parameters: (
      obj: Any,
      filepath_or_buffer: FilePathOrBuffer,
      compression: Optional[str] = "infer",
      protocol: int = pickle.HIGHEST_PROTOCOL,
  )
docstring: Pickle (serialize) object to file.
  
      Parameters
      ----------
      obj : any object
          Any python object.
      filepath_or_buffer : str, path object or file-like object
          File path, URL, or buffer where the pickled object will be stored.
  
          .. versionchanged:: 1.0.0
             Accept URL. URL has to be of S3 or GCS.
  
      compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default 'infer'
          If 'infer' and 'path_or_url' is path-like, then detect compression from
          the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no
          compression) If 'infer' and 'path_or_url' is not path-like, then use
          None (= no decompression).
      protocol : int
          Int which indicates which protocol should be used by the pickler,
          default HIGHEST_PROTOCOL (see [1], paragraph 12.1.2). The possible
          values for this parameter depend on the version of Python. For Python
          2.x, possible values are 0, 1, 2. For Python>=3.0, 3 is a valid value.
          For Python >= 3.4, 4 is a valid value. A negative value for the
          protocol parameter is equivalent to setting its value to
          HIGHEST_PROTOCOL.
  
          .. [1] https://docs.python.org/3/library/pickle.html
          .. versionadded:: 0.21.0
  
      See Also
      --------
      read_pickle : Load pickled pandas object (or any object) from file.
      DataFrame.to_hdf : Write DataFrame to an HDF5 file.
      DataFrame.to_sql : Write DataFrame to a SQL database.
      DataFrame.to_parquet : Write a DataFrame to the binary parquet format.
  
      Examples
      --------
      >>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
      >>> original_df
         foo  bar
      0    0    5
      1    1    6
      2    2    7
      3    3    8
      4    4    9
      >>> pd.to_pickle(original_df, "./dummy.pkl")
  
      >>> unpickled_df = pd.read_pickle("./dummy.pkl")
      >>> unpickled_df
         foo  bar
      0    0    5
      1    1    6
      2    2    7
      3    3    8
      4    4    9
  
      >>> import os
      >>> os.remove("./dummy.pkl")
docstring_summary: Pickle (serialize) object to file.
docstring_tokens: Pickle ( serialize ) object to file .
function: def to_pickle(
      obj: Any,
      filepath_or_buffer: FilePathOrBuffer,
      compression: Optional[str] = "infer",
      protocol: int = pickle.HIGHEST_PROTOCOL,
  ):
      """
      Pickle (serialize) object to file.
  
      Parameters
      ----------
      obj : any object
          Any python object.
      filepath_or_buffer : str, path object or file-like object
          File path, URL, or buffer where the pickled object will be stored.
  
          .. versionchanged:: 1.0.0
             Accept URL. URL has to be of S3 or GCS.
  
      compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default 'infer'
          If 'infer' and 'path_or_url' is path-like, then detect compression from
          the following extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no
          compression) If 'infer' and 'path_or_url' is not path-like, then use
          None (= no decompression).
      protocol : int
          Int which indicates which protocol should be used by the pickler,
          default HIGHEST_PROTOCOL (see [1], paragraph 12.1.2). The possible
          values for this parameter depend on the version of Python. For Python
          2.x, possible values are 0, 1, 2. For Python>=3.0, 3 is a valid value.
          For Python >= 3.4, 4 is a valid value. A negative value for the
          protocol parameter is equivalent to setting its value to
          HIGHEST_PROTOCOL.
  
          .. [1] https://docs.python.org/3/library/pickle.html
          .. versionadded:: 0.21.0
  
      See Also
      --------
      read_pickle : Load pickled pandas object (or any object) from file.
      DataFrame.to_hdf : Write DataFrame to an HDF5 file.
      DataFrame.to_sql : Write DataFrame to a SQL database.
      DataFrame.to_parquet : Write a DataFrame to the binary parquet format.
  
      Examples
      --------
      >>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
      >>> original_df
         foo  bar
      0    0    5
      1    1    6
      2    2    7
      3    3    8
      4    4    9
      >>> pd.to_pickle(original_df, "./dummy.pkl")
  
      >>> unpickled_df = pd.read_pickle("./dummy.pkl")
      >>> unpickled_df
         foo  bar
      0    0    5
      1    1    6
      2    2    7
      3    3    8
      4    4    9
  
      >>> import os
      >>> os.remove("./dummy.pkl")
      """
      fp_or_buf, _, compression, should_close = get_filepath_or_buffer(
          filepath_or_buffer, compression=compression, mode="wb"
      )
      if not isinstance(fp_or_buf, str) and compression == "infer":
          compression = None
      f, fh = get_handle(fp_or_buf, "wb", compression=compression, is_text=False)
      if protocol < 0:
          protocol = pickle.HIGHEST_PROTOCOL
      try:
          f.write(pickle.dumps(obj, protocol=protocol))
      finally:
          f.close()
          for _f in fh:
              _f.close()
          if should_close:
              try:
                  fp_or_buf.close()
              except ValueError:
                  pass
function_tokens: def to_pickle ( obj : Any , filepath_or_buffer : FilePathOrBuffer , compression : Optional [ str ] = "infer" , protocol : int = pickle . HIGHEST_PROTOCOL , ) : fp_or_buf , _ , compression , should_close = get_filepath_or_buffer ( filepath_or_buffer , compression = compression , mode = "wb" ) if not isinstance ( fp_or_buf , str ) and compression == "infer" : compression = None f , fh = get_handle ( fp_or_buf , "wb" , compression = compression , is_text = False ) if protocol < 0 : protocol = pickle . HIGHEST_PROTOCOL try : f . write ( pickle . dumps ( obj , protocol = protocol ) ) finally : f . close ( ) for _f in fh : _f . close ( ) if should_close : try : fp_or_buf . close ( ) except ValueError : pass