drover

drover: a command-line utility to deploy Python packages to AWS Lambda functions

Background

This utility aims to provide a simple, repeatable, and efficient process for deploying a Python package as a Lambda.

To encourage separating infrequently changing Python dependencies in a separate "requirements" layer, by default drover requires a list of regular expressions to define which files to include in the Lambda function; all other files are placed in a requirements layer that is then attached to the Lambda function.

Next, drover generates and stores hashes for both the Lambda function and the requirements layer. This allows drover to avoid redundantly updating the Lambda function and/or requirements layer if no package contents have changed.

As much as possible, drover avoids altering existing infrastructure. Infrastructure utilities such as Terraform may be used to create a Lambda and manage its surrounding resources and drover may be used to update the Lambda function as well as its layers.

Supported Platforms

This utility is continuously unit tested on a GNU/Linux system with Python 3.6, 3.7, and 3.8.

Usage

Settings

The following drover.yml settings file demonstrates how to configure a staging stage that may be used to deploy a Python package to a Lambda named basic-lambda in the us-east-1 region:

stages:
  staging:
    region_name: us-east-1
    function_name: basic-lambda
    compatible_runtime: python3.8
    function_file_patterns:
      - '^basic_lambda.*'
    function_extra_paths:
      - instance
    upload_bucket:
      region_name: us-east-1
      bucket_name: drover-examples

The compatible_runtime value will be used to define the compatible runtime for both the requirements layer (if present) and the Lambda function.

While processing files from the install path (see: --install-path below), any files matching regular expressions defined in the function_file_patterns list will be included in the function; any remaining files will be included in the requirements layer.

The function_extra_paths list may contain additional paths to include in the function layer archive; non-absolute paths will be relative to the current working directory.

The upload_bucket map may provide a S3 Bucket name and its associated region for use when uploading Lambda function and layer archive files.

Command line interface

Assuming a Python package exists in the basic_lambda directory, the following commands demonstrate a simple Lambda deploy with drover:

pip install --target install basic_lambda
drover --install-path install staging

Assuming the Lambda is not already up to date, drover will attempt to upload the latest source and update the Lambda function:

Requirements digest: None
Function digest: 0b37cf78f6ad4c137fb1f77751c0c0e759dd2d6c515937d33fae435b9e091f72
Skipping requirements upload
Uploading function archive...
Failed to upload function archive to bucket; falling back to direct file upload.
Updating function resource...
Updated function "basic-lambda" resource; size: 1.78 KiB; ARN: arn:aws:lambda:us-east-1:977874552542:function:basic-lambda

Additional examples

For more examples, see the examples directory.

How to contribute

Contributions are welcome in the form of inquiries, issues, and pull requests.

Development Environment

Initialize a development environment by executing nox -s dev-3.8; the drover utility will be installed in the .nox/dev-3-8 Python virtual environment binary path.