class_docstr: A base class for data sources.
  
  This class represents a custom data source that allows for reading from and/or
  writing to it. The data source provides methods to create readers and writers
  for reading and writing data, respectively. At least one of the methods ``reader``
  or ``writer`` must be implemented by any subclass to make the data source either
  readable or writable (or both).
  
  After implementing this interface, you can start to load your data source using
  ``spark.read.format(...).load()`` and save data using ``df.write.format(...).save()``.
  
  .. versionadded: 4.0.0
docstr: Returns a string represents the format name of this data source.
  
  By default, it is the class name of the data source. It can be overridden to
  provide a customized short name for the data source.
  
  Examples
  --------
  >>> def name(cls):
  ...     return "my_data_source"
code: def name(cls) -> str:
      """
      Returns a string represents the format name of this data source.
  
      By default, it is the class name of the data source. It can be overridden to
      provide a customized short name for the data source.
  
      Examples
      --------
      >>> def name(cls):
      ...     return "my_data_source"
      """
      return cls.__name__
  
imports: from abc import ABC, abstractmethod
  from collections import UserDict
  from typing import Any, Dict, Iterator, List, Sequence, Tuple, Type, Union, TYPE_CHECKING
  from pyspark.sql import Row
  from pyspark.sql.types import StructType
  from pyspark.errors import PySparkNotImplementedError
label_desc: Use image node_id 2 for calling the DataSource obj's underlying member method code with example usage: obj.name(cls) and returns: cls