Ejemplos de Lambda que se utilizan para SDK Python (Boto3)

import boto3


def main():
    """
    List the Lambda functions in your AWS account.
    """
    # Create the Lambda client
    lambda_client = boto3.client("lambda")

    # Use the paginator to list the functions
    paginator = lambda_client.get_paginator("list_functions")
    response_iterator = paginator.paginate()

    print("Here are the Lambda functions in your account:")
    for page in response_iterator:
        for function in page["Functions"]:
            print(f"  {function['FunctionName']}")


if __name__ == "__main__":
    main()

Defina un controlador de Lambda que aumente un número.

import logging

logger = logging.getLogger()
logger.setLevel(logging.INFO)


def lambda_handler(event, context):
    """
    Accepts an action and a single number, performs the specified action on the number,
    and returns the result. The only allowable action is 'increment'.

    :param event: The event dict that contains the parameters sent when the function
                  is invoked.
    :param context: The context in which the function is called.
    :return: The result of the action.
    """
    result = None
    action = event.get("action")
    if action == "increment":
        result = event.get("number", 0) + 1
        logger.info("Calculated result of %s", result)
    else:
        logger.error("%s is not a valid action.", action)

    response = {"result": result}
    return response

Defina un segundo controlador Lambda que realice operaciones aritméticas.

import logging
import os


logger = logging.getLogger()

# Define a list of Python lambda functions that are called by this AWS Lambda function.
ACTIONS = {
    "plus": lambda x, y: x + y,
    "minus": lambda x, y: x - y,
    "times": lambda x, y: x * y,
    "divided-by": lambda x, y: x / y,
}


def lambda_handler(event, context):
    """
    Accepts an action and two numbers, performs the specified action on the numbers,
    and returns the result.

    :param event: The event dict that contains the parameters sent when the function
                  is invoked.
    :param context: The context in which the function is called.
    :return: The result of the specified action.
    """
    # Set the log level based on a variable configured in the Lambda environment.
    logger.setLevel(os.environ.get("LOG_LEVEL", logging.INFO))
    logger.debug("Event: %s", event)

    action = event.get("action")
    func = ACTIONS.get(action)
    x = event.get("x")
    y = event.get("y")
    result = None
    try:
        if func is not None and x is not None and y is not None:
            result = func(x, y)
            logger.info("%s %s %s is %s", x, action, y, result)
        else:
            logger.error("I can't calculate %s %s %s.", x, action, y)
    except ZeroDivisionError:
        logger.warning("I can't divide %s by 0!", x)

    response = {"result": result}
    return response

Cree funciones que ajusten las acciones de Lambda.

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    @staticmethod
    def create_deployment_package(source_file, destination_file):
        """
        Creates a Lambda deployment package in .zip format in an in-memory buffer. This
        buffer can be passed directly to Lambda when creating the function.

        :param source_file: The name of the file that contains the Lambda handler
                            function.
        :param destination_file: The name to give the file when it's deployed to Lambda.
        :return: The deployment package.
        """
        buffer = io.BytesIO()
        with zipfile.ZipFile(buffer, "w") as zipped:
            zipped.write(source_file, destination_file)
        buffer.seek(0)
        return buffer.read()

    def get_iam_role(self, iam_role_name):
        """
        Get an AWS Identity and Access Management (IAM) role.

        :param iam_role_name: The name of the role to retrieve.
        :return: The IAM role.
        """
        role = None
        try:
            temp_role = self.iam_resource.Role(iam_role_name)
            temp_role.load()
            role = temp_role
            logger.info("Got IAM role %s", role.name)
        except ClientError as err:
            if err.response["Error"]["Code"] == "NoSuchEntity":
                logger.info("IAM role %s does not exist.", iam_role_name)
            else:
                logger.error(
                    "Couldn't get IAM role %s. Here's why: %s: %s",
                    iam_role_name,
                    err.response["Error"]["Code"],
                    err.response["Error"]["Message"],
                )
                raise
        return role

    def create_iam_role_for_lambda(self, iam_role_name):
        """
        Creates an IAM role that grants the Lambda function basic permissions. If a
        role with the specified name already exists, it is used for the demo.

        :param iam_role_name: The name of the role to create.
        :return: The role and a value that indicates whether the role is newly created.
        """
        role = self.get_iam_role(iam_role_name)
        if role is not None:
            return role, False

        lambda_assume_role_policy = {
            "Version": "2012-10-17",
            "Statement": [
                {
                    "Effect": "Allow",
                    "Principal": {"Service": "lambda.amazonaws.com"},
                    "Action": "sts:AssumeRole",
                }
            ],
        }
        policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"

        try:
            role = self.iam_resource.create_role(
                RoleName=iam_role_name,
                AssumeRolePolicyDocument=json.dumps(lambda_assume_role_policy),
            )
            logger.info("Created role %s.", role.name)
            role.attach_policy(PolicyArn=policy_arn)
            logger.info("Attached basic execution policy to role %s.", role.name)
        except ClientError as error:
            if error.response["Error"]["Code"] == "EntityAlreadyExists":
                role = self.iam_resource.Role(iam_role_name)
                logger.warning("The role %s already exists. Using it.", iam_role_name)
            else:
                logger.exception(
                    "Couldn't create role %s or attach policy %s.",
                    iam_role_name,
                    policy_arn,
                )
                raise

        return role, True

    def get_function(self, function_name):
        """
        Gets data about a Lambda function.

        :param function_name: The name of the function.
        :return: The function data.
        """
        response = None
        try:
            response = self.lambda_client.get_function(FunctionName=function_name)
        except ClientError as err:
            if err.response["Error"]["Code"] == "ResourceNotFoundException":
                logger.info("Function %s does not exist.", function_name)
            else:
                logger.error(
                    "Couldn't get function %s. Here's why: %s: %s",
                    function_name,
                    err.response["Error"]["Code"],
                    err.response["Error"]["Message"],
                )
                raise
        return response


    def create_function(
        self, function_name, handler_name, iam_role, deployment_package
    ):
        """
        Deploys a Lambda function.

        :param function_name: The name of the Lambda function.
        :param handler_name: The fully qualified name of the handler function. This
                             must include the file name and the function name.
        :param iam_role: The IAM role to use for the function.
        :param deployment_package: The deployment package that contains the function
                                   code in .zip format.
        :return: The Amazon Resource Name (ARN) of the newly created function.
        """
        try:
            response = self.lambda_client.create_function(
                FunctionName=function_name,
                Description="AWS Lambda doc example",
                Runtime="python3.9",
                Role=iam_role.arn,
                Handler=handler_name,
                Code={"ZipFile": deployment_package},
                Publish=True,
            )
            function_arn = response["FunctionArn"]
            waiter = self.lambda_client.get_waiter("function_active_v2")
            waiter.wait(FunctionName=function_name)
            logger.info(
                "Created function '%s' with ARN: '%s'.",
                function_name,
                response["FunctionArn"],
            )
        except ClientError:
            logger.error("Couldn't create function %s.", function_name)
            raise
        else:
            return function_arn


    def delete_function(self, function_name):
        """
        Deletes a Lambda function.

        :param function_name: The name of the function to delete.
        """
        try:
            self.lambda_client.delete_function(FunctionName=function_name)
        except ClientError:
            logger.exception("Couldn't delete function %s.", function_name)
            raise


    def invoke_function(self, function_name, function_params, get_log=False):
        """
        Invokes a Lambda function.

        :param function_name: The name of the function to invoke.
        :param function_params: The parameters of the function as a dict. This dict
                                is serialized to JSON before it is sent to Lambda.
        :param get_log: When true, the last 4 KB of the execution log are included in
                        the response.
        :return: The response from the function invocation.
        """
        try:
            response = self.lambda_client.invoke(
                FunctionName=function_name,
                Payload=json.dumps(function_params),
                LogType="Tail" if get_log else "None",
            )
            logger.info("Invoked function %s.", function_name)
        except ClientError:
            logger.exception("Couldn't invoke function %s.", function_name)
            raise
        return response


    def update_function_code(self, function_name, deployment_package):
        """
        Updates the code for a Lambda function by submitting a .zip archive that contains
        the code for the function.

        :param function_name: The name of the function to update.
        :param deployment_package: The function code to update, packaged as bytes in
                                   .zip format.
        :return: Data about the update, including the status.
        """
        try:
            response = self.lambda_client.update_function_code(
                FunctionName=function_name, ZipFile=deployment_package
            )
        except ClientError as err:
            logger.error(
                "Couldn't update function %s. Here's why: %s: %s",
                function_name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return response


    def update_function_configuration(self, function_name, env_vars):
        """
        Updates the environment variables for a Lambda function.

        :param function_name: The name of the function to update.
        :param env_vars: A dict of environment variables to update.
        :return: Data about the update, including the status.
        """
        try:
            response = self.lambda_client.update_function_configuration(
                FunctionName=function_name, Environment={"Variables": env_vars}
            )
        except ClientError as err:
            logger.error(
                "Couldn't update function configuration %s. Here's why: %s: %s",
                function_name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return response


    def list_functions(self):
        """
        Lists the Lambda functions for the current account.
        """
        try:
            func_paginator = self.lambda_client.get_paginator("list_functions")
            for func_page in func_paginator.paginate():
                for func in func_page["Functions"]:
                    print(func["FunctionName"])
                    desc = func.get("Description")
                    if desc:
                        print(f"\t{desc}")
                    print(f"\t{func['Runtime']}: {func['Handler']}")
        except ClientError as err:
            logger.error(
                "Couldn't list functions. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

Cree una función que ejecute el escenario.

class UpdateFunctionWaiter(CustomWaiter):
    """A custom waiter that waits until a function is successfully updated."""

    def __init__(self, client):
        super().__init__(
            "UpdateSuccess",
            "GetFunction",
            "Configuration.LastUpdateStatus",
            {"Successful": WaitState.SUCCESS, "Failed": WaitState.FAILURE},
            client,
        )

    def wait(self, function_name):
        self._wait(FunctionName=function_name)


def run_scenario(lambda_client, iam_resource, basic_file, calculator_file, lambda_name):
    """
    Runs the scenario.

    :param lambda_client: A Boto3 Lambda client.
    :param iam_resource: A Boto3 IAM resource.
    :param basic_file: The name of the file that contains the basic Lambda handler.
    :param calculator_file: The name of the file that contains the calculator Lambda handler.
    :param lambda_name: The name to give resources created for the scenario, such as the
                        IAM role and the Lambda function.
    """
    logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")

    print("-" * 88)
    print("Welcome to the AWS Lambda getting started with functions demo.")
    print("-" * 88)

    wrapper = LambdaWrapper(lambda_client, iam_resource)

    print("Checking for IAM role for Lambda...")
    iam_role, should_wait = wrapper.create_iam_role_for_lambda(lambda_name)
    if should_wait:
        logger.info("Giving AWS time to create resources...")
        wait(10)

    print(f"Looking for function {lambda_name}...")
    function = wrapper.get_function(lambda_name)
    if function is None:
        print("Zipping the Python script into a deployment package...")
        deployment_package = wrapper.create_deployment_package(
            basic_file, f"{lambda_name}.py"
        )
        print(f"...and creating the {lambda_name} Lambda function.")
        wrapper.create_function(
            lambda_name, f"{lambda_name}.lambda_handler", iam_role, deployment_package
        )
    else:
        print(f"Function {lambda_name} already exists.")
    print("-" * 88)

    print(f"Let's invoke {lambda_name}. This function increments a number.")
    action_params = {
        "action": "increment",
        "number": q.ask("Give me a number to increment: ", q.is_int),
    }
    print(f"Invoking {lambda_name}...")
    response = wrapper.invoke_function(lambda_name, action_params)
    print(
        f"Incrementing {action_params['number']} resulted in "
        f"{json.load(response['Payload'])}"
    )
    print("-" * 88)

    print(f"Let's update the function to an arithmetic calculator.")
    q.ask("Press Enter when you're ready.")
    print("Creating a new deployment package...")
    deployment_package = wrapper.create_deployment_package(
        calculator_file, f"{lambda_name}.py"
    )
    print(f"...and updating the {lambda_name} Lambda function.")
    update_waiter = UpdateFunctionWaiter(lambda_client)
    wrapper.update_function_code(lambda_name, deployment_package)
    update_waiter.wait(lambda_name)
    print(f"This function uses an environment variable to control logging level.")
    print(f"Let's set it to DEBUG to get the most logging.")
    wrapper.update_function_configuration(
        lambda_name, {"LOG_LEVEL": logging.getLevelName(logging.DEBUG)}
    )

    actions = ["plus", "minus", "times", "divided-by"]
    want_invoke = True
    while want_invoke:
        print(f"Let's invoke {lambda_name}. You can invoke these actions:")
        for index, action in enumerate(actions):
            print(f"{index + 1}: {action}")
        action_params = {}
        action_index = q.ask(
            "Enter the number of the action you want to take: ",
            q.is_int,
            q.in_range(1, len(actions)),
        )
        action_params["action"] = actions[action_index - 1]
        print(f"You've chosen to invoke 'x {action_params['action']} y'.")
        action_params["x"] = q.ask("Enter a value for x: ", q.is_int)
        action_params["y"] = q.ask("Enter a value for y: ", q.is_int)
        print(f"Invoking {lambda_name}...")
        response = wrapper.invoke_function(lambda_name, action_params, True)
        print(
            f"Calculating {action_params['x']} {action_params['action']} {action_params['y']} "
            f"resulted in {json.load(response['Payload'])}"
        )
        q.ask("Press Enter to see the logs from the call.")
        print(base64.b64decode(response["LogResult"]).decode())
        want_invoke = q.ask("That was fun. Shall we do it again? (y/n) ", q.is_yesno)
    print("-" * 88)

    if q.ask(
        "Do you want to list all of the functions in your account? (y/n) ", q.is_yesno
    ):
        wrapper.list_functions()
    print("-" * 88)

    if q.ask("Ready to delete the function and role? (y/n) ", q.is_yesno):
        for policy in iam_role.attached_policies.all():
            policy.detach_role(RoleName=iam_role.name)
        iam_role.delete()
        print(f"Deleted role {lambda_name}.")
        wrapper.delete_function(lambda_name)
        print(f"Deleted function {lambda_name}.")

    print("\nThanks for watching!")
    print("-" * 88)


if __name__ == "__main__":
    try:
        run_scenario(
            boto3.client("lambda"),
            boto3.resource("iam"),
            "lambda_handler_basic.py",
            "lambda_handler_calculator.py",
            "doc_example_lambda_calculator",
        )
    except Exception:
        logging.exception("Something went wrong with the demo!")

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def create_function(
        self, function_name, handler_name, iam_role, deployment_package
    ):
        """
        Deploys a Lambda function.

        :param function_name: The name of the Lambda function.
        :param handler_name: The fully qualified name of the handler function. This
                             must include the file name and the function name.
        :param iam_role: The IAM role to use for the function.
        :param deployment_package: The deployment package that contains the function
                                   code in .zip format.
        :return: The Amazon Resource Name (ARN) of the newly created function.
        """
        try:
            response = self.lambda_client.create_function(
                FunctionName=function_name,
                Description="AWS Lambda doc example",
                Runtime="python3.9",
                Role=iam_role.arn,
                Handler=handler_name,
                Code={"ZipFile": deployment_package},
                Publish=True,
            )
            function_arn = response["FunctionArn"]
            waiter = self.lambda_client.get_waiter("function_active_v2")
            waiter.wait(FunctionName=function_name)
            logger.info(
                "Created function '%s' with ARN: '%s'.",
                function_name,
                response["FunctionArn"],
            )
        except ClientError:
            logger.error("Couldn't create function %s.", function_name)
            raise
        else:
            return function_arn

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def delete_function(self, function_name):
        """
        Deletes a Lambda function.

        :param function_name: The name of the function to delete.
        """
        try:
            self.lambda_client.delete_function(FunctionName=function_name)
        except ClientError:
            logger.exception("Couldn't delete function %s.", function_name)
            raise

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def get_function(self, function_name):
        """
        Gets data about a Lambda function.

        :param function_name: The name of the function.
        :return: The function data.
        """
        response = None
        try:
            response = self.lambda_client.get_function(FunctionName=function_name)
        except ClientError as err:
            if err.response["Error"]["Code"] == "ResourceNotFoundException":
                logger.info("Function %s does not exist.", function_name)
            else:
                logger.error(
                    "Couldn't get function %s. Here's why: %s: %s",
                    function_name,
                    err.response["Error"]["Code"],
                    err.response["Error"]["Message"],
                )
                raise
        return response

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def invoke_function(self, function_name, function_params, get_log=False):
        """
        Invokes a Lambda function.

        :param function_name: The name of the function to invoke.
        :param function_params: The parameters of the function as a dict. This dict
                                is serialized to JSON before it is sent to Lambda.
        :param get_log: When true, the last 4 KB of the execution log are included in
                        the response.
        :return: The response from the function invocation.
        """
        try:
            response = self.lambda_client.invoke(
                FunctionName=function_name,
                Payload=json.dumps(function_params),
                LogType="Tail" if get_log else "None",
            )
            logger.info("Invoked function %s.", function_name)
        except ClientError:
            logger.exception("Couldn't invoke function %s.", function_name)
            raise
        return response

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def list_functions(self):
        """
        Lists the Lambda functions for the current account.
        """
        try:
            func_paginator = self.lambda_client.get_paginator("list_functions")
            for func_page in func_paginator.paginate():
                for func in func_page["Functions"]:
                    print(func["FunctionName"])
                    desc = func.get("Description")
                    if desc:
                        print(f"\t{desc}")
                    print(f"\t{func['Runtime']}: {func['Handler']}")
        except ClientError as err:
            logger.error(
                "Couldn't list functions. Here's why: %s: %s",
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def update_function_code(self, function_name, deployment_package):
        """
        Updates the code for a Lambda function by submitting a .zip archive that contains
        the code for the function.

        :param function_name: The name of the function to update.
        :param deployment_package: The function code to update, packaged as bytes in
                                   .zip format.
        :return: Data about the update, including the status.
        """
        try:
            response = self.lambda_client.update_function_code(
                FunctionName=function_name, ZipFile=deployment_package
            )
        except ClientError as err:
            logger.error(
                "Couldn't update function %s. Here's why: %s: %s",
                function_name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return response

class LambdaWrapper:
    def __init__(self, lambda_client, iam_resource):
        self.lambda_client = lambda_client
        self.iam_resource = iam_resource


    def update_function_configuration(self, function_name, env_vars):
        """
        Updates the environment variables for a Lambda function.

        :param function_name: The name of the function to update.
        :param env_vars: A dict of environment variables to update.
        :return: Data about the update, including the status.
        """
        try:
            response = self.lambda_client.update_function_configuration(
                FunctionName=function_name, Environment={"Variables": env_vars}
            )
        except ClientError as err:
            logger.error(
                "Couldn't update function configuration %s. Here's why: %s: %s",
                function_name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise
        else:
            return response

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Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en GitHub.

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Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en. GitHub

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Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en. GitHub

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Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en GitHub.

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Este ejemplo se ve mejor en GitHub. Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en GitHub.

En este ejemplo se muestra cómo registrar una AWS Lambda función como destino de un EventBridge evento programado de Amazon. El controlador Lambda escribe un mensaje descriptivo y los datos completos del evento en Amazon CloudWatch Logs para su posterior recuperación.

Es mejor ver este ejemplo en GitHub. Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en GitHub.

Conexión a una RDS base de datos de Amazon en una función Lambda mediante Python.

import json
import os
import boto3
import pymysql

# RDS settings
proxy_host_name = os.environ['PROXY_HOST_NAME']
port = int(os.environ['PORT'])
db_name = os.environ['DB_NAME']
db_user_name = os.environ['DB_USER_NAME']
aws_region = os.environ['AWS_REGION']


# Fetch RDS Auth Token
def get_auth_token():
    client = boto3.client('rds')
    token = client.generate_db_auth_token(
        DBHostname=proxy_host_name,
        Port=port
        DBUsername=db_user_name
        Region=aws_region
    )
    return token

def lambda_handler(event, context):
    token = get_auth_token()
    try:
        connection = pymysql.connect(
            host=proxy_host_name,
            user=db_user_name,
            password=token,
            db=db_name,
            port=port,
            ssl={'ca': 'Amazon RDS'}  # Ensure you have the CA bundle for SSL connection
        )
        
        with connection.cursor() as cursor:
            cursor.execute('SELECT %s + %s AS sum', (3, 2))
            result = cursor.fetchone()

        return result
        
    except Exception as e:
        return (f"Error: {str(e)}")  # Return an error message if an exception occurs 
    

Uso de un evento de Kinesis con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import base64
def lambda_handler(event, context):

    for record in event['Records']:
        try:
            print(f"Processed Kinesis Event - EventID: {record['eventID']}")
            record_data = base64.b64decode(record['kinesis']['data']).decode('utf-8')
            print(f"Record Data: {record_data}")
            # TODO: Do interesting work based on the new data
        except Exception as e:
            print(f"An error occurred {e}")
            raise e
    print(f"Successfully processed {len(event['Records'])} records.")

Consumo de un evento de DynamoDB con Lambda mediante Python.

import json

def lambda_handler(event, context):
    print(json.dumps(event, indent=2))

    for record in event['Records']:
        log_dynamodb_record(record)

def log_dynamodb_record(record):
    print(record['eventID'])
    print(record['eventName'])
    print(f"DynamoDB Record: {json.dumps(record['dynamodb'])}")

Consumo de un evento de Amazon DocumentDB con Lambda mediante Python.

import json

def lambda_handler(event, context):
    for record in event.get('events', []):
        log_document_db_event(record)
    return 'OK'

def log_document_db_event(record):
    event_data = record.get('event', {})
    operation_type = event_data.get('operationType', 'Unknown')
    db = event_data.get('ns', {}).get('db', 'Unknown')
    collection = event_data.get('ns', {}).get('coll', 'Unknown')
    full_document = event_data.get('fullDocument', {})

    print(f"Operation type: {operation_type}")
    print(f"db: {db}")
    print(f"collection: {collection}")
    print("Full document:", json.dumps(full_document, indent=2))

Consumir un MSK evento de Amazon con Lambda mediante Python.

import base64

def lambda_handler(event, context):
    # Iterate through keys
    for key in event['records']:
        print('Key:', key)
        # Iterate through records
        for record in event['records'][key]:
            print('Record:', record)
            # Decode base64
            msg = base64.b64decode(record['value']).decode('utf-8')
            print('Message:', msg)

Uso de un evento de S3 con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import json
import urllib.parse
import boto3

print('Loading function')

s3 = boto3.client('s3')


def lambda_handler(event, context):
    #print("Received event: " + json.dumps(event, indent=2))

    # Get the object from the event and show its content type
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')
    try:
        response = s3.get_object(Bucket=bucket, Key=key)
        print("CONTENT TYPE: " + response['ContentType'])
        return response['ContentType']
    except Exception as e:
        print(e)
        print('Error getting object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket))
        raise e
              

Consumir un SNS evento con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def lambda_handler(event, context):
    for record in event['Records']:
        process_message(record)
    print("done")

def process_message(record):
    try:
        message = record['Sns']['Message']
        print(f"Processed message {message}")
        # TODO; Process your record here
        
    except Exception as e:
        print("An error occurred")
        raise e

Consumir un SQS evento con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def lambda_handler(event, context):
    for message in event['Records']:
        process_message(message)
    print("done")

def process_message(message):
    try:
        print(f"Processed message {message['body']}")
        # TODO: Do interesting work based on the new message
    except Exception as err:
        print("An error occurred")
        raise err

Notificación de los errores de los elementos del lote de Kinesis con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def handler(event, context):
    records = event.get("Records")
    curRecordSequenceNumber = ""
    
    for record in records:
        try:
            # Process your record
            curRecordSequenceNumber = record["kinesis"]["sequenceNumber"]
        except Exception as e:
            # Return failed record's sequence number
            return {"batchItemFailures":[{"itemIdentifier": curRecordSequenceNumber}]}

    return {"batchItemFailures":[]}

Notificación de los errores de los elementos del lote de DynamoDB con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
def handler(event, context):
    records = event.get("Records")
    curRecordSequenceNumber = ""
    
    for record in records:
        try:
            # Process your record
            curRecordSequenceNumber = record["dynamodb"]["SequenceNumber"]
        except Exception as e:
            # Return failed record's sequence number
            return {"batchItemFailures":[{"itemIdentifier": curRecordSequenceNumber}]}

    return {"batchItemFailures":[]}

Notificación de errores de elementos de SQS lote con Lambda mediante Python.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0

def lambda_handler(event, context):
    if event:
        batch_item_failures = []
        sqs_batch_response = {}
     
        for record in event["Records"]:
            try:
                # process message
            except Exception as e:
                batch_item_failures.append({"itemIdentifier": record['messageId']})
        
        sqs_batch_response["batchItemFailures"] = batch_item_failures
        return sqs_batch_response