AWS Lambda

Create a Lambda with Python code.

Pants can create a Lambda-compatible zip file from your Python code, allowing you to develop your Lambdas in your repository instead of using the online Cloud9 editor.


FYI: how Pants does this

Under-the-hood, Pants uses the PEX project, to select the appropriate third-party requirements and first-party sources and lay them out in a zip file, in the format recommended by AWS.

Step 1: Activate the Python AWS Lambda backend

Add this to your pants.toml:

backend_packages.add = [

This adds the new python_awslambda target, which you can confirm by running pants help python_awslambda


Set layout = "zip" for Pants 2.17

Pants 2.17 is transitioning to a new, better layout, but defaults to the old Lambdex layout for backwards compatibility. To silence the warnings and be ready for Pants 2.18, add the following to the end of your pants.toml:

layout = "zip"

If you have existing python_awslambda targets, this will change the handler from lambdex_handler.handler to lambda_function.handler (see below for more details).

Step 2: Define a python_awslambda target

First, add your lambda function in a Python file like you would normally do with AWS Lambda. Specifically, create a function def my_handler_name(event, context) with the name you want.

Then, in your BUILD file, make sure that you have a python_source or python_sources target with the handler file included in the sources field. You can use pants tailor :: to automate this.

Add a python_awslambda target and define the runtime and handler fields. The runtime should be one of the values from https://docs.aws.amazon.com/lambda/latest/dg/lambda-python.html. The handler has the form handler_file.py:handler_func, which Pants will convert into a well-formed entry point. Alternatively, you can set handler to the format path.to.module:handler_func.

For example:

# The default `sources` field will include our handler file.

    # Pants will convert this to `project.lambda_example:example_handler`.
def example_handler(event, context):
    print("Hello AWS!")

Pants will use dependency inference based on the handler field, which you can confirm by running pants dependencies path/to:lambda. You can also manually add to the dependencies field.

You can optionally set the output_path field to change the generated zip file's path.


Use resource instead of file

file / files targets will not be included in the built AWS Lambda because filesystem APIs like open() would not load them as expected. Instead, use the resource and resources target. See Assets and archives for further explanation.

Step 3: Run package

Now run pants package on your python_awslambda target to create a zipped file.

For example:

$ pants package project/:lambda
Wrote dist/project/lambda.zip
  Handler: lambda_function.handler


Running from macOS and failing to build?

AWS Lambdas must run on Linux, so Pants tells PEX and Pip to build for Linux when resolving your third party dependencies. This means that you can only use pre-built wheels (bdists). If your project requires any source distributions (sdists) that must be built locally, PEX and pip will fail to run.

If this happens, you must either change your dependencies to only use dependencies with pre-built wheels or find a Linux environment to run pants package.

Step 4: Upload to AWS

You can use any of the various AWS methods to upload your zip file, such as the AWS console or the AWS CLI via aws lambda create-function and aws lambda update-function-code.

You can specify the AWS lambda handler as lambda_function.handler. This is a re-export of the function referred to by the handler field of the target.

Docker Integration

To deploy a Python lambda function with container images, you can use Pants's Docker support.

For example:

FROM public.ecr.aws/lambda/python:3.8

RUN yum install unzip -y
COPY project/lambda.zip .
RUN unzip lambda.zip -d "${LAMBDA_TASK_ROOT}"
CMD ["lambda_function.handler"]


    dependencies = [":lambda"],

Then, use pants package project:my_image, for example. Pants will first build your AWS Lambda, and then will build the Docker image and copy it into the AWS Lambda.

Advanced: Using PEX directly

In the rare case where you need access to PEX features, such as dynamic selection of dependencies, a PEX file created by pex_binary can be used as a Lambda package directly. A PEX file is a carefully constructed zip file, and can be understood natively by AWS. Note: using pex_binary results in larger packages and slower cold starts and is likely to be less convenient than using python_awslambda.

The handler of a pex_binary is not re-exported at the fixed lambda_function.handler path, and the Lambda handler must be configured as the __pex__ pseudo-package followed by the handler's normal module path (for instance, if the handler is called func in some/module/path.py within a source root, then use __pex__.some.module.path.func). The __pex__ pseudo-package ensures dependencies are initialized before running any of your code.

For example:


    # specify an appropriate platform(s) for the targeted Lambda runtime (complete_platforms works too)
def example_handler(event, context):
    print("Hello AWS!")

Then, use pants package project:lambda, and upload the resulting project/lambdex.pex to AWS. The handler will need to be configured in AWS as __pex__.lambda_example.example_handler (assuming project is a source root).

Migrating from Pants 2.16 and earlier

Pants has implemented a new way to package Lambdas in 2.17, resulting in smaller packages and faster cold starts. This involves some changes:

  • In Pants 2.16 and earlier, Pants used the Lambdex project. First, Pants would convert your code into a Pex file and then use Lambdex to adapt this to be better understood by AWS by adding a shim handler at the path lambdex_handler.handler. This shim handler first triggers the Pex initialization to choose and unzip dependencies, during the "INIT" phase.
  • In Pants 2.17, the use of Lambdex is deprecated, in favour of choosing the appropriate dependencies ahead of time, as described above, without needing to do this on each cold start. This results in a zip file laid out in the format recommended by AWS, and includes a re-export of the handler at the path lambda_function.handler.
  • In Pants 2.18, the new behaviour will become the default behaviour.
  • In Pants 2.19, the old Lambdex behaviour will be entirely removed.

Any existing python_awslambda targets will change how they are built. Migrating has three steps:

  1. opt-in to the new behaviour in Pants 2.17
  2. package the new targets
  3. upload those packages to AWS, and update the configured handler from lambdex_handler.handler (old) to lambda_function.handler (new)

To opt-in to the new behaviour in Pants 2.17, add the following to the end of your pants.toml:

layout = "zip"

To temporarily continue using the old behaviour in Pants 2.17, instead set layout = "lambdex". This will not be supported in Pants 2.19. If you encounter a bug with layout = "zip", please let us know. If you require advanced PEX features, switch to using pex_binary directly.