code: def read_feather(
      path: FilePath | ReadBuffer[bytes],
      columns: Sequence[Hashable] | None = None,
      use_threads: bool = True,
      storage_options: StorageOptions | None = None,
      dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
  ) -> DataFrame:
      """
      Load a feather-format object from the file path.
  
      Parameters
      ----------
      path : str, path object, or file-like object
          String, path object (implementing ``os.PathLike[str]``), or file-like
          object implementing a binary ``read()`` function. The string could be a URL.
          Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is
          expected. A local file could be: ``file://localhost/path/to/table.feather``.
      columns : sequence, default None
          If not provided, all columns are read.
      use_threads : bool, default True
          Whether to parallelize reading using multiple threads.
      {storage_options}
  
      dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
          Back-end data type applied to the resultant :class:`DataFrame`
          (still experimental). Behaviour is as follows:
  
          * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
            (default).
          * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
            DataFrame.
  
          .. versionadded:: 2.0
  
      Returns
      -------
      type of object stored in file
  
      Examples
      --------
      >>> df = pd.read_feather("path/to/file.feather")  # doctest: +SKIP
      """
      import_optional_dependency("pyarrow")
      from pyarrow import feather
  
      # import utils to register the pyarrow extension types
      import pandas.core.arrays.arrow.extension_types  # pyright: ignore[reportUnusedImport] # noqa: F401
  
      check_dtype_backend(dtype_backend)
  
      with get_handle(
          path, "rb", storage_options=storage_options, is_text=False
      ) as handles:
          if (
              dtype_backend is lib.no_default
              and not using_pyarrow_string_dtype()
          ):
              return feather.read_feather(
                  handles.handle,
                  columns=columns,
                  use_threads=bool(use_threads),
              )
  
          pa_table = feather.read_table(
              handles.handle,
              columns=columns,
              use_threads=bool(use_threads),
          )
  
          if dtype_backend == "numpy_nullable":
              from pandas.io._util import _arrow_dtype_mapping
  
              return pa_table.to_pandas(
                  types_mapper=_arrow_dtype_mapping().get
              )
  
          elif dtype_backend == "pyarrow":
              return pa_table.to_pandas(types_mapper=pd.ArrowDtype)
  
          elif using_pyarrow_string_dtype():
              return pa_table.to_pandas(
                  types_mapper=arrow_string_types_mapper()
              )
          else:
              raise NotImplementedError
  
file_path: pandas/pandas/io/feather_format.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any
  from pandas._config import using_pyarrow_string_dtype
  from pandas._libs import lib
  from pandas.compat._optional import import_optional_dependency
  from pandas.util._decorators import doc
  from pandas.util._validators import check_dtype_backend
  import pandas
  from pandas.core.api import DataFrame
  from pandas.core.shared_docs import _shared_docs
  from pandas.io._util import arrow_string_types_mapper
  from pandas.io.common import get_handle
label_desc: Use image node_id 2 for calling a global function with example usage: read_feather(path, columns, use_threads, storage_options, dtype_backend) and returns: feather, pa_table, pa_table, pa_table