airflow lambda_function 源码
airflow lambda_function 代码
文件路径:/airflow/providers/amazon/aws/operators/lambda_function.py
#
# 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.
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Sequence
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.lambda_function import LambdaHook
if TYPE_CHECKING:
from airflow.utils.context import Context
class AwsLambdaInvokeFunctionOperator(BaseOperator):
"""
Invokes an AWS Lambda function.
You can invoke a function synchronously (and wait for the response),
or asynchronously.
To invoke a function asynchronously,
set `invocation_type` to `Event`. For more details,
review the boto3 Lambda invoke docs.
:param function_name: The name of the AWS Lambda function, version, or alias.
:param payload: The JSON string that you want to provide to your Lambda function as input.
:param log_type: Set to Tail to include the execution log in the response. Otherwise, set to "None".
:param qualifier: Specify a version or alias to invoke a published version of the function.
:param aws_conn_id: The AWS connection ID to use
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:AwsLambdaInvokeFunctionOperator`
"""
template_fields: Sequence[str] = ('function_name', 'payload', 'qualifier', 'invocation_type')
ui_color = '#ff7300'
def __init__(
self,
*,
function_name: str,
log_type: str | None = None,
qualifier: str | None = None,
invocation_type: str | None = None,
client_context: str | None = None,
payload: str | None = None,
aws_conn_id: str = 'aws_default',
**kwargs,
):
super().__init__(**kwargs)
self.function_name = function_name
self.payload = payload
self.log_type = log_type
self.qualifier = qualifier
self.invocation_type = invocation_type
self.client_context = client_context
self.aws_conn_id = aws_conn_id
def execute(self, context: Context):
"""
Invokes the target AWS Lambda function from Airflow.
:return: The response payload from the function, or an error object.
"""
hook = LambdaHook(aws_conn_id=self.aws_conn_id)
success_status_codes = [200, 202, 204]
self.log.info("Invoking AWS Lambda function: %s with payload: %s", self.function_name, self.payload)
response = hook.invoke_lambda(
function_name=self.function_name,
invocation_type=self.invocation_type,
log_type=self.log_type,
client_context=self.client_context,
payload=self.payload,
qualifier=self.qualifier,
)
self.log.info("Lambda response metadata: %r", response.get("ResponseMetadata"))
if response.get("StatusCode") not in success_status_codes:
raise ValueError('Lambda function did not execute', json.dumps(response.get("ResponseMetadata")))
payload_stream = response.get("Payload")
payload = payload_stream.read().decode()
if "FunctionError" in response:
raise ValueError(
'Lambda function execution resulted in error',
{"ResponseMetadata": response.get("ResponseMetadata"), "Payload": payload},
)
self.log.info('Lambda function invocation succeeded: %r', response.get("ResponseMetadata"))
return payload
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