feat(lambda-python-alpha): cache python lambda dependencies usig lambda layer

[orshemtov]

Issue # (if applicable)

Closes #23829

Reason for this change

cdk synth takes very long to synthesize a PythonFunction construct, because the dependencies are getting installed regardless if there was any changes made to them.

The dependencies, whether they are specified in a requirements.txt file, a poetry.lock file or a pipenv.lock file, get installed as part of the CMD in the bundling phase, meaning that we don't use docker's cache or any other caching mechanism and re-install the dependencies from the internet every time.

Trying to compute a custom assetHash based on the dependencies file won't work, because of where the call for install is currently placed (in the CMD of the bundling phase container)

This causes deployment times to rise significantly, in some cases from minutes to hours.

Description of changes

The PythonFunction construct in function.ts will introduce a new prop: layer which is defined as:

/**
   * Whether or not to create a layer for the function's dependencies.
   * @default - No layer is created.
   */
  readonly layer?: boolean;

If layer is true, we create the layer before the constructor of PythonFunction is called, and attach the layer to PythonFunction in the constructor's layers prop.

To control whether dependencies are installed during the Bundling phase, a new prop is introduced to BundlingOptions and is defined as:

  /**
   * Whether or not to install the dependencies
   * @default true
   */
  readonly installDependencies?: boolean;

Since bundling is used for the PythonLayerVersion and PythonFunction props, this prop defaults to true, to not alter any behavior of PythonLayerVersion.

When initializing a PythonFunction, if layer is true, and we are creating a layer, the installDependencies is set to true for the layer creation, and false for the constructor of PythonFunction, so dependencies will only be installed in the layer.

To compute the assetHash for the layer, I added a dependenciesHash(entry) method inside the Packaging class, with this we can compute the hash of the lock file, and in the created layer we can use AssetHashType.CUSTOM with this hash.

bundling: {
          ...props.bundling,
          installDependencies: true,
          // assetExcludes: ["TODO: exclude everything except the dependencies file"]
          assetHashType: AssetHashType.CUSTOM,
          assetHash: Packaging.dependenciesHash(entry),
        },

Description of how you validated changes

This is my first PR here, and in open source in general, I am working on adding and validating the changes with unit tests, I would appreciate some help with that, if possible.

Checklist

• My code adheres to the CONTRIBUTING GUIDE and DESIGN GUIDELINES

TODOs

• assetExcludes for the created layer, exclude all files besides the lock file
• Add tests
• Edit README.md

---

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache-2.0 license

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[orshemtov]

Exemption Request

This is a first PR for me in this codebase, i have the general idea of the design and the required code changes, and could use some help with the PR process

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