class_docstr: Wraps a Python callable and captures args/kwargs when called for execution.
  
  :param python_callable: A reference to an object that is callable
  :param op_kwargs: a dictionary of keyword arguments that will get unpacked
      in your function (templated)
  :param op_args: a list of positional arguments that will get unpacked when
      calling your callable (templated)
  :param multiple_outputs: If set to True, the decorated function's return value will be unrolled to
      multiple XCom values. Dict will unroll to XCom values with its keys as XCom keys. Defaults to False.
code: def __init__(
      self, *, python_callable, op_args, op_kwargs, **kwargs
  ) -> None:
      kwargs_to_upstream = {
          "python_callable": python_callable,
          "op_args": op_args,
          "op_kwargs": op_kwargs,
      }
      super().__init__(
          kwargs_to_upstream=kwargs_to_upstream,
          python_callable=python_callable,
          op_args=op_args,
          op_kwargs=op_kwargs,
          **kwargs,
      )
  
file_path: airflow/airflow/decorators/python.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Callable, Sequence
  from airflow.decorators.base import DecoratedOperator, task_decorator_factory
  from airflow.operators.python import PythonOperator
label_desc: Use image node_id 1 to create a new _PythonDecoratedOperator object from inherited base classes: DecoratedOperator, PythonOperator with example: obj = _PythonDecoratedOperator()