README.rst

python-lambda-4dn

(python-λ forked for 4DN-DCIC projects)

This is a toolset for developing and deploying serverless Python code in AWS Lambda.

Important

This is a FORK of Nick Ficano's Python-lambda package. It will NOT be updated regularly and is frozen for the needs of projects at the 4D Nucleome Data Coordination and Integration Center (4DN-DCIC).

Description

AWS Lambda is a service that allows you to write Python, Java, or Node.js code that gets executed in response to events like http requests or files uploaded to S3.

Working with Lambda is relatively easy, but the process of bundling and deploying your code is not as simple as it could be.

The Python-Lambda library takes away the guess work of developing your Python-Lambda services by providing you a toolset to streamline the annoying parts.

Important Legal Notice

The original Python-lambda is licensed under an ISC license. The version of that license active at time of the fork is here. Github's summary of that license describes it as:

A permissive license lets people do anything with your code with proper attribution and without warranty. The ISC license is functionally equivalent to the BSD 2-Clause and MIT licenses, removing some language that is no longer necessary.

Since our derivative work is covered under the MIT license, and on a theory that the underlying license is equivalent to the MIT license, we shorthand our licensing requirements as just "MIT" because that's more consistent with how we describe licensing for other 4DN-DCIC software. However, for the properly formal legal detail, please refer to our actual LICENSE.

System Requirements

• Python 3.6
• Pip (Any should work)
• Virtualenv (>=15.0.0)

Setting Up a Virtual Environment (OPTIONAL)

This is optional. If you do not create a virtual environment, Poetry will make one for you. But there are still good reasons you might want to make your own, so here are three ways to do it:

• If you have virtualenvwrapper that knows to use Python 3.6:

  mkvirtualenv myenv
  

• If you have virtualenv but not virtualenvwrapper, and you have python3.6 in your PATH:

  virtualenv myenv -p python3.6
  

• If you are using pyenv to control what environment you use:

  pyenv exec python -m venv myenv
  

Installing Poetry in a Virtual Environment

Once you have created a virtual environment, or have decided to just let Poetry handle that, install with poetry:

poetry install

Getting Started

Using this library is intended to be as straightforward as possible. Code for a very simple lambda used in the tests is reproduced below.

config = {
    'function_name': 'my_test_function',
    'function_module': 'service',
    'function_handler': 'handler',
    'handler': 'service.handler',
    'region': 'us-east-1',
    'runtime': 'python3.6',
    'role': 'helloworld',
    'description': 'Test lambda'
}

def handler(event, context):
    return 'Hello! My input event is %s' % event

This code illustrates the two things required to create a lambda. The first is config, which specifies metadata for AWS. One important thing to note in here is the role field. This must be a IAM role with Lambda permissions - the one in this example is ours. The second is the handler function. This is the actual code that is executed.

Given this code in example_function.py you would deploy this function like so:

from aws_lambda import deploy_function
import example_function
deploy_function(example_function,
                function_name_suffix='<suffix>',
                package_objects=['list', 'of', 'local', 'modules'],
                requirements_fpath='path/to/requirements',
                extra_config={'optional_arguments_for': 'boto3'})

And that's it! You've deployed a simple lambda function. You can navigate to the AWS console to create a test event to trigger it or you can invoke it directly using Boto3.

Advanced Usage

Many of the options specified in the above code block when it came to actually deploying the function are not used. These become more useful as you want to make more complicated lambda functions. The ideal way to incorporate dependencies into lambda functions is by providing a requirements.txt file. We rely on pip to install these packages and have found it to be very reliable. While it is also possible to specify local modules as well through package_objects, doing so is not recommended because those modules must be specified at the top level of the repository in order to work out of the box. There is a comment on this topic in example_function_package.py with code on how to handle it.

Tests

Tests can be found in the test_aws_lambda.py. Using the tests as a guide to develop your lambdas is probably a good idea. You can also see how to invoke the lambdas directly from Python (and interpret the response). You can invoke all of this by just doing:

pytest

The usual pytest arguments are permited. For example, to invoke an individual test, mention its name. To see verbose output, use -v; or use -vv for extra-verbose output, as in:

pytest -vv -k test_deploy_lambda_with_package_and_requirements