airflow python 源码
airflow python 代码
文件路径:/airflow/decorators/python.py
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# to you under the Apache License, Version 2.0 (the
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#
# http://www.apache.org/licenses/LICENSE-2.0
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# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
from typing import Callable, Sequence
from airflow.decorators.base import DecoratedOperator, TaskDecorator, task_decorator_factory
from airflow.operators.python import PythonOperator
class _PythonDecoratedOperator(DecoratedOperator, PythonOperator):
"""
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.
"""
template_fields: Sequence[str] = ('templates_dict', 'op_args', 'op_kwargs')
template_fields_renderers = {"templates_dict": "json", "op_args": "py", "op_kwargs": "py"}
# since we won't mutate the arguments, we should just do the shallow copy
# there are some cases we can't deepcopy the objects (e.g protobuf).
shallow_copy_attrs: Sequence[str] = ('python_callable',)
custom_operator_name: str = '@task'
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,
)
def python_task(
python_callable: Callable | None = None,
multiple_outputs: bool | None = None,
**kwargs,
) -> TaskDecorator:
"""Wraps a function into an Airflow operator.
Accepts kwargs for operator kwarg. Can be reused in a single DAG.
:param python_callable: Function to decorate
: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.
"""
return task_decorator_factory(
python_callable=python_callable,
multiple_outputs=multiple_outputs,
decorated_operator_class=_PythonDecoratedOperator,
**kwargs,
)
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