reported by Pylint.

              
# define abstract base classes to enable isinstance type checking on our
# objects
def create_pandas_abc_type(name, attr, comp):

    # https://github.com/python/mypy/issues/1006
    # error: 'classmethod' used with a non-method
    @classmethod  # type: ignore[misc]
    def _check(cls, inst) -> bool:

            

Reported by Pylint.