Metadata-Version: 2.1
Name: aws-cdk.aws-lambda
Version: 1.117.0
Summary: The CDK Construct Library for AWS::Lambda
Home-page: https://github.com/aws/aws-cdk
Author: Amazon Web Services
License: Apache-2.0
Project-URL: Source, https://github.com/aws/aws-cdk.git
Description: # AWS Lambda Construct Library
        
        <!--BEGIN STABILITY BANNER-->---
        
        
        ![cfn-resources: Stable](https://img.shields.io/badge/cfn--resources-stable-success.svg?style=for-the-badge)
        
        ![cdk-constructs: Stable](https://img.shields.io/badge/cdk--constructs-stable-success.svg?style=for-the-badge)
        
        ---
        <!--END STABILITY BANNER-->
        
        This construct library allows you to define AWS Lambda Functions.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler"))
        )
        ```
        
        ## Handler Code
        
        The `lambda.Code` class includes static convenience methods for various types of
        runtime code.
        
        * `lambda.Code.fromBucket(bucket, key[, objectVersion])` - specify an S3 object
          that contains the archive of your runtime code.
        * `lambda.Code.fromInline(code)` - inline the handle code as a string. This is
          limited to supported runtimes and the code cannot exceed 4KiB.
        * `lambda.Code.fromAsset(path)` - specify a directory or a .zip file in the local
          filesystem which will be zipped and uploaded to S3 before deployment. See also
          [bundling asset code](#bundling-asset-code).
        * `lambda.Code.fromDockerBuild(path, options)` - use the result of a Docker
          build as code. The runtime code is expected to be located at `/asset` in the
          image and will be zipped and uploaded to S3 as an asset.
        
        The following example shows how to define a Python function and deploy the code
        from the local directory `my-lambda-handler` to it:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        lambda_.Function(self, "MyLambda",
            code=lambda_.Code.from_asset(path.join(__dirname, "my-lambda-handler")),
            handler="index.main",
            runtime=lambda_.Runtime.PYTHON_3_6
        )
        ```
        
        When deploying a stack that contains this code, the directory will be zip
        archived and then uploaded to an S3 bucket, then the exact location of the S3
        objects will be passed when the stack is deployed.
        
        During synthesis, the CDK expects to find a directory on disk at the asset
        directory specified. Note that we are referencing the asset directory relatively
        to our CDK project directory. This is especially important when we want to share
        this construct through a library. Different programming languages will have
        different techniques for bundling resources into libraries.
        
        ## Docker Images
        
        Lambda functions allow specifying their handlers within docker images. The docker
        image can be an image from ECR or a local asset that the CDK will package and load
        into ECR.
        
        The following `DockerImageFunction` construct uses a local folder with a
        Dockerfile as the asset that will be used as the function handler.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        DockerImageFunction(self, "AssetFunction",
            code=DockerImageCode.from_image_asset(path.join(__dirname, "docker-handler"))
        )
        ```
        
        You can also specify an image that already exists in ECR as the function handler.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_ecr as ecr
        
        repo = ecr.Repository(self, "Repository")
        
        DockerImageFunction(self, "ECRFunction",
            code=DockerImageCode.from_ecr(repo)
        )
        ```
        
        ## Execution Role
        
        Lambda functions assume an IAM role during execution. In CDK by default, Lambda
        functions will use an autogenerated Role if one is not provided.
        
        The autogenerated Role is automatically given permissions to execute the Lambda
        function. To reference the autogenerated Role:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler"))
        )
        
        fn.role
        ```
        
        You can also provide your own IAM role. Provided IAM roles will not automatically
        be given permissions to execute the Lambda function. To provide a role and grant
        it appropriate permissions:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_iam as iam
        
        my_role = iam.Role(self, "My Role",
            assumed_by=iam.ServicePrincipal("sns.amazonaws.com")
        )
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler")),
            role=my_role
        )
        
        my_role.add_managed_policy(iam.ManagedPolicy.from_aws_managed_policy_name("service-role/AWSLambdaBasicExecutionRole"))
        my_role.add_managed_policy(iam.ManagedPolicy.from_aws_managed_policy_name("service-role/AWSLambdaVPCAccessExecutionRole"))
        ```
        
        ## Resource-based Policies
        
        AWS Lambda supports resource-based policies for controlling access to Lambda
        functions and layers on a per-resource basis. In particular, this allows you to
        give permission to AWS services and other AWS accounts to modify and invoke your
        functions. You can also restrict permissions given to AWS services by providing
        a source account or ARN (representing the account and identifier of the resource
        that accesses the function or layer).
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_iam as iam
        
        principal = iam.ServicePrincipal("my-service")
        
        fn.grant_invoke(principal)
        
        # Equivalent to:
        fn.add_permission("my-service Invocation",
            principal=principal
        )
        ```
        
        For more information, see [Resource-based
        policies](https://docs.aws.amazon.com/lambda/latest/dg/access-control-resource-based.html)
        in the AWS Lambda Developer Guide.
        
        Providing an unowned principal (such as account principals, generic ARN
        principals, service principals, and principals in other accounts) to a call to
        `fn.grantInvoke` will result in a resource-based policy being created. If the
        principal in question has conditions limiting the source account or ARN of the
        operation (see above), these conditions will be automatically added to the
        resource policy.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_iam as iam
        
        service_principal = iam.ServicePrincipal("my-service")
        source_arn = "arn:aws:s3:::my-bucket"
        source_account = "111122223333"
        service_principal_with_conditions = service_principal.with_conditions({
            "ArnLike": {
                "aws:_source_arn": source_arn
            },
            "StringEquals": {
                "aws:_source_account": source_account
            }
        })
        
        fn.grant_invoke(service_principal_with_conditions)
        
        # Equivalent to:
        fn.add_permission("my-service Invocation",
            principal=service_principal,
            source_arn=source_arn,
            source_account=source_account
        )
        ```
        
        ## Versions
        
        You can use
        [versions](https://docs.aws.amazon.com/lambda/latest/dg/configuration-versions.html)
        to manage the deployment of your AWS Lambda functions. For example, you can
        publish a new version of a function for beta testing without affecting users of
        the stable production version.
        
        The function version includes the following information:
        
        * The function code and all associated dependencies.
        * The Lambda runtime that executes the function.
        * All of the function settings, including the environment variables.
        * A unique Amazon Resource Name (ARN) to identify this version of the function.
        
        You could create a version to your lambda function using the `Version` construct.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction", ...)
        version = Version(self, "MyVersion",
            lambda_=fn
        )
        ```
        
        The major caveat to know here is that a function version must always point to a
        specific 'version' of the function. When the function is modified, the version
        will continue to point to the 'then version' of the function.
        
        One way to ensure that the `lambda.Version` always points to the latest version
        of your `lambda.Function` is to set an environment variable which changes at
        least as often as your code does. This makes sure the function always has the
        latest code. For instance -
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        code_version = "stringOrMethodToGetCodeVersion"
        fn = lambda_.Function(self, "MyFunction",
            environment={
                "CodeVersionString": code_version
            }
        )
        ```
        
        The `fn.latestVersion` property returns a `lambda.IVersion` which represents
        the `$LATEST` pseudo-version.
        
        However, most AWS services require a specific AWS Lambda version,
        and won't allow you to use `$LATEST`. Therefore, you would normally want
        to use `lambda.currentVersion`.
        
        The `fn.currentVersion` property can be used to obtain a `lambda.Version`
        resource that represents the AWS Lambda function defined in your application.
        Any change to your function's code or configuration will result in the creation
        of a new version resource. You can specify options for this version through the
        `currentVersionOptions` property.
        
        NOTE: The `currentVersion` property is only supported when your AWS Lambda function
        uses either `lambda.Code.fromAsset` or `lambda.Code.fromInline`. Other types
        of code providers (such as `lambda.Code.fromBucket`) require that you define a
        `lambda.Version` resource directly since the CDK is unable to determine if
        their contents had changed.
        
        ### `currentVersion`: Updated hashing logic
        
        To produce a new lambda version each time the lambda function is modified, the
        `currentVersion` property under the hood, computes a new logical id based on the
        properties of the function. This informs CloudFormation that a new
        `AWS::Lambda::Version` resource should be created pointing to the updated Lambda
        function.
        
        However, a bug was introduced in this calculation that caused the logical id to
        change when it was not required (ex: when the Function's `Tags` property, or
        when the `DependsOn` clause was modified). This caused the deployment to fail
        since the Lambda service does not allow creating duplicate versions.
        
        This has been fixed in the AWS CDK but *existing* users need to opt-in via a
        [feature flag](https://docs.aws.amazon.com/cdk/latest/guide/featureflags.html). Users who have run `cdk init` since this fix will be opted in,
        by default.
        
        Existing users will need to enable the [feature flag](https://docs.aws.amazon.com/cdk/latest/guide/featureflags.html)
        `@aws-cdk/aws-lambda:recognizeVersionProps`. Since CloudFormation does not
        allow duplicate versions, they will also need to make some modification to
        their function so that a new version can be created. Any trivial change such as
        a whitespace change in the code or a no-op environment variable will suffice.
        
        When the new logic is in effect, you may rarely come across the following error:
        `The following properties are not recognized as version properties`. This will
        occur, typically when [property overrides](https://docs.aws.amazon.com/cdk/latest/guide/cfn_layer.html#cfn_layer_raw) are used, when a new property
        introduced in `AWS::Lambda::Function` is used that CDK is still unaware of.
        
        To overcome this error, use the API `Function.classifyVersionProperty()` to
        record whether a new version should be generated when this property is changed.
        This can be typically determined by checking whether the property can be
        modified using the *[UpdateFunctionConfiguration](https://docs.aws.amazon.com/lambda/latest/dg/API_UpdateFunctionConfiguration.html)* API or not.
        
        ## Aliases
        
        You can define one or more
        [aliases](https://docs.aws.amazon.com/lambda/latest/dg/configuration-aliases.html)
        for your AWS Lambda function. A Lambda alias is like a pointer to a specific
        Lambda function version. Users can access the function version using the alias
        ARN.
        
        The `version.addAlias()` method can be used to define an AWS Lambda alias that
        points to a specific version.
        
        The following example defines an alias named `live` which will always point to a
        version that represents the function as defined in your CDK app. When you change
        your lambda code or configuration, a new resource will be created. You can
        specify options for the current version through the `currentVersionOptions`
        property.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.core as cdk
        
        
        fn = Function(self, "MyFunction",
            current_version_options=VersionOptions(
                removal_policy=cdk.RemovalPolicy.RETAIN, # retain old versions
                retry_attempts=1
            ),
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler"))
        )
        
        fn.current_version.add_alias("live")
        ```
        
        ## Layers
        
        The `lambda.LayerVersion` class can be used to define Lambda layers and manage
        granting permissions to other AWS accounts or organizations.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        layer = lambda_.LayerVersion(stack, "MyLayer",
            code=lambda_.Code.from_asset(path.join(__dirname, "layer-code")),
            compatible_runtimes=[lambda_.Runtime.NODEJS_10_X],
            license="Apache-2.0",
            description="A layer to test the L2 construct"
        )
        
        # To grant usage by other AWS accounts
        layer.add_permission("remote-account-grant", account_id=aws_account_id)
        
        # To grant usage to all accounts in some AWS Ogranization
        # layer.grantUsage({ accountId: '*', organizationId });
        
        lambda_.Function(stack, "MyLayeredLambda",
            code=lambda_.InlineCode("foo"),
            handler="index.handler",
            runtime=lambda_.Runtime.NODEJS_10_X,
            layers=[layer]
        )
        ```
        
        By default, updating a layer creates a new layer version, and CloudFormation will delete the old version as part of the stack update.
        
        Alternatively, a removal policy can be used to retain the old version:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.core as cdk
        
        
        LayerVersion(self, "MyLayer",
            removal_policy=cdk.RemovalPolicy.RETAIN,
            code=Code.from_asset(path.join(__dirname, "lambda-handler"))
        )
        ```
        
        ## Lambda Insights
        
        Lambda functions can be configured to use CloudWatch [Lambda Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Lambda-Insights.html)
        which provides low-level runtime metrics for a Lambda functions.
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        import aws_cdk.lambda as lambda_
        
        
        Function(self, "MyFunction",
            insights_version=lambda_.LambdaInsightsVersion.VERSION_1_0_98_0
        )
        ```
        
        If the version of insights is not yet available in the CDK, you can also provide the ARN directly as so -
        
        ```python
        # Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
        layer_arn = "arn:aws:lambda:us-east-1:580247275435:layer:LambdaInsightsExtension:14"
        Function(self, "MyFunction",
            insights_version=lambda_.LambdaInsightsVersion.from_insight_version_arn(layer_arn)
        )
        ```
        
        ## Event Rule Target
        
        You can use an AWS Lambda function as a target for an Amazon CloudWatch event
        rule:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_events as events
        import aws_cdk.aws_events_targets as targets
        
        rule = events.Rule(self, "Schedule Rule",
            schedule=events.Schedule.cron(minute="0", hour="4")
        )
        rule.add_target(targets.LambdaFunction(fn))
        ```
        
        ## Event Sources
        
        AWS Lambda supports a [variety of event sources](https://docs.aws.amazon.com/lambda/latest/dg/invoking-lambda-function.html).
        
        In most cases, it is possible to trigger a function as a result of an event by
        using one of the `add<Event>Notification` methods on the source construct. For
        example, the `s3.Bucket` construct has an `onEvent` method which can be used to
        trigger a Lambda when an event, such as PutObject occurs on an S3 bucket.
        
        An alternative way to add event sources to a function is to use `function.addEventSource(source)`.
        This method accepts an `IEventSource` object. The module **@aws-cdk/aws-lambda-event-sources**
        includes classes for the various event sources supported by AWS Lambda.
        
        For example, the following code adds an SQS queue as an event source for a function:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_lambda_event_sources as eventsources
        import aws_cdk.aws_sqs as sqs
        
        queue = sqs.Queue(self, "Queue")
        fn.add_event_source(eventsources.SqsEventSource(queue))
        ```
        
        The following code adds an S3 bucket notification as an event source:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_lambda_event_sources as eventsources
        import aws_cdk.aws_s3 as s3
        
        bucket = s3.Bucket(self, "Bucket")
        fn.add_event_source(eventsources.S3EventSource(bucket,
            events=[s3.EventType.OBJECT_CREATED, s3.EventType.OBJECT_REMOVED],
            filters=[NotificationKeyFilter(prefix="subdir/")]
        ))
        ```
        
        See the documentation for the **@aws-cdk/aws-lambda-event-sources** module for more details.
        
        ## Lambda with DLQ
        
        A dead-letter queue can be automatically created for a Lambda function by
        setting the `deadLetterQueueEnabled: true` configuration.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_inline("exports.handler = function(event, ctx, cb) { return cb(null, \"hi\"); }"),
            dead_letter_queue_enabled=True
        )
        ```
        
        It is also possible to provide a dead-letter queue instead of getting a new queue created:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_sqs as sqs
        
        
        dlq = sqs.Queue(self, "DLQ")
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_inline("exports.handler = function(event, ctx, cb) { return cb(null, \"hi\"); }"),
            dead_letter_queue=dlq
        )
        ```
        
        See [the AWS documentation](https://docs.aws.amazon.com/lambda/latest/dg/dlq.html)
        to learn more about AWS Lambdas and DLQs.
        
        ## Lambda with X-Ray Tracing
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_inline("exports.handler = function(event, ctx, cb) { return cb(null, \"hi\"); }"),
            tracing=Tracing.ACTIVE
        )
        ```
        
        See [the AWS documentation](https://docs.aws.amazon.com/lambda/latest/dg/lambda-x-ray.html)
        to learn more about AWS Lambda's X-Ray support.
        
        ## Lambda with Profiling
        
        The following code configures the lambda function with CodeGuru profiling. By default, this creates a new CodeGuru
        profiling group -
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_lambda as lambda_
        
        
        fn = Function(self, "MyFunction",
            runtime=Runtime.PYTHON_3_6,
            handler="index.handler",
            code=Code.from_asset("lambda-handler"),
            profiling=True
        )
        ```
        
        The `profilingGroup` property can be used to configure an existing CodeGuru profiler group.
        
        CodeGuru profiling is supported for all Java runtimes and Python3.6+ runtimes.
        
        See [the AWS documentation](https://docs.aws.amazon.com/codeguru/latest/profiler-ug/setting-up-lambda.html)
        to learn more about AWS Lambda's Profiling support.
        
        ## Lambda with Reserved Concurrent Executions
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        fn = Function(self, "MyFunction",
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_inline("exports.handler = function(event, ctx, cb) { return cb(null, \"hi\"); }"),
            reserved_concurrent_executions=100
        )
        ```
        
        See [the AWS documentation](https://docs.aws.amazon.com/lambda/latest/dg/concurrent-executions.html)
        managing concurrency.
        
        ## AutoScaling
        
        You can use Application AutoScaling to automatically configure the provisioned concurrency for your functions. AutoScaling can be set to track utilization or be based on a schedule. To configure AutoScaling on a function alias:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_autoscaling as autoscaling
        
        alias = Alias(self, "Alias",
            alias_name="prod",
            version=fn.latest_version
        )
        
        # Create AutoScaling target
        as = alias.add_auto_scaling(max_capacity=50)
        
        # Configure Target Tracking
        as.scale_on_utilization(
            utilization_target=0.5
        )
        
        # Configure Scheduled Scaling
        as.scale_on_schedule("ScaleUpInTheMorning",
            schedule=autoscaling.Schedule.cron(hour="8", minute="0"),
            min_capacity=20
        )
        ```
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_applicationautoscaling as appscaling
        import aws_cdk.core as cdk
        import ...lib as lambda_
        
        #
        # Stack verification steps:
        # aws application-autoscaling describe-scalable-targets --service-namespace lambda --resource-ids function:<function name>:prod
        # has a minCapacity of 3 and maxCapacity of 50
        #
        class TestStack(cdk.Stack):
            def __init__(self, scope, id):
                super().__init__(scope, id)
        
                fn = lambda_.Function(self, "MyLambda",
                    code=lambda_.InlineCode("exports.handler = async () => { console.log('hello world'); };"),
                    handler="index.handler",
                    runtime=lambda_.Runtime.NODEJS_10_X
                )
        
                version = fn.add_version("1", undefined, "integ-test")
        
                alias = lambda_.Alias(self, "Alias",
                    alias_name="prod",
                    version=version
                )
        
                scaling_target = alias.add_auto_scaling(min_capacity=3, max_capacity=50)
        
                scaling_target.scale_on_utilization(
                    utilization_target=0.5
                )
        
                scaling_target.scale_on_schedule("ScaleUpInTheMorning",
                    schedule=appscaling.Schedule.cron(hour="8", minute="0"),
                    min_capacity=20
                )
        
                scaling_target.scale_on_schedule("ScaleDownAtNight",
                    schedule=appscaling.Schedule.cron(hour="20", minute="0"),
                    max_capacity=20
                )
        
                cdk.CfnOutput(self, "FunctionName",
                    value=fn.function_name
                )
        
        app = cdk.App()
        
        TestStack(app, "aws-lambda-autoscaling")
        
        app.synth()
        ```
        
        See [the AWS documentation](https://docs.aws.amazon.com/lambda/latest/dg/invocation-scaling.html) on autoscaling lambda functions.
        
        ## Log Group
        
        Lambda functions automatically create a log group with the name `/aws/lambda/<function-name>` upon first execution with
        log data set to never expire.
        
        The `logRetention` property can be used to set a different expiration period.
        
        It is possible to obtain the function's log group as a `logs.ILogGroup` by calling the `logGroup` property of the
        `Function` construct.
        
        By default, CDK uses the AWS SDK retry options when creating a log group. The `logRetentionRetryOptions` property
        allows you to customize the maximum number of retries and base backoff duration.
        
        *Note* that, if either `logRetention` is set or `logGroup` property is called, a [CloudFormation custom
        resource](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-cfn-customresource.html) is added
        to the stack that pre-creates the log group as part of the stack deployment, if it already doesn't exist, and sets the
        correct log retention period (never expire, by default).
        
        *Further note* that, if the log group already exists and the `logRetention` is not set, the custom resource will reset
        the log retention to never expire even if it was configured with a different value.
        
        ## FileSystem Access
        
        You can configure a function to mount an Amazon Elastic File System (Amazon EFS) to a
        directory in your runtime environment with the `filesystem` property. To access Amazon EFS
        from lambda function, the Amazon EFS access point will be required.
        
        The following sample allows the lambda function to mount the Amazon EFS access point to `/mnt/msg` in the runtime environment and access the filesystem with the POSIX identity defined in `posixUser`.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_ec2 as ec2
        import aws_cdk.aws_efs as efs
        
        
        # create a new VPC
        vpc = ec2.Vpc(self, "VPC")
        
        # create a new Amazon EFS filesystem
        file_system = efs.FileSystem(self, "Efs", vpc=vpc)
        
        # create a new access point from the filesystem
        access_point = file_system.add_access_point("AccessPoint",
            # set /export/lambda as the root of the access point
            path="/export/lambda",
            # as /export/lambda does not exist in a new efs filesystem, the efs will create the directory with the following createAcl
            create_acl=Acl(
                owner_uid="1001",
                owner_gid="1001",
                permissions="750"
            ),
            # enforce the POSIX identity so lambda function will access with this identity
            posix_user=PosixUser(
                uid="1001",
                gid="1001"
            )
        )
        
        fn = Function(self, "MyLambda",
            # mount the access point to /mnt/msg in the lambda runtime environment
            filesystem=FileSystem.from_efs_access_point(access_point, "/mnt/msg"),
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler")),
            vpc=vpc
        )
        ```
        
        ## Singleton Function
        
        The `SingletonFunction` construct is a way to guarantee that a lambda function will be guaranteed to be part of the stack,
        once and only once, irrespective of how many times the construct is declared to be part of the stack. This is guaranteed
        as long as the `uuid` property and the optional `lambdaPurpose` property stay the same whenever they're declared into the
        stack.
        
        A typical use case of this function is when a higher level construct needs to declare a Lambda function as part of it but
        needs to guarantee that the function is declared once. However, a user of this higher level construct can declare it any
        number of times and with different properties. Using `SingletonFunction` here with a fixed `uuid` will guarantee this.
        
        For example, the `LogRetention` construct requires only one single lambda function for all different log groups whose
        retention it seeks to manage.
        
        ## Bundling Asset Code
        
        When using `lambda.Code.fromAsset(path)` it is possible to bundle the code by running a
        command in a Docker container. The asset path will be mounted at `/asset-input`. The
        Docker container is responsible for putting content at `/asset-output`. The content at
        `/asset-output` will be zipped and used as Lambda code.
        
        Example with Python:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        Function(self, "Function",
            code=Code.from_asset(path.join(__dirname, "my-python-handler"),
                bundling={
                    "image": Runtime.PYTHON_3_8.bundling_image,
                    "command": ["bash", "-c", "pip install -r requirements.txt -t /asset-output && cp -au . /asset-output"
                    ]
                }
            ),
            runtime=Runtime.PYTHON_3_8,
            handler="index.handler"
        )
        ```
        
        Runtimes expose a `bundlingImage` property that points to the [AWS SAM](https://github.com/awslabs/aws-sam-cli) build image.
        
        Use `cdk.DockerImage.fromRegistry(image)` to use an existing image or
        `cdk.DockerImage.fromBuild(path)` to build a specific image:
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.core as cdk
        
        
        Function(self, "Function",
            code=Code.from_asset("/path/to/handler",
                bundling=BundlingOptions(
                    image=cdk.DockerImage.from_build("/path/to/dir/with/DockerFile",
                        build_args={
                            "ARG1": "value1"
                        }
                    ),
                    command=["my", "cool", "command"]
                )
            ),
            runtime=Runtime.PYTHON_3_8,
            handler="index.handler"
        )
        ```
        
        ## Language-specific APIs
        
        Language-specific higher level constructs are provided in separate modules:
        
        * `@aws-cdk/aws-lambda-nodejs`: [Github](https://github.com/aws/aws-cdk/tree/master/packages/%40aws-cdk/aws-lambda-nodejs) & [CDK Docs](https://docs.aws.amazon.com/cdk/api/latest/docs/aws-lambda-nodejs-readme.html)
        * `@aws-cdk/aws-lambda-python`: [Github](https://github.com/aws/aws-cdk/tree/master/packages/%40aws-cdk/aws-lambda-python) & [CDK Docs](https://docs.aws.amazon.com/cdk/api/latest/docs/aws-lambda-python-readme.html)
        
        ## Code Signing
        
        Code signing for AWS Lambda helps to ensure that only trusted code runs in your Lambda functions.
        When enabled, AWS Lambda checks every code deployment and verifies that the code package is signed by a trusted source.
        For more information, see [Configuring code signing for AWS Lambda](https://docs.aws.amazon.com/lambda/latest/dg/configuration-codesigning.html).
        The following code configures a function with code signing.
        
        ```python
        # Example automatically generated. See https://github.com/aws/jsii/issues/826
        import aws_cdk.aws_signer as signer
        
        
        signing_profile = signer.SigningProfile(self, "SigningProfile",
            platform=signer.Platform.AWS_LAMBDA_SHA384_ECDSA
        )
        
        code_signing_config = CodeSigningConfig(self, "CodeSigningConfig",
            signing_profiles=[signing_profile]
        )
        
        Function(self, "Function",
            code_signing_config=code_signing_config,
            runtime=Runtime.NODEJS_12_X,
            handler="index.handler",
            code=Code.from_asset(path.join(__dirname, "lambda-handler"))
        )
        ```
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Typing :: Typed
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved
Classifier: Framework :: AWS CDK
Classifier: Framework :: AWS CDK :: 1
Requires-Python: >=3.6
Description-Content-Type: text/markdown
