a command-line utility to deploy Python packages to Lambda functions
Project description
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.
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