Source code for airflow.providers.amazon.aws.operators.lambda_function

#
# 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
import warnings
from typing import TYPE_CHECKING, Sequence

from airflow.compat.functools import cached_property
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.lambda_function import LambdaHook

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class LambdaCreateFunctionOperator(BaseOperator): """ Creates an AWS Lambda function. More information regarding parameters of this operator can be found here https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/lambda.html#Lambda.Client.create_function .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:LambdaCreateFunctionOperator` :param function_name: The name of the AWS Lambda function, version, or alias. :param runtime: The identifier of the function's runtime. Runtime is required if the deployment package is a .zip file archive. :param role: The Amazon Resource Name (ARN) of the function's execution role. :param handler: The name of the method within your code that Lambda calls to run your function. Handler is required if the deployment package is a .zip file archive. :param code: The code for the function. :param description: A description of the function. :param timeout: The amount of time (in seconds) that Lambda allows a function to run before stopping it. :param config: Optional dictionary for arbitrary parameters to the boto API create_lambda call. :param wait_for_completion: If True, the operator will wait until the function is active. :param aws_conn_id: The AWS connection ID to use """
[docs] template_fields: Sequence[str] = ( "function_name", "runtime", "role", "handler", "code", "config",
)
[docs] ui_color = "#ff7300"
def __init__( self, *, function_name: str, runtime: str | None = None, role: str, handler: str | None = None, code: dict, description: str | None = None, timeout: int | None = None, config: dict = {}, wait_for_completion: bool = False, aws_conn_id: str = "aws_default", **kwargs, ): super().__init__(**kwargs) self.function_name = function_name self.runtime = runtime self.role = role self.handler = handler self.code = code self.description = description self.timeout = timeout self.config = config self.wait_for_completion = wait_for_completion self.aws_conn_id = aws_conn_id @cached_property
[docs] def hook(self) -> LambdaHook: return LambdaHook(aws_conn_id=self.aws_conn_id)
[docs] def execute(self, context: Context): self.log.info("Creating AWS Lambda function: %s", self.function_name) response = self.hook.create_lambda( function_name=self.function_name, runtime=self.runtime, role=self.role, handler=self.handler, code=self.code, description=self.description, timeout=self.timeout, **self.config, ) self.log.info("Lambda response: %r", response) if self.wait_for_completion: self.log.info("Wait for Lambda function to be active") waiter = self.hook.conn.get_waiter("function_active_v2") waiter.wait( FunctionName=self.function_name, ) return response.get("FunctionArn")
[docs]class LambdaInvokeFunctionOperator(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. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:LambdaInvokeFunctionOperator` :param function_name: The name of the AWS Lambda function, version, or alias. :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 invocation_type: AWS Lambda invocation type (RequestResponse, Event, DryRun) :param client_context: Data about the invoking client to pass to the function in the context object :param payload: JSON provided as input to the Lambda function :param aws_conn_id: The AWS connection ID to use """
[docs] template_fields: Sequence[str] = ("function_name", "payload", "qualifier", "invocation_type")
[docs] 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 @cached_property
[docs] def hook(self) -> LambdaHook: return LambdaHook(aws_conn_id=self.aws_conn_id)
[docs] def execute(self, context: Context): """ Invokes the target AWS Lambda function from Airflow. :return: The response payload from the function, or an error object. """ success_status_codes = [200, 202, 204] self.log.info("Invoking AWS Lambda function: %s with payload: %s", self.function_name, self.payload) response = self.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
[docs]class AwsLambdaInvokeFunctionOperator(LambdaInvokeFunctionOperator): """ This class is deprecated. Please use :class:`airflow.providers.amazon.aws.operators.lambda_function.LambdaInvokeFunctionOperator`. """ def __init__(self, *args, **kwargs): warnings.warn( "This class is deprecated." "Please use" "`airflow.providers.amazon.aws.operators.lambda_function.LambdaInvokeFunctionOperator`.", DeprecationWarning, stacklevel=2, ) super().__init__(*args, **kwargs)

Was this entry helpful?