kilna/python-lambda repository overview

⁠python-lambda-docker

Lightweight docker image for running, testing, packaging and deploying python-based AWS lambda functions

⁠Links

• Docker: python-lambda⁠
• GitHub: python-lambda-docker⁠
• Based on the python-lambda library⁠ by nficano⁠

⁠Purpose

I needed a Docker-based environment in which to host AWS python lambda functions for the purpose of testing and building them... python-lambda works well under virtualenv for development, but build and deployment automation require a clean and reproducible environment to operate in. Our CI system already supported Docker as a containerization system, so it was the obvious choice.

In order to use this, you will have your project derive its own Dockerfile based on a base python-lambda image corresponding to which version of Python you wish to run.

⁠Usage

An example of a usable project can be found in the example/⁠ directory. The lambda function in service.py⁠ takes a JSON input file like the one provided in event.json⁠ and returns an ASCII-art version of the text described in it. The Dockerfile⁠ derives from python-lambda as a base image, and loading the example directory contents into the image at the path /lambda, then installs dependencies from the requirements.txt⁠ file.

⁠Building a Derived Docker Image

To build a docker image from the provided example/⁠ called example-lambda-image with the ASCII-art lambda function in it, run:

$ cd example/
$ docker build --tag example-lambda-image .

Any time you make changes to the example project, you'll need to re-run the docker build command above, or you can investigate using docker volumes to sync local filesystem changes into the container.

⁠Switching Python Versions

The example Dockerfile⁠ uses a :latest docker tag in the FROM line, which is currently the same as :3.6, but if you wish to use a different Python version you can change this. Supported Python versions are 2.7 and 3.6. To use Python version 2.7 change the first line of the example Dockerfile⁠ to:

FROM kilna/python-lambda:2.7

You will also need to change the following line in config.yaml⁠

runtime: python2.7

⁠Executing the Lambda Function

If you want to execute the lambda function against the event.json⁠ input file:

$ docker run example-lambda-image lambda invoke
 _  _     _ _                        _    _ _
| || |___| | |___    __ __ _____ _ _| |__| | |
| __ / -_) | / _ \_  \ V  V / _ \ '_| / _` |_|
|_||_\___|_|_\___( )  \_/\_/\___/_| |_\__,_(_)
                 |/

⁠Building and Testing the Lambda Function

If you would like to builf the lambda function (which will package the function and all its dependencies), run:

$ docker run example-lambda-image lambda build

The result will be a zip file created in the /lambda/dist directory inside the container.

If you would like to build and test the lambda function and gather up the results, you can run:

$ docker run example-lambda-image lambda_build_tar | tar -x -v
build.log
test.log
dist/
dist/2017-09-01-003647-example-lambda.zip

Behind the scenes, what this does is:

• Removes any log and dist files from prior runs
• Executes 'lambda build' and stores the log in /lambda/build.log in the container
• If present and executable, runs /lambda/run_tests and stores the log in /lambda/test.log in the container
• Tars the log files, and the contents of the dist directory in /lambda on the container and pipes it to standard output
• Untars the contents bundled up within the container, and extracts them into your current directory

⁠Deploying the Lambda Function

You can deploy your lambda function to Amazon's infrastructure... you'll need to add AWS credentials into the config.yaml⁠ file. Alternately, if your local AWS CLI environment is working, you can add a .aws/ directory (you can cp ~/.aws) into the example/ directory), then re-build your image. Once AWS is working within your container, you can then run the following to deploy your function to Amazon:

$ docker run example-lambda-image lambda deploy