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This is an AWS Lambda Python project template with production ready setup. You can easily generate a folder structure as a foundation,then plugin your business code, then go to production.

Best practices and automation features included in this template:

  • Automate Project Setup with DevOps Best Practices

  • Internal Enterprise Standard of AWS / Python Project Development Workflow

  • Determinative Dependency Management

  • Centralized Config Management

  • Git Branching and CI/CD Strategy

  • Multi-Environment Deployment

  • Multi AWS Regions and Multi AWS Accounts Deployment

  • Infrastructure as Code

  • Human-in-the-Loop Pipeline Development and Deployment

  • AWS Lambda Function Application Code and Unit Test Best Practice

  • Continuously Build Versioned AWS Lambda Dependency Layer

  • AWS Lambda Function Deployment Automation

  • Versioned Build Artifacts Management

  • Continuously Release to Production Using Semantic Versioning

  • Immutable Deployment and Rollback to Historical Version


All the best practice used in this repo is based on my career experience, and my personal opinion. I have done over 50+ AWS microservice projects in dev and 10+ projects in production environments. It is the best practice I am using for years. In average, it took me around months of work to setup a production ready git repo with proper CI/CD strategy. This project template saves me efforts to setup the DevOps automation, and allows me to focus on the business logic, and greatly reduces the releasing cycle. In the three most recent production projects, it took me around 1 week from scratch to production, and fastest releasing cycle is reduced to 1 day. Again, it is my personal best practice, please use it at your own risk.


Enter the following command, it will use the latest template.

pip install cookiecutter

Or, you can use a specific released version, you can find full list of release at here.

# use specific version
cookiecutter --checkout tags/${version}
# for example (v5 is the latest as of 2023-02-18)
cookiecutter --checkout tags/v6

Then fill in some information:

package_name [my_package]: ...
author_name [Firstname Lastname]: ...
author_email []: ...

Then it will generate a Git repo folder structures like this:

  • /bin/*.py: binary executable scripts for automation, devops, CI/CD

  • /config/...: non-sensitive multi-env config management

  • /${package_name}/... your python project source code

  • /lambda_app/...: AWS Lambda microservices management and deployment

  • /tests/...: unit test

  • /tests_int/..: integration test

  • /.coveragerc: code coverage test config

  • /Makefile: the automation script CLI tools for local development

  • /pyproject.toml and /poetry.lock: determinative dependency management

  • (Optional) /codebuild-config.json and /buildspec.yml: the CI/CD integration with AWS CodeBuild, but you can use any other CI/CD platform (GitHub Actions, Jenkins, CircleCI, GitLab pipeline, BitBucket, Pipeline, etc …), and just copy and paste the following shell scripts to your CI workflow definition file:

pip install poetry==1.2.2 --quiet --disable-pip-version-check
pip install -r requirements-automation.txt --quiet --disable-pip-version-check
python ./bin/
./.venv/bin/python ./bin/
./.venv/bin/python ./bin/
./.venv/bin/python ./bin/

We have an example project generated from this template aws_lambda_python_example-project. Please take a look at it.

DevOps Best Practices