Amazon base images for Python Using an Amazon base image Using a non-Amazon base image

Deploy Python Lambda functions with container images

There are three ways to build a container image for a Python Lambda function:

Using an Amazon base image for Python

The Amazon base images are preloaded with a language runtime, a runtime interface client to manage the interaction between Lambda and your function code, and a runtime interface emulator for local testing.
Using an Amazon base image for custom runtimes

Amazon provides base images that contain the Amazon Linux or Amazon Linux 2 operating system and the runtime interface emulator. You can add your preferred runtime, dependencies, and code to these images. To make the image compatible with Lambda, you must include the runtime interface client for Python in the image.
Using a non-Amazon base image

You can use an alternative base image from another container registry, such as Alpine Linux or Debian. You can also use a custom image created by your organization. To make the image compatible with Lambda, you must include the runtime interface client for Python in the image.

Tip

To reduce the time it takes for Lambda container functions to become active, see Use multi-stage builds in the Docker documentation. To build efficient container images, follow the Best practices for writing Dockerfiles.

This page explains how to build, test, and deploy container images for Lambda.

Topics

Amazon base images for Python
Using an Amazon base image for Python
Using an alternative base image with the runtime interface client

Amazon base images for Python

Amazon provides the following base images for Python:

Tags	Runtime	Operating system	Dockerfile	Deprecation
3.11	Python 3.11	Amazon Linux 2	Dockerfile for Python 3.11 on GitHub
3.10	Python 3.10	Amazon Linux 2	Dockerfile for Python 3.10 on GitHub
3.9	Python 3.9	Amazon Linux 2	Dockerfile for Python 3.9 on GitHub
3.8	Python 3.8	Amazon Linux 2	Dockerfile for Python 3.8 on GitHub
3.7	Python 3.7	Amazon Linux	Dockerfile for Python 3.7 on GitHub	Nov 27, 2023

Amazon ECR repository: gallery.ecr.aws/lambda/python

Dependency search path in the base images

When you use an import statement in your code, the Python runtime searches the directories in its search path until it finds the module or package. By default, the runtime searches the {LAMBDA_TASK_ROOT} directory first. If you include a version of a runtime-included library in your image, your version will take precedence over the version that's included in the runtime.

Other steps in the search path depend on which version of the Lambda base image for Python you're using:

Python 3.11: Runtime-included libraries and pip-installed libraries are installed in the /var/lang/lib/python3.11/site-packages directory. This directory has precedence over /var/runtime in the search path. You can override the SDK by using pip to install a newer version. You can use pip to verify that the runtime-included SDK and its dependencies are compatible with any packages that you install.
Python 3.7-3.10: Runtime-included libraries are installed in the /var/runtime directory. Pip-installed libraries are installed in the /var/lang/lib/python3.x/site-packages directory. The /var/runtime directory has precedence over /var/lang/lib/python3.x/site-packages in the search path.

You can see the full search path for your Lambda function by adding the following code snippet.


import sys
      
search_path = sys.path
print(search_path)

Using an Amazon base image for Python

To complete the steps in this section, you must have the following:

To create a container image from an Amazon base image for Python

Create a directory for the project, and then switch to that directory.
```
mkdir example
cd example
```
Create a new file called lambda_function.py. You can add the following sample function code to the file for testing, or use your own.
Example Python function
```
import sys
def handler(event, context):
    return 'Hello from Amazon Lambda using Python' + sys.version + '!'
```
Create a new file called requirements.txt. If you're using the sample function code from the previous step, you can leave the file empty because there are no dependencies. Otherwise, list each required library. For example, here's what your requirements.txt should look like if your function uses the Amazon SDK for Python (Boto3):
Example requirements.txt
```
boto3
```

Create a new Dockerfile with the following configuration:

Set the FROM property to the URI of the base image.
Use the COPY command to copy the function code and runtime dependencies to {LAMBDA_TASK_ROOT}.
Set the CMD argument to the Lambda function handler.

Example Dockerfile


FROM public.ecr.aws/lambda/python:3.11

# Copy requirements.txt
COPY requirements.txt ${LAMBDA_TASK_ROOT}

# Copy function code
COPY lambda_function.py ${LAMBDA_TASK_ROOT}

# Install the specified packages
RUN pip install -r requirements.txt

# Set the CMD to your handler (could also be done as a parameter override outside of the Dockerfile)
CMD [ "lambda_function.handler" ]

Build the Docker image with the docker build command. The following example names the image docker-image and gives it the test tag.
```
docker build --platform linux/amd64 -t docker-image:test .
```
Note
The command specifies the --platform linux/amd64 option to ensure that your container is compatible with the Lambda execution environment regardless of the architecture of your build machine. If you intend to create a Lambda function using the ARM64 instruction set architecture, be sure to change the command to use the --platform linux/arm64 option instead.

Start the Docker image with the docker run command. In this example, docker-image is the image name and test is the tag.
```
docker run -p 9000:8080 docker-image:test
```
This command runs the image as a container and creates a local endpoint at localhost:9000/2015-03-31/functions/function/invocations.
From a new terminal window, post an event to the following endpoint using a curl command:
```
curl "http://localhost:9000/2015-03-31/functions/function/invocations" -d '{}'
```
This command invokes the function with an empty event and returns a response. If you're using your own function code rather than the sample function code, you might want to invoke the function with a JSON payload. Example:
```
curl "http://localhost:9000/2015-03-31/functions/function/invocations" -d '{"payload":"hello world!"}'
```
Get the container ID.
```
docker ps
```
Use the docker kill command to stop the container. In this command, replace 3766c4ab331c with the container ID from the previous step.
```
docker kill 3766c4ab331c
```

To upload the image to Amazon ECR and create the Lambda function

Run the get-login-password command to authenticate the Docker CLI to your Amazon ECR registry.
- Set the --region value to the Amazon Web Services Region where you want to create the Amazon ECR repository.
- Replace 111122223333 with your Amazon Web Services account ID.
```
aws ecr get-login-password --region cn-north-1 | docker login --username AWS --password-stdin 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn
```

Create a repository in Amazon ECR using the create-repository command.


aws ecr create-repository --repository-name hello-world --image-scanning-configuration scanOnPush=true --image-tag-mutability MUTABLE

If successful, you see a response like this:


{
    "repository": {
        "repositoryArn": "arn:aws:ecr:cn-north-1:111122223333:repository/hello-world",
        "registryId": "111122223333",
        "repositoryName": "hello-world",
        "repositoryUri": "111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world",
        "createdAt": "2023-03-09T10:39:01+00:00",
        "imageTagMutability": "MUTABLE",
        "imageScanningConfiguration": {
            "scanOnPush": true
        },
        "encryptionConfiguration": {
            "encryptionType": "AES256"
        }
    }
}

Copy the repositoryUri from the output in the previous step.
Run the docker tag command to tag your local image into your Amazon ECR repository as the latest version. In this command:
- Replace docker-image:test with the name and tag of your Docker image.
- Replace <ECRrepositoryUri> with the repositoryUri that you copied. Make sure to include :latest at the end of the URI.
```
docker tag docker-image:test <ECRrepositoryUri>:latest
```
Example:
```
docker tag docker-image:test 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest
```
Run the docker push command to deploy your local image to the Amazon ECR repository. Make sure to include :latest at the end of the repository URI.
```
docker push 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest
```
Create an execution role for the function, if you don't already have one. You need the Amazon Resource Name (ARN) of the role in the next step.

Create the Lambda function. For ImageUri, specify the repository URI from earlier. Make sure to include :latest at the end of the URI.


aws lambda create-function \
  --function-name hello-world \
  --package-type Image \
  --code ImageUri=111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest \
  --role arn:aws:iam::111122223333:role/lambda-ex

Invoke the function.


aws lambda invoke --function-name hello-world response.json

You should see a response like this:


{
  "ExecutedVersion": "$LATEST", 
  "StatusCode": 200
}

To see the output of the function, check the response.json file.

To update the function code, you must build the image again, upload the new image to the Amazon ECR repository, and then use the update-function-code command to deploy the image to the Lambda function.

Using an alternative base image with the runtime interface client

If you use a base image for custom runtimes or an alternative base image, you must include the runtime interface client in your image. The runtime interface client extends the Lambda runtime API, which manages the interaction between Lambda and your function code.

Install the the runtime interface client for Python using the pip package manager:


pip install awslambdaric

You can also download the Python runtime interface client from GitHub.

The following example demonstrates how to build a container image for Python using a non-Amazon base image. The example Dockerfile uses an official Python base image. The Dockerfile includes the runtime interface client for Python.

To complete the steps in this section, you must have the following:

To create a container image from a non-Amazon base image

Create a directory for the project, and then switch to that directory.
```
mkdir example
cd example
```
Create a new file called lambda_function.py. You can add the following sample function code to the file for testing, or use your own.
Example Python function
```
import sys
def handler(event, context):
    return 'Hello from Amazon Lambda using Python' + sys.version + '!'
```
Create a new file called requirements.txt. If you're using the sample function code from the previous step, you can leave the file empty because there are no dependencies. Otherwise, list each required library. For example, here's what your requirements.txt should look like if your function uses the Amazon SDK for Python (Boto3):
Example requirements.txt
```
boto3
```

Create a new Dockerfile. The following Dockerfile uses an official Python base image instead of an Amazon base image. The Dockerfile includes the runtime interface client, which makes the image compatible with Lambda. The following example Dockerfile uses a multi-stage build.

Set the FROM property to the base image.
Set the ENTRYPOINT to the module that you want the Docker container to run when it starts. In this case, the module is the runtime interface client.
Set the CMD to the Lambda function handler.

Example Dockerfile


# Define custom function directory
ARG FUNCTION_DIR="/function"

FROM python:3.11 as build-image

# Include global arg in this stage of the build
ARG FUNCTION_DIR

# Copy function code
RUN mkdir -p ${FUNCTION_DIR}
COPY . ${FUNCTION_DIR}

# Install the function's dependencies
RUN pip install \
    --target ${FUNCTION_DIR} \
        awslambdaric

# Use a slim version of the base Python image to reduce the final image size
FROM python:3.11-slim

# Include global arg in this stage of the build
ARG FUNCTION_DIR
# Set working directory to function root directory
WORKDIR ${FUNCTION_DIR}

# Copy in the built dependencies
COPY --from=build-image ${FUNCTION_DIR} ${FUNCTION_DIR}

# Set runtime interface client as default command for the container runtime
ENTRYPOINT [ "/usr/local/bin/python", "-m", "awslambdaric" ]
# Pass the name of the function handler as an argument to the runtime
CMD [ "lambda_function.handler" ]

Build the Docker image with the docker build command. The following example names the image docker-image and gives it the test tag.
```
docker build --platform linux/amd64 -t docker-image:test .
```
Note
The command specifies the --platform linux/amd64 option to ensure that your container is compatible with the Lambda execution environment regardless of the architecture of your build machine. If you intend to create a Lambda function using the ARM64 instruction set architecture, be sure to change the command to use the --platform linux/arm64 option instead.

Use the runtime interface emulator to locally test the image. You can build the emulator into your image or install it on your local machine.

To install and run the runtime interface emulator on your local machine

From your project directory, run the following command to download the runtime interface emulator (x86-64 architecture) from GitHub and install it on your local machine.


mkdir -p ~/.aws-lambda-rie && \
    curl -Lo ~/.aws-lambda-rie/aws-lambda-rie https://github.com/aws/aws-lambda-runtime-interface-emulator/releases/latest/download/aws-lambda-rie && \
    chmod +x ~/.aws-lambda-rie/aws-lambda-rie

To install the arm64 emulator, replace the GitHub repository URL in the previous command with the following:


https://github.com/aws/aws-lambda-runtime-interface-emulator/releases/latest/download/aws-lambda-rie-arm64

Start the Docker image with the docker run command. Note the following:
- docker-image is the image name and test is the tag.
- /usr/local/bin/python -m awslambdaric lambda_function.handler is the ENTRYPOINT followed by the CMD from your Dockerfile.
```
docker run -d -v ~/.aws-lambda-rie:/aws-lambda -p 9000:8080 \
    --entrypoint /aws-lambda/aws-lambda-rie \
    docker-image:test \
        /usr/local/bin/python -m awslambdaric lambda_function.handler
```
This command runs the image as a container and creates a local endpoint at localhost:9000/2015-03-31/functions/function/invocations.
Post an event to the following endpoint using a curl command:
```
curl "http://localhost:9000/2015-03-31/functions/function/invocations" -d '{}'
```
This command invokes the function with an empty event and returns a response. Some functions might require a JSON payload. Example:
```
curl "http://localhost:9000/2015-03-31/functions/function/invocations" -d '{"payload":"hello world!"}'
```
Get the container ID.
```
docker ps
```
Use the docker kill command to stop the container. In this command, replace 3766c4ab331c with the container ID from the previous step.
```
docker kill 3766c4ab331c
```

To upload the image to Amazon ECR and create the Lambda function

Run the get-login-password command to authenticate the Docker CLI to your Amazon ECR registry.
- Set the --region value to the Amazon Web Services Region where you want to create the Amazon ECR repository.
- Replace 111122223333 with your Amazon Web Services account ID.
```
aws ecr get-login-password --region cn-north-1 | docker login --username AWS --password-stdin 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn
```

Create a repository in Amazon ECR using the create-repository command.


aws ecr create-repository --repository-name hello-world --image-scanning-configuration scanOnPush=true --image-tag-mutability MUTABLE

If successful, you see a response like this:


{
    "repository": {
        "repositoryArn": "arn:aws:ecr:cn-north-1:111122223333:repository/hello-world",
        "registryId": "111122223333",
        "repositoryName": "hello-world",
        "repositoryUri": "111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world",
        "createdAt": "2023-03-09T10:39:01+00:00",
        "imageTagMutability": "MUTABLE",
        "imageScanningConfiguration": {
            "scanOnPush": true
        },
        "encryptionConfiguration": {
            "encryptionType": "AES256"
        }
    }
}

Copy the repositoryUri from the output in the previous step.
Run the docker tag command to tag your local image into your Amazon ECR repository as the latest version. In this command:
- Replace docker-image:test with the name and tag of your Docker image.
- Replace <ECRrepositoryUri> with the repositoryUri that you copied. Make sure to include :latest at the end of the URI.
```
docker tag docker-image:test <ECRrepositoryUri>:latest
```
Example:
```
docker tag docker-image:test 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest
```
Run the docker push command to deploy your local image to the Amazon ECR repository. Make sure to include :latest at the end of the repository URI.
```
docker push 111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest
```
Create an execution role for the function, if you don't already have one. You need the Amazon Resource Name (ARN) of the role in the next step.

Create the Lambda function. For ImageUri, specify the repository URI from earlier. Make sure to include :latest at the end of the URI.


aws lambda create-function \
  --function-name hello-world \
  --package-type Image \
  --code ImageUri=111122223333.dkr.ecr.cn-north-1.amazonaws.com.cn/hello-world:latest \
  --role arn:aws:iam::111122223333:role/lambda-ex

Invoke the function.


aws lambda invoke --function-name hello-world response.json

You should see a response like this:


{
  "ExecutedVersion": "$LATEST", 
  "StatusCode": 200
}

To see the output of the function, check the response.json file.

For an example of how to create a Python image from an Alpine base image, see Container image support for Lambda on the Amazon Blog.

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Deploy .zip file archives

Context

Deploy Python Lambda functions with container images

Tip

Topics

Amazon base images for Python

Dependency search path in the base images

Using an Amazon base image for Python

To create a container image from an Amazon base image for Python

Example Python function

Example requirements.txt

Example Dockerfile

Note

To upload the image to Amazon ECR and create the Lambda function

Using an alternative base image with the runtime interface client

To create a container image from a non-Amazon base image

Example Python function

Example requirements.txt

Example Dockerfile

Note

To install and run the runtime interface emulator on your local machine

To upload the image to Amazon ECR and create the Lambda function