semvec/pypi-packages huggingface dataset:
layer-builder 0.1.1
Enables building AWS Lambda Layers from requirement files as part of CDK deployments
License: MIT
Requires Python: <4.0,>=3.10

# layer-builder
Simple library that supports building AWS Lambda layers as part of your AWS CDK build process.
Cross-platform (supports both Win and Mac), targeting both x86 and ARM chips, and 
based on you existing `requirements.txt`.

## Build from requirements
Using this library, you can build a layer containing the packages defined in a `requirements.txt`
file in your AWS CDK pipeline (or other tools). The packages are installed in a local directory
using the appropriate platform target. 

Wherever possible we attempt to limit the size of the resulting layer by removing any packages 
that are already native to Lambda (`boto`, `six`, `future`, etc.) or otherwise 
unnecessary. `additional_commands` and `cleanup_function` parameters can be used to further
reduce the size of the package by removing any unnecessary libraries.

```Python
from layer_builder import build_from_requirements
from constructs import Construct
from aws_cdk import Stack, aws_lambda as aws_lambda

class LayerStack(Stack):

    def __init__(
        self,
        scope: Construct,
        construct_id: str,
        **kwargs,
    ) -> None:
        super().__init__(scope, construct_id, **kwargs)
        
        build_from_requirements(
            "../../requirements.txt", # The packages to install
            "./build/layer", # Where to place the layer packages
            max_mb=20, # Check if the size of the layer is larger than expected
            clean=True, # Delete previous install
            graviton=True, # Specify targeting ARM architecture
        )
        self.my_layer = aws_lambda.LayerVersion(
            self,
            "my-layer",
            compatible_runtimes=[aws_lambda.Runtime.PYTHON_3_13],
            compatible_architectures=[aws_lambda.Architecture.ARM_64],
            code=aws_lambda.Code.from_asset("./build/layer"),
        )
```