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The CDK Construct Library for AWS Lambda in Python

Project description

Amazon Lambda Python Library

---

cdk-constructs: Experimental

The APIs of higher level constructs in this module are experimental and under active development. They are subject to non-backward compatible changes or removal in any future version. These are not subject to the Semantic Versioning model and breaking changes will be announced in the release notes. This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.


This library provides constructs for Python Lambda functions.

To use this module, you will need to have Docker installed.

Python Function

Define a PythonFunction:

lambda_.PythonFunction(self, "MyFunction",
    entry="/path/to/my/function",  # required
    index="my_index.py",  # optional, defaults to 'index.py'
    handler="my_exported_func",  # optional, defaults to 'handler'
    runtime=Runtime.PYTHON_3_6
)

All other properties of lambda.Function are supported, see also the AWS Lambda construct library.

Module Dependencies

If requirements.txt or Pipfile exists at the entry path, the construct will handle installing all required modules in a Lambda compatible Docker container according to the runtime and with the Docker platform based on the target architecture of the Lambda function.

Python bundles are only recreated and published when a file in a source directory has changed. Therefore (and as a general best-practice), it is highly recommended to commit a lockfile with a list of all transitive dependencies and their exact versions. This will ensure that when any dependency version is updated, the bundle asset is recreated and uploaded.

To that end, we recommend using pipenv or poetry which has lockfile support.

Lambda with a requirements.txt

.
├── lambda_function.py # exports a function named 'handler'
├── requirements.txt # has to be present at the entry path

Lambda with a Pipfile

.
├── lambda_function.py # exports a function named 'handler'
├── Pipfile # has to be present at the entry path
├── Pipfile.lock # your lock file

Lambda with a poetry.lock

.
├── lambda_function.py # exports a function named 'handler'
├── pyproject.toml # has to be present at the entry path
├── poetry.lock # your poetry lock file

Lambda Layer Support

You may create a python-based lambda layer with PythonLayerVersion. If PythonLayerVersion detects a requirements.txt or Pipfile or poetry.lock with the associated pyproject.toml at the entry path, then PythonLayerVersion will include the dependencies inline with your code in the layer.

lambda_.PythonFunction(self, "MyFunction",
    entry="/path/to/my/function",
    layers=[
        lambda_.PythonLayerVersion(self, "MyLayer",
            entry="/path/to/my/layer"
        )
    ]
)

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