blob: 61e5d1f5dc93eea0e3f679fa3167ba0dc7231845 [file] [log] [blame]
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import inspect
from textwrap import dedent
from typing import Callable, Optional, TypeVar
from airflow.decorators.base import DecoratedOperator, task_decorator_factory
from airflow.operators.python import PythonVirtualenvOperator
from airflow.utils.python_virtualenv import remove_task_decorator
class _PythonVirtualenvDecoratedOperator(DecoratedOperator, PythonVirtualenvOperator):
"""
Wraps a Python callable and captures args/kwargs when called for execution.
:param python_callable: A reference to an object that is callable
:type python_callable: python callable
:param op_kwargs: a dictionary of keyword arguments that will get unpacked
in your function (templated)
:type op_kwargs: dict
:param op_args: a list of positional arguments that will get unpacked when
calling your callable (templated)
:type op_args: list
:param multiple_outputs: if set, function return value will be
unrolled to multiple XCom values. Dict will unroll to xcom values with keys as keys.
Defaults to False.
:type multiple_outputs: bool
"""
template_fields = ('op_args', 'op_kwargs')
template_fields_renderers = {"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 = ('python_callable',)
def __init__(
self,
**kwargs,
) -> None:
kwargs_to_upstream = {
"python_callable": kwargs["python_callable"],
"op_args": kwargs["op_args"],
"op_kwargs": kwargs["op_kwargs"],
}
super().__init__(kwargs_to_upstream=kwargs_to_upstream, **kwargs)
def get_python_source(self):
raw_source = inspect.getsource(self.python_callable)
res = dedent(raw_source)
res = remove_task_decorator(res, "@task.virtualenv")
return res
T = TypeVar("T", bound=Callable)
def _virtualenv_task(
python_callable: Optional[Callable] = None, multiple_outputs: Optional[bool] = None, **kwargs
):
"""
Python operator decorator. 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
:type python_callable: Optional[Callable]
:param multiple_outputs: if set, function return value will be
unrolled to multiple XCom values. List/Tuples will unroll to xcom values
with index as key. Dict will unroll to xcom values with keys as XCom keys.
Defaults to False.
:type multiple_outputs: bool
"""
return task_decorator_factory(
python_callable=python_callable,
multiple_outputs=multiple_outputs,
decorated_operator_class=_PythonVirtualenvDecoratedOperator,
**kwargs,
)