code: def get_filepath_or_buffer(
      filepath_or_buffer, encoding=None, compression=None, mode=None
  ):
      """
      If the filepath_or_buffer is a url, translate and return the buffer.
      Otherwise passthrough.
  
      Parameters
      ----------
      filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
                           or buffer
      encoding : the encoding to use to decode py3 bytes, default is 'utf-8'
      mode : str, optional
  
      Returns
      -------
      tuple of ({a filepath_ or buffer or S3File instance},
                encoding, str,
                compression, str,
                should_close, bool)
      """
      filepath_or_buffer = _stringify_path(filepath_or_buffer)
  
      if _is_url(filepath_or_buffer):
          req = _urlopen(filepath_or_buffer)
          content_encoding = req.headers.get("Content-Encoding", None)
          if content_encoding == "gzip":
              # Override compression based on Content-Encoding header
              compression = "gzip"
          reader = BytesIO(req.read())
          req.close()
          return reader, encoding, compression, True
  
      if is_s3_url(filepath_or_buffer):
          from pandas.io import s3
  
          return s3.get_filepath_or_buffer(
              filepath_or_buffer,
              encoding=encoding,
              compression=compression,
              mode=mode,
          )
  
      if is_gcs_url(filepath_or_buffer):
          from pandas.io import gcs
  
          return gcs.get_filepath_or_buffer(
              filepath_or_buffer,
              encoding=encoding,
              compression=compression,
              mode=mode,
          )
  
      if isinstance(
          filepath_or_buffer,
          (compat.string_types, compat.binary_type, mmap.mmap),
      ):
          return (
              _expand_user(filepath_or_buffer),
              None,
              compression,
              False,
          )
  
      if not is_file_like(filepath_or_buffer):
          msg = "Invalid file path or buffer object type: {_type}"
          raise ValueError(msg.format(_type=type(filepath_or_buffer)))
  
      return filepath_or_buffer, None, compression, False
  
imports: import codecs
  from contextlib import closing, contextmanager
  import csv
  import mmap
  import os
  import zipfile
  import pandas.compat
  from pandas.compat import BytesIO, StringIO, string_types, text_type
  from pandas.errors import AbstractMethodError, DtypeWarning, EmptyDataError, ParserError, ParserWarning
  from pandas.core.dtypes.common import is_file_like, is_number
  from pandas.io.formats.printing import pprint_thing
label_desc: Use image node_id 7 for calling a global function with example usage: get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode) and returns: filepath_or_buffer,  None,  compression,  False, reader,  encoding,  compression,  True, s3, gcs, _expand_user,  None,  compression,  False