Serverless Python: Managing Python Dependencies in AWS Lambda Layer

 build_layer.sh <layer_name> <path/to/requirements/file> <python-version> 

 scripts/build_layer.sh tensorflow requirements/tensorflow.txt 3.8 

tensorflow==2.4.0 

#!/bin/bash set -eo pipefail function usage { file_name=$0 echo "usage: ${file_name} <layer_name> <path/to/requirements.txt/file> <python_version>" exit 1 } layer_name=${1} requirements_file=${2} python_version=${3} if [[ -z "${requirements_file}" ]]; then requirements_file="requirements.txt" fi if [[ -z "${layer_name}" || ! -f "${requirements_file}" ]]; then usage fi layer_path=".layers/${layer_name}/python/lib/python${python_version}/site-packages" rm -rf "$layer_path" echo "Installing packages from ${requirements_file}" docker run --rm \ --user $UID \ --volume "$PWD:/var/task" \ --workdir /var/task \ --env CV_PYPI_USERNAME \ --env CV_PYPI_PASSWORD \ "lambci/lambda:build-python${python_version}" \ pip install -Ur "${requirements_file}" --target "${layer_path}" echo "Removing unnecessary packages from ${layer_path}" rm -rf "$layer_path"/{botocore,boto3}* echo "Removing unnecessary files/folders from ${layer_path}" find "$layer_path" -type f -name "*.pyc" -exec rm -rf {} + find "$layer_path" -type d -name "__pycache__" -exec rm -rf {} + find "$layer_path" -type d \( -name "tests" -o -name "test" \) -exec rm -rf {} + echo "Layer creation finished at ${layer_path}"