parameters: (
      df,
      path,
      write_index=True,
      storage_options=None,
      compression=None,
      compute=True,
      **kwargs,
  )
return_statement: return delayed(list)(parts)
docstring: Write a dask_cudf dataframe to ORC file(s) (one file per partition).
  
      Parameters
      ----------
      df : dask_cudf.DataFrame
      path: string or pathlib.Path
          Destination directory for data.  Prepend with protocol like ``s3://``
          or ``hdfs://`` for remote data.
      write_index : boolean, optional
          Whether or not to write the index. Defaults to True.
      storage_options: None or dict
          Further parameters to pass to the bytes backend.
      compression : string or dict, optional
      compute : bool, optional
          If True (default) then the result is computed immediately. If False
          then a ``dask.delayed`` object is returned for future computation.
docstring_summary: Write a dask_cudf dataframe to ORC file(s) (one file per partition).
docstring_tokens: Write a dask_cudf dataframe to ORC file ( s ) ( one file per partition ) .
function: def to_orc(
      df,
      path,
      write_index=True,
      storage_options=None,
      compression=None,
      compute=True,
      **kwargs,
  ):
      """Write a dask_cudf dataframe to ORC file(s) (one file per partition).
  
      Parameters
      ----------
      df : dask_cudf.DataFrame
      path: string or pathlib.Path
          Destination directory for data.  Prepend with protocol like ``s3://``
          or ``hdfs://`` for remote data.
      write_index : boolean, optional
          Whether or not to write the index. Defaults to True.
      storage_options: None or dict
          Further parameters to pass to the bytes backend.
      compression : string or dict, optional
      compute : bool, optional
          If True (default) then the result is computed immediately. If False
          then a ``dask.delayed`` object is returned for future computation.
      """
  
      from dask import compute as dask_compute, delayed
  
      # TODO: Use upstream dask implementation once available
      #       (see: Dask Issue#5596)
  
      if hasattr(path, "name"):
          path = stringify_path(path)
      fs, _, _ = get_fs_token_paths(
          path, mode="wb", storage_options=storage_options
      )
      # Trim any protocol information from the path before forwarding
      path = fs._strip_protocol(path)
  
      if write_index:
          df = df.reset_index()
      else:
          # Not writing index - might as well drop it
          df = df.reset_index(drop=True)
  
      fs.mkdirs(path, exist_ok=True)
  
      # Use i_offset and df.npartitions to define file-name list
      filenames = ["part.%i.orc" % i for i in range(df.npartitions)]
  
      # write parts
      dwrite = delayed(write_orc_partition)
      parts = [
          dwrite(d, path, fs, filename, compression=compression)
          for d, filename in zip(df.to_delayed(), filenames)
      ]
  
      if compute:
          return dask_compute(*parts)
  
      return delayed(list)(parts)
function_tokens: def to_orc ( df , path , write_index = True , storage_options = None , compression = None , compute = True , * * kwargs , ) : from dask import compute as dask_compute , delayed # TODO: Use upstream dask implementation once available #       (see: Dask Issue#5596) if hasattr ( path , "name" ) : path = stringify_path ( path ) fs , _ , _ = get_fs_token_paths ( path , mode = "wb" , storage_options = storage_options ) # Trim any protocol information from the path before forwarding path = fs . _strip_protocol ( path ) if write_index : df = df . reset_index ( ) else : # Not writing index - might as well drop it df = df . reset_index ( drop = True ) fs . mkdirs ( path , exist_ok = True ) # Use i_offset and df.npartitions to define file-name list filenames = [ "part.%i.orc" % i for i in range ( df . npartitions ) ] # write parts dwrite = delayed ( write_orc_partition ) parts = [ dwrite ( d , path , fs , filename , compression = compression ) for d , filename in zip ( df . to_delayed ( ) , filenames ) ] if compute : return dask_compute ( * parts ) return delayed ( list ) ( parts )