old_contents: from pathlib import Path
  from typing import (
      IO,
      TYPE_CHECKING,
      AnyStr,
      Collection,
      Dict,
      List,
      Optional,
      TypeVar,
      Union,
  )
  
  import numpy as np
  
  # To prevent import cycles place any internal imports in the branch below
  # and use a string literal forward reference to it in subsequent types
  # https://mypy.readthedocs.io/en/latest/common_issues.html#import-cycles
  if TYPE_CHECKING:
      from pandas._libs import Period, Timedelta, Timestamp  # noqa: F401
      from pandas.core.arrays.base import ExtensionArray  # noqa: F401
      from pandas.core.dtypes.dtypes import ExtensionDtype  # noqa: F401
      from pandas.core.indexes.base import Index  # noqa: F401
      from pandas.core.series import Series  # noqa: F401
      from pandas.core.generic import NDFrame  # noqa: F401
      from pandas import Interval  # noqa: F401
  
  # arrary-like
  
  AnyArrayLike = TypeVar("AnyArrayLike", "ExtensionArray", "Index", "Series", np.ndarray)
  ArrayLike = TypeVar("ArrayLike", "ExtensionArray", np.ndarray)
  
  # scalars
  
  PythonScalar = Union[str, int, float, bool]
  DatetimeLikeScalar = TypeVar("DatetimeLikeScalar", "Period", "Timestamp", "Timedelta")
  PandasScalar = Union[DatetimeLikeScalar, "Interval"]
  Scalar = Union[PythonScalar, PandasScalar]
  
  # other
  
  Dtype = Union[str, np.dtype, "ExtensionDtype"]
  FilePathOrBuffer = Union[str, Path, IO[AnyStr]]
  FrameOrSeries = TypeVar("FrameOrSeries", bound="NDFrame")
  Axis = Union[str, int]
  Ordered = Optional[bool]
  JSONSerializable = Union[PythonScalar, List, Dict]
  Axes = Collection
  
  # to maintain type information across generic functions and parametrization
  T = TypeVar("T")
  
new_contents: from pathlib import Path
  from typing import (
      IO,
      TYPE_CHECKING,
      AnyStr,
      Collection,
      Dict,
      List,
      Optional,
      TypeVar,
      Union,
  )
  
  import numpy as np
  
  # To prevent import cycles place any internal imports in the branch below
  # and use a string literal forward reference to it in subsequent types
  # https://mypy.readthedocs.io/en/latest/common_issues.html#import-cycles
  if TYPE_CHECKING:
      from pandas._libs import Period, Timedelta, Timestamp  # noqa: F401
      from pandas.core.arrays.base import ExtensionArray  # noqa: F401
      from pandas.core.dtypes.dtypes import ExtensionDtype  # noqa: F401
      from pandas.core.indexes.base import Index  # noqa: F401
      from pandas.core.series import Series  # noqa: F401
      from pandas.core.generic import NDFrame  # noqa: F401
      from pandas import Interval  # noqa: F401
  
  # array-like
  
  AnyArrayLike = TypeVar("AnyArrayLike", "ExtensionArray", "Index", "Series", np.ndarray)
  ArrayLike = TypeVar("ArrayLike", "ExtensionArray", np.ndarray)
  
  # scalars
  
  PythonScalar = Union[str, int, float, bool]
  DatetimeLikeScalar = TypeVar("DatetimeLikeScalar", "Period", "Timestamp", "Timedelta")
  PandasScalar = Union[DatetimeLikeScalar, "Interval"]
  Scalar = Union[PythonScalar, PandasScalar]
  
  # other
  
  Dtype = Union[str, np.dtype, "ExtensionDtype"]
  FilePathOrBuffer = Union[str, Path, IO[AnyStr]]
  FrameOrSeries = TypeVar("FrameOrSeries", bound="NDFrame")
  Axis = Union[str, int]
  Ordered = Optional[bool]
  JSONSerializable = Union[PythonScalar, List, Dict]
  Axes = Collection
  
  # to maintain type information across generic functions and parametrization
  T = TypeVar("T")
  
subject: fix typo