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The Python images based on Wolfi and maintained by Chainguard provide distroless images that are suitable for building and running Python workloads.
Chainguard offers both a minimal runtime image containing just Python, and a development image that contains a package manager and a shell. Because Python applications typically require the installation of third-party dependencies via the Python package installer pip, you may need to implement a multi-stage Docker build that uses the Python -dev image to set up the application.
-dev
In this guide, we’ll cover two examples to showcase Python container images based on Wolfi as a runtime. In the first, we’ll use the minimal image containing just Python (which has access to the Python standard library), and in the second we’ll demonstrate a multi-stage build.
In this example, we’ll build and run a distroless Python Chainguard Image in a single-stage build process. We’ll first make a demonstration app and then build and run it.
We’ll start by creating a basic command-line Python application to serve as a demo. This app will generate random octopus facts based on a list in a text file. This app will use the random module from the Python standard library.
random
First, create a directory for your app. You can use any meaningful name and path for you, our example will use octo-facts/.
octo-facts/
mkdir ~/octo-facts/ && cd $_
Create a new file to serve as the application entry point. We’ll use main.py. You can edit this file in whatever code editor you would like. We’ll use Nano as an example.
main.py
nano main.py
The following Python script defines a light CLI app that takes in a text file, octo-facts.txt, and returns a random line from that file.
octo-facts.txt
'''Import random module to implement random.choice() function''' import random def random_line(text): '''Opens and reads lines of a UTF-8 encoded file, returning a random line''' with open(text, 'r', encoding='UTF-8') as file: line = file.readlines() return random.choice(line) def main(): '''Prints random line from facts.txt; verify your path''' print(random_line('facts.txt')) if __name__ == "__main__": main()
Copy this code to your main.py script, save and close the file.
Next, pull down the facts.txt file with curl. Inspect the URL before downloading it to ensure it is safe to do so. Make sure you are still in the same directory where your main.py script is.
facts.txt
curl
curl -O https://raw.githubusercontent.com/chainguard-dev/edu-images-demos/main/python/octo-facts/facts.txt
At this point, you can run the script and be sure you are satisfied with the functionality. It is recommended that you use a Python programming environment. Ensure whether you will be using the python or python3 command.
python
python3
python main.py
You should receive the output of a randomized octopus fact.
The wolfi octopus was discovered in 1913.
The demo application is now ready. In the next step, you’ll create a Dockerfile to run your app.
For this single-stage build, we’ll only use one FROM line in our Dockerfile. Our resulting image will be based on the distroless Python Wolfi image, which means it doesn’t come with a package manager or even a shell.
FROM
We’ll begin by creating a Dockerfile. Again, you can use any code editor of your choice, we’ll use Nano for demonstation purposes.
nano Dockerfile
The following Dockerfile will:
python:latest
FROM cgr.dev/chainguard/python:latest WORKDIR /octo-facts COPY main.py facts.txt ./ ENTRYPOINT [ "python", "/octo-facts/main.py" ]
Save the file when you’re finished.
You can now build the image. If you receive an error, try again with sudo.
sudo
docker build . -t octo-facts
Once the build is finished, run the image.
docker run --rm octo-facts
And you should get output similar to what you got before, with a random octopus fact.
Octopuses can breathe and see through their skin.
You have successfully completed the single-stage Python Chainguard Image. At this point, you can continue to the multi-stage example or advanced usage.
In this example, we’ll build and run a multi-stage Python Chainguard Image to demonstrate the process that includes a build image with pip and a shell, and a final distroless image.
We’ll start by creating a Python application that will take in an image file and convert it to ANSI escape sequences on the CLI to render an image.
To begin, create a directory for your app. You can use any meaningful name and path that resonates with you, our example will use inky/.
inky/
mkdir ~/inky/ && cd $_
We’ll first write out the requirements for our app in the requirements.txt file. We’ll download the most recent version of Python setuptools at the time of writing, and also install climage.
requirements.txt
setuptools==67.4.0 climage==0.1.3
With requirements declared, create a new file to serve as the application entry point. We’ll use inky.py. You can edit this file in whatever code editor you would like. We’ll use Nano as an example.
inky.py
nano inky.py
The following Python script defines a CLI app that takes in an image file, chainguard.png, and prints a representation of that file on the command line.
chainguard.png
'''import climage module to display images on terminal''' import climage def main(): '''Take in PNG and output as ANSI to terminal''' output = climage.convert('chainguard.png', is_unicode=True) print(output) if __name__ == "__main__": main()
You can now install the dependencies with pip and run the above program. It is recommended that you use a Python programming environment, ensure whether you are using the pip or pip3 command.
pip
pip3
pip install -r requirements.txt
Now you can run the program. Ensure whether you’re using the python or python3 command.
python inky.py
You’ll receive a representation of the Chainguard Inky logo on the command line. With your demo application ready, you’re ready to move onto the container stage.
To make sure our final image is distroless while still being able to install dependencies with pip, our build will consist of two stages: first, we’ll build the application using the dev image variant, a Wolfi-based image that includes pip and other useful tools for development. Then, we’ll create a separate stage for the final image. The resulting image will be based on the distroless Python Wolfi image, which means it doesn’t come with pip or even a shell.
Begin by editing a Dockerfile, with Nano for instance.
python:latest-dev
builder
/inky
Copy this configuration to your own Dockerfile:
FROM cgr.dev/chainguard/python:latest-dev as builder WORKDIR /inky COPY requirements.txt . RUN pip install -r requirements.txt --user FROM cgr.dev/chainguard/python:latest WORKDIR /inky # Make sure you update Python version in path COPY --from=builder /home/nonroot/.local/lib/python3.11/site-packages /home/nonroot/.local/lib/python3.11/site-packages COPY inky.py inky.png ./ ENTRYPOINT [ "python", "/inky/inky.py" ]
You can now build the image. If you receive a permission error, try running under sudo.
docker build . -t inky
Once the build is finished, run the image with:
docker run --rm inky
And you should get output similar to what you got before, with a printed Inky on the command line.
If your project requires a more specific set of packages that aren't included within the general-purpose Python Chainguard Image, you'll first need to check if the package you want is already available on the wolfi-os repository.
If the package is available, you can use the wolfi-base image in a Dockerfile and install what you need with apk, then use the resulting image as base for your app. Check the "Using the wolfi-base Image" section of our images quickstart guide for more information.
apk
If the packages you need are not available, you can build your own apks using melange. Please refer to this guide for more information.