A Serverless v1.x plugin to automatically bundle dependencies from requirements.txt and make them available in your PYTHONPATH.

Requires Serverless >= v1.12

sls plugin install -n serverless-python-requirements

🍎🍺🐍 Mac Brew installed Python notes

Compiling non-pure-Python modules or fetching their manylinux wheels is supported on non-linux OSs via the use of Docker and the docker-lambda image. To enable docker usage, add the following to your serverless.yml:

custom:
  pythonRequirements:
    dockerizePip: true

The dockerizePip option supports a special case in addition to booleans of 'non-linux' which makes it dockerize only on non-linux environments.

To utilize your own Docker container instead of the default, add the following to your serverless.yml:

custom:
  pythonRequirements:
    dockerImage: <image name>:tag

This must be the full image name and tag to use, including the runtime specific tag if applicable.

Alternatively, you can define your Docker image in your own Dockerfile and add the following to your serverless.yml:

custom:
  pythonRequirements:
    dockerFile: ./path/to/Dockerfile

With Dockerfile the path to the Dockerfile that must be in the current folder (or a subfolder). Please note the dockerImage and the dockerFile are mutually exclusive.

To install requirements from private git repositories, add the following to your serverless.yml:

custom:
  pythonRequirements:
    dockerizePip: true
    dockerSsh: true

The dockerSsh option will mount your $HOME/.ssh/id_rsa and $HOME/.ssh/known_hosts as a volume in the docker container. If your SSH key is password protected, you can use ssh-agent because $SSH_AUTH_SOCK is also mounted & the env var set. It is important that the host of your private repositories has already been added in your $HOME/.ssh/known_hosts file, as the install process will fail otherwise due to host authenticity failure.

🏁 Windows notes

If you include a Pipfile and have pipenv installed instead of a requirements.txt this will use pipenv lock -r to generate them. It is fully compatible with all options such as zip and dockerizePip. If you don't want this plugin to generate it for you, set the following option:

custom:
  pythonRequirements:
    usePipenv: false

To help deal with potentially large dependencies (for example: numpy, scipy and scikit-learn) there is support for compressing the libraries. This does require a minor change to your code to decompress them. To enable this add the following to your serverless.yml:

custom:
  pythonRequirements:
    zip: true

and add this to your handler module before any code that imports your deps:

try:
  import unzip_requirements
except ImportError:
  pass

Works on non 'win32' environments: Docker, WSL are included
To remove the tests, information and caches from the installed packages, enable the slim option. This will: strip the .so files, remove __pycache__ directories and dist-info directories.

custom:
  pythonRequirements:
    slim: true

To specify additional directories to remove from the installed packages, define the patterns using regex as a slimPatterns option in serverless config:

custom:
  pythonRequirements:
    slim: true
    slimPatterns:
      - "*.egg-info*"

This will remove all folders within the installed requirements that match the names in slimPatterns

You can omit a package from deployment with the noDeploy option. Note that dependencies of omitted packages must explicitly be omitted too. By default, this will not install the AWS SDKs that are already installed on Lambda. This example makes it instead omit pytest:

custom:
  pythonRequirements:
    noDeploy:
      - pytest

You can specify extra arguments to be passed to pip like this:

custom:
  pythonRequirements:
      dockerizePip: true
      pipCmdExtraArgs:
          - --cache-dir
          - .requirements-cache

When using --cache-dir don't forget to also exclude it from the package.

package:
  exclude:
    - .requirements-cache/**

Some pip workflows involve using requirements files not named requirements.txt. To support these, this plugin has the following option:

custom:
  pythonRequirements:
    fileName: requirements-prod.txt

If you have different python functions, with different sets of requirements, you can avoid including all the unecessary dependencies of your functions by using the following structure:

├── serverless.yml
├── function1
│      ├── requirements.txt
│      └── index.py
└── function2
       ├── requirements.txt
       └── index.py

With the content of your serverless.yml containing:

package:
  individually: true

functions:
  func1:
    handler: index.handler
    module: function1
  func2:
    handler: index.handler
    module: function2

The result is 2 zip archives, with only the requirements for function1 in the first one, and only the requirements for function2 in the second one.

Quick notes on the config file:

• The module field must be used to tell the plugin where to find the requirements.txt file for each function.
• The handler field must not be prefixed by the folder name (already known through module) as the root of the zip artifact is already the path to your function.

Sometimes your Python executable isn't available on your $PATH as python2.7 or python3.6 (for example, windows or using pyenv). To support this, this plugin has the following option:

custom:
  pythonRequirements:
    pythonBin: /opt/python3.6/bin/python

For certain libraries, default packaging produces too large an installation, even when zipping. In those cases it may be necessary to tailor make a version of the module. In that case you can store them in a directory and use the vendor option, and the plugin will copy them along with all the other dependencies to install:

custom:
  pythonRequirements:
    vendor: ./vendored-libraries
functions:
  hello:
    handler: hello.handler
    vendor: ./hello-vendor # The option is also available at the function level

The .requirements and requirements.zip(if using zip support) files are left behind to speed things up on subsequent deploys. To clean them up, run sls requirements clean. You can also create them (and unzip_requirements if using zip support) manually with sls requirements install.

If you are using your own Python library, you have to cleanup .requirements on any update. You can use the following option to cleanup .requirements everytime you package.

custom:
  pythonRequirements:
    invalidateCaches: true

Brew wilfully breaks the --target option with no seeming intention to fix it which causes issues since this uses that option. There are a few easy workarounds for this:

• Install Python from python.org and specify it with the pythonBin option.

OR

• Create a virtualenv and activate it while using serverless.

OR

• Install Docker and use the dockerizePip option.

Also, brew seems to cause issues with pipenv, so make sure you install pipenv using pip.

For usage of dockerizePip on Windows do Step 1 only if running serverless on windows, or do both Step 1 & 2 if running serverless inside WSL.

1. Enabling shared volume in Windows Docker Taskbar settings
2. Installing the Docker client on Windows Subsystem for Linux (Ubuntu)

Some Python packages require extra OS dependencies to build successfully. To deal with this, replace the default image (lambci/lambda:python3.6) with a Dockerfile like:

# AWS Lambda execution environment is based on Amazon Linux 1
FROM amazonlinux:1

# Install Python 3.6
RUN yum -y install python36 python36-pip

# Install your dependencies
RUN curl -s https://bootstrap.pypa.io/get-pip.py | python3
RUN yum -y install python3-devel mysql-devel gcc

# Set the same WORKDIR as default image
RUN mkdir /var/task
WORKDIR /var/task

Then update your serverless.yml:

custom:
  pythonRequirements:
    dockerFile: Dockerfile

Some Python packages require extra OS libraries (*.so files) at runtime. You need to manually include these files in the root directory of your Serverless package. The simplest way to do this is to commit the files to your repository:

For instance, the mysqlclient package requires libmysqlclient.so.1020. If you use the Dockerfile from the previous section, you can extract this file from the builder Dockerfile:

1. Extract the library:

docker run --rm -v "$(pwd):/var/task" sls-py-reqs-custom cp -v /usr/lib64/mysql57/libmysqlclient.so.1020 .

(If you get the error Unable to find image 'sls-py-reqs-custom:latest' locally, run sls package to build the image.) 2. Commit to your repo:

git add libmysqlclient.so.1020
git commit -m "Add libmysqlclient.so.1020"

3. Verify the library gets included in your package:

sls package
zipinfo .serverless/xxx.zip

(If you can't see the library, you might need to adjust your package include/exclude configuration in serverless.yml.)

• @dschep - Lead developer & maintainer
• @azurelogic - logging & documentation fixes
• @abetomo - style & linting
• @angstwad - deploy --function support
• @mather - the cache invalidation option
• @rmax - the extra pip args option
• @bsamuel-ui - Python 3 support
• @suxor42 - fixing permission issues with Docker on Linux
• @mbeltran213 - fixing docker linux -u option bug
• @Tethik - adding usePipenv option
• @miketheman - fixing bug with includes when using zip option
• @wattdave - fixing bug when using deploymentBucket
• @heri16 - fixing Docker support in Windows
• @ryansb - package individually support
• @cgrimal - Private SSH Repo access in Docker, dockerFile option to build a custom docker image, real per-function requirements, and the vendor option
• @kichik - Imposed windows & noDeploy support, switched to adding files straight to zip instead of creating symlinks, and improved pip chache support when using docker.
• @dee-me-tree-or-love - the slim package option
• @alexjurkiewicz - docs about docker workflows