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$ npm install --save serverless-package-python-functions
# serverless.yml plugins: - serverless-package-python-functions
A Serverless Framework plugin for packaging Python Lambda functions with only the dependencies they need.
This plugin makes it easy to manage function-level and service-level dependencies for your awesome Python Serverless project
Let's consider the following project structure
your-awesome-project/ ├── common_files │ ├── common1.py │ └── common2.py ├── function1 │ ├── lambda.py │ └── requirements.txt # with simplejson library ├── function2 │ ├── lambda.py │ └── requirements.txt ├── requirements.txt # with requests library └── serverless.yml
This project has:
This plugin will package your functions into individual zip files that look like:
├── lambda.py # function-level code ├── requirements.txt ├── common1.py # service-level code ├── common2.py ├── simplejson # function-level dependencies ├── simplejson-3.10.0.dist-info ├── requests # service-level dependencies └── requests-2.13.0.dist-info
So that the below code
import common1, common2, requests, simplejson
in function1/lambda.py works like works like a charm!
The plugin also supports packaging your dependencies using a Docker Image that replicates your cloud providers environment, allowing you easily work with platform-dependent libraries like numpy.
The plugin handles the creation of the artifact zip files for your Serverless functions.
When serverless deploy is run, the plugin will:
The Serverless framework will then pickup each zip file and upload it to your provider.
Here's a simple serverless.yml configuration for this plugin, assuming the project structure above one of the functions we add -${opt:stage} to the name in order to append the stage to the function name
service: your-awesome-project
package:
individually: true
plugins:
- serverless-package-python-functions
custom:
pkgPyFuncs: # plugin configuration
buildDir: _build
requirementsFile: 'requirements.txt'
globalRequirements:
- ./requirements.txt
globalIncludes:
- ./common_files
cleanup: true
functions:
function1:
name: function1-${opt:stage}
handler: lambda.handler
package:
include:
- function1
artifact: ${self:custom.pkgPyFuncs.buildDir}/function1.zip
function2:
name: function2
handler: lambda.handler
package:
include:
- function2
artifact: ${self:custom.pkgPyFuncs.buildDir}/function2.zip
The plugin configurations are simple:
| Configuration | Description | Optional? |
|---|---|---|
| buildDir | Path to a build directory relative to project root, e.g. build | No |
| requirementsFile | The name of the requirements file used for function-level requirements. All function-level requirements files must use the name specified here. | Yes. Defaults to requirements.txt |
| globalRequirements | A list of paths to files containing service-level pip requirements. | Yes |
| globalIncludes | A list of paths to folders containing service-level code files (i.e. code common to all functions). Only the folders contents will be packaged, not the folder itself. Paths to files are not currently supported. | Yes |
| useDocker | Boolean indicating whether to package pip dependencies using Docker. Set this to true if your project uses platform-specific compiled libraries like numpy. Requires a Docker installation. | Yes. Defaults to false |
| dockerImage | The Docker image to use to compile functions if useDocker is set to true. Must be specified as repository:tag. If the image doesn't exist on the system, it will be downloaded. The initial download may take some time. | Yes. Defaults to lambci/lambda:build-${provider.runtime} |
| containerName | The desired name for the Docker container. | Yes. Defaults to serverless-package-python-functions |
| abortOnPackagingErrors | Boolean indicating whether you want to stop deployment when packaging errors are detected. Examples of scenarios that will cause packaging errors include: useDocker is enabled but the Docker service is not running, pip finds dependency mismatches, virtual environment errrors, etc.. When an error is detected, this will prompt via commandline to continue or abort deploy. | Yes. Defaults to false |
At the function level, you:
At the package level, you may need to:
Now, you may be wondering, doesn't the Serverless documentation say:
Serverless won't zip your service if [artifact] is configured and therefore exclude and include will be ignored. Either you use artifact or include / exclude.
Yes, that is correct and is actually awesome! Since Serverless ignores include/exclude silently when artifact is specified, it allows this plugin take advantage of the include property to provide you with a familiar interface for specifying function-level dependencies. So while this plugin uses include to determine what goes in your artifact, all Serverless cares about is the artifact that this plugin creates when it executes.
The last thing that your keen eye may have noticed from the example serverless.yml above is that handler is specified simply as lambda.handler not ${self:custom.pkgPyFuncs.buildDir}/function/lambda.hadler or function/lambda.handler. This is because the plugin zips your artifacts such that /path/to/function is the root of the zip file. Combined with the fact that it uses pip install -t to download pip dependencies directly to the top level of the zip file, this makes imports significantly simpler for your project. Furthermore, since pip install -t downloads the actual pip package files into a folder, this plugin works without the need for virtualenv
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