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from __future__ import annotations
import json
from datetime import timedelta
from functools import cached_property
from typing import TYPE_CHECKING, Any, Sequence
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.lambda_function import LambdaHook
from airflow.providers.amazon.aws.triggers.lambda_function import LambdaCreateFunctionCompleteTrigger
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 waiter_max_attempts: Maximum number of attempts to poll the creation.
:param waiter_delay: Number of seconds between polling the state of the creation.
:param deferrable: If True, the operator will wait asynchronously for the creation to complete.
This implies waiting for creation complete. This mode requires aiobotocore module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param aws_conn_id: The AWS connection ID to use
"""
[docs] template_fields: Sequence[str] = (
"function_name",
"runtime",
"role",
"handler",
"code",
"config",
)
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,
waiter_max_attempts: int = 60,
waiter_delay: int = 15,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=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.waiter_delay = waiter_delay
self.waiter_max_attempts = waiter_max_attempts
self.deferrable = deferrable
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.deferrable:
self.defer(
trigger=LambdaCreateFunctionCompleteTrigger(
function_name=self.function_name,
function_arn=response["FunctionArn"],
waiter_delay=self.waiter_delay,
waiter_max_attempts=self.waiter_max_attempts,
aws_conn_id=self.aws_conn_id,
),
method_name="execute_complete",
timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay),
)
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] def execute_complete(self, context: Context, event: dict[str, Any] | None = None) -> str:
if not event or event["status"] != "success":
raise AirflowException(f"Trigger error: event is {event}")
self.log.info("Lambda function created successfully")
return event["function_arn"]
[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 and task logs.
Otherwise, set to "None". Applies to synchronously invoked functions only,
and returns the last 4 KB of the execution log.
:param keep_empty_log_lines: Whether or not keep empty lines in the execution log.
: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")
def __init__(
self,
*,
function_name: str,
log_type: str | None = None,
keep_empty_log_lines: bool = True,
qualifier: str | None = None,
invocation_type: str | None = None,
client_context: str | None = None,
payload: bytes | 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.keep_empty_log_lines = keep_empty_log_lines
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):
"""
Invoke 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 log_result := response.get("LogResult"):
log_records = self.hook.encode_log_result(
log_result,
keep_empty_lines=self.keep_empty_log_lines,
)
if log_records:
self.log.info(
"The last 4 KB of the Lambda execution log (keep_empty_log_lines=%s).",
self.keep_empty_log_lines,
)
for log_record in log_records:
self.log.info(log_record)
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
