BundlingOptions

class aws_cdk.aws_lambda_python.BundlingOptions(*, asset_hash=None, asset_hash_type=None, build_args=None, environment=None, image=None, output_path_suffix=None)

Bases: object

(experimental) Options for bundling.

Parameters:
  • asset_hash (Optional[str]) – (experimental) Specify a custom hash for this asset. If assetHashType is set it must be set to AssetHashType.CUSTOM. For consistency, this custom hash will be SHA256 hashed and encoded as hex. The resulting hash will be the asset hash. NOTE: the hash is used in order to identify a specific revision of the asset, and used for optimizing and caching deployment activities related to this asset such as packaging, uploading to Amazon S3, etc. If you chose to customize the hash, you will need to make sure it is updated every time the asset changes, or otherwise it is possible that some deployments will not be invalidated. Default: - Based on assetHashType

  • asset_hash_type (Optional[AssetHashType]) – (experimental) Determines how asset hash is calculated. Assets will get rebuild and uploaded only if their hash has changed. If asset hash is set to SOURCE (default), then only changes to the source directory will cause the asset to rebuild. This means, for example, that in order to pick up a new dependency version, a change must be made to the source tree. Ideally, this can be implemented by including a dependency lockfile in your source tree or using fixed dependencies. If the asset hash is set to OUTPUT, the hash is calculated after bundling. This means that any change in the output will cause the asset to be invalidated and uploaded. Bear in mind that pip adds timestamps to dependencies it installs, which implies that in this mode Python bundles will always get rebuild and uploaded. Normally this is an anti-pattern since build Default: AssetHashType.SOURCE By default, hash is calculated based on the contents of the source directory. This means that only updates to the source will cause the asset to rebuild.

  • build_args (Optional[Mapping[str, str]]) – (experimental) Optional build arguments to pass to the default container. This can be used to customize the index URLs used for installing dependencies. This is not used if a custom image is provided. Default: - No build arguments.

  • environment (Optional[Mapping[str, str]]) – (experimental) Environment variables defined when bundling runs. Default: - no environment variables are defined.

  • image (Optional[DockerImage]) – (experimental) Docker image to use for bundling. If no options are provided, the default bundling image will be used. Dependencies will be installed using the default packaging commands and copied over from into the Lambda asset. Default: - Default bundling image.

  • output_path_suffix (Optional[str]) – (experimental) Output path suffix: the suffix for the directory into which the bundled output is written. Default: - ‘python’ for a layer, empty string otherwise.

Stability:

experimental

ExampleMetadata:

infused

Example:

entry = "/path/to/function"
image = DockerImage.from_build(entry)

lambda_.PythonFunction(self, "function",
    entry=entry,
    runtime=Runtime.PYTHON_3_8,
    bundling=lambda.BundlingOptions(
        build_args={"PIP_INDEX_URL": "https://your.index.url/simple/", "PIP_EXTRA_INDEX_URL": "https://your.extra-index.url/simple/"}
    )
)

Attributes

asset_hash

(experimental) Specify a custom hash for this asset.

If assetHashType is set it must be set to AssetHashType.CUSTOM. For consistency, this custom hash will be SHA256 hashed and encoded as hex. The resulting hash will be the asset hash.

NOTE: the hash is used in order to identify a specific revision of the asset, and used for optimizing and caching deployment activities related to this asset such as packaging, uploading to Amazon S3, etc. If you chose to customize the hash, you will need to make sure it is updated every time the asset changes, or otherwise it is possible that some deployments will not be invalidated.

Default:
  • Based on assetHashType

Stability:

experimental

asset_hash_type

(experimental) Determines how asset hash is calculated. Assets will get rebuild and uploaded only if their hash has changed.

If asset hash is set to SOURCE (default), then only changes to the source directory will cause the asset to rebuild. This means, for example, that in order to pick up a new dependency version, a change must be made to the source tree. Ideally, this can be implemented by including a dependency lockfile in your source tree or using fixed dependencies.

If the asset hash is set to OUTPUT, the hash is calculated after bundling. This means that any change in the output will cause the asset to be invalidated and uploaded. Bear in mind that pip adds timestamps to dependencies it installs, which implies that in this mode Python bundles will always get rebuild and uploaded. Normally this is an anti-pattern since build

Default:

AssetHashType.SOURCE By default, hash is calculated based on the contents of the source directory. This means that only updates to the source will cause the asset to rebuild.

Stability:

experimental

build_args

(experimental) Optional build arguments to pass to the default container.

This can be used to customize the index URLs used for installing dependencies. This is not used if a custom image is provided.

Default:
  • No build arguments.

Stability:

experimental

environment

(experimental) Environment variables defined when bundling runs.

Default:
  • no environment variables are defined.

Stability:

experimental

image

(experimental) Docker image to use for bundling.

If no options are provided, the default bundling image will be used. Dependencies will be installed using the default packaging commands and copied over from into the Lambda asset.

Default:
  • Default bundling image.

Stability:

experimental

output_path_suffix

the suffix for the directory into which the bundled output is written.

Default:
  • ‘python’ for a layer, empty string otherwise.

Stability:

experimental

Type:

(experimental) Output path suffix