Python docker images
A simple way to build a Python project ======================================
This repository provides and demonstrates a way to pack python package into a compact Docker image, based on modern Ubuntu Jammy operation system.
Awailable images
This project is available both in the official docker repository and also on the Github Container Registry (ghcr.io).
ghcr.io | docker.io ------- | --------- ghcr.io/snakepacker/python/all | snakepacker/python:all ghcr.io/snakepacker/python/all-pillow | snakepacker/python:all-pillow ghcr.io/snakepacker/python/3.13 | snakepacker/python:3.13 ghcr.io/snakepacker/python/3.13-pillow | snakepacker/python:3.13-pillow ghcr.io/snakepacker/python/3.12 | snakepacker/python:3.12 ghcr.io/snakepacker/python/3.12-pillow | snakepacker/python:3.12-pillow ghcr.io/snakepacker/python/3.11 | snakepacker/python:3.11 ghcr.io/snakepacker/python/3.11-pillow | snakepacker/python:3.11-pillow ghcr.io/snakepacker/python/3.10 | snakepacker/python:3.10 ghcr.io/snakepacker/python/3.10-pillow | snakepacker/python:3.10-pillow ghcr.io/snakepacker/python/3.9 | snakepacker/python:3.9 ghcr.io/snakepacker/python/3.9-pillow | snakepacker/python:3.9-pillow ghcr.io/snakepacker/python/3.8 | snakepacker/python:3.8 ghcr.io/snakepacker/python/3.8-pillow | snakepacker/python:3.8-pillow ghcr.io/snakepacker/python/pylama | snakepacker/python:pylama ghcr.io/snakepacker/python/pylava | snakepacker/python:pylava ghcr.io/snakepacker/python/ipython | snakepacker/python:ipython ghcr.io/snakepacker/python/certbot | snakepacker/python:certbot ghcr.io/snakepacker/python/black | snakepacker/python:black ghcr.io/snakepacker/python/gray | snakepacker/python:gray ghcr.io/snakepacker/python/ruff | snakepacker/python:ruff ghcr.io/snakepacker/python/uv | snakepacker/python:uv ghcr.io/snakepacker/python/jupyterlab | snakepacker/python:jupyterlab ghcr.io/snakepacker/python/base | snakepacker/python:base
Image descriptions
The images according to their purpose and features:
Tag | Info | Purpose | Features ------- |------------------------------------------------------------------------------------------| ------- | -------- all | | build stage | all available python versions, libpython headers and compiler all-pillow |
| build stage | all available python versions, libpython headers, graphics libraries headers and compiler 3.13 |
| target stage | pure python 3.13 3.12 |
| target stage | pure python 3.12 3.11 |
| target stage | pure python 3.11 3.10 |
| target stage | pure python 3.10 3.9 |
| target stage | pure python 3.9 3.8 |
| target stage | pure python 3.8 3.13-pillow |
| target stage | pure python 3.13 with graphics libraries binaries 3.12-pillow |
| target stage | pure python 3.12 with graphics libraries binaries 3.11-pillow |
| target stage | pure python 3.11 with graphics libraries binaries 3.10-pillow |
| target stage | pure python 3.10 with graphics libraries binaries 3.9-pillow |
| target stage | pure python 3.9 with graphics libraries binaries 3.8-pillow |
| target stage | pure python 3.8 with graphics libraries binaries pylama |
| ready to use | pylama application image (useful for CI) pylava |
| ready to use | pylava application image (useful for CI) ipython |
| ready to use | ipython application image certbot |
| ready to use | certbot application image black |
| ready to use | black application image (useful for CI) gray |
| ready to use | gray application image (useful for CI) ruff |
| ready to use | ruff linter image (useful for CI) uv |
| ready to use | An extremely fast Python package and project manager (useful for CI) jupyterlab |
| ready to use | jupyterlab image base |
| | common layers
Concept
The main idea of this method is to build a virtualenv for your package using heavy full-powered image (e.g. ghcr.io/snakepacker/python:all, that contains all necessary headers, libraries, compiler, etc.), and then copy it into thin base image with suitable Python version.
Reasons
Why so complex? You could just COPY directory with your python project into Docker container, and for the first point of view this seems to be reasonable.
But just copying directory with python project cause several problems:
- Generated on different operating system .pyc files can be put into Docker
- Large possibility that you would also pack garbage files: pytest and tox
- No explicit entrypoint. It is not obvious what commands end user is able to
-h or --help arguments).
- By default, tox interprets your package as python module, e.g. it tries to
pip install . when preparing environment.
Yes, of course, you can solve all of those problems using hacks, specific settings, .dockeridnore file, and other tricks. But it would be non-intuitive and non-obvious for your users.
So, we recommend to spend a little more time and pack your package carefully, so your users would run it with pleasure.
Example
For example, you may build the jupyter notebook. Just create a Dockerfile with the following content:
#################################################################
####################### BUILD STAGE #############################
#################################################################
This image contains:
1. All the Python versions
2. required python headers
3. C compiler and developer tools
FROM ghcr.io/snakepacker/python:all as builder
Create virtualenv on python 3.10
Target folder should be the same on the build stage and on the target stage
RUN python3.10 -m venv /usr/share/python3/app
Install target package
RUN /usr/share/python3/app/bin/pip install -U pip 'ipython[notebook]'
Will be find required system libraries and their packages
RUN find-libdeps /usr/share/python3/app > /usr/share/python3/app/pkgdeps.txt
################################################################# ####################### TARGET STAGE ############################ #################################################################
Use the image version used on the build stage
FROM ghcr.io/snakepacker/python:3.10
Copy virtualenv to the target image
COPY --from=builder /usr/share/python3/app /usr/share/python3/app
Install the required library packages
RUN xargs -ra /usr/share/python3/app/pkgdeps.txt apt-install
Create a symlink to the target binary (just for convenience)
RUN ln -snf /usr/share/python3/app/bin/ipython /usr/bin/
CMD ["ipython"]
And just build this:
docker build -t ipython .
Useful tools
All images contain ready to use and simple wrappers for easy image building.
apt-install
Pretty simple bash script. The main purpose is removing the apt cache and temporary files after installation when you want to install something through apt-get install.
Otherwise, you have to write something like this
apt-get update && \
apt-get install -y tcpdump && \
rm -fr /var/lib/apt/lists /var/lib/cache/ /var/log/
It might be replaced like this:
apt-install tcpdump
wait-for-port
Python script which waits for availability one or multiple TCP ports. It's very useful for tests and with docker-compose.
wait-for-port --period=0.5 --timeout=600 postgres:5432 pgbouncer:6432 && python myscript.py
Or shorter (values from previous example are defaults):
wait-for-port postgres:5432 pgbouncer:6432 && python myscript.py
This script will be trying to make connections to passed endpoints until timeout would be reached or endpoints stay connectable.
find-libdeps
A shell script which find binary *.so files and resolve required system package for install library dependencies.
Save required packages
find-libdeps /usr/share/python3/app > /usr/share/python3/app/pkgdeps.txt
Install saved packages
xargs -ra /usr/share/python3/app/pkgdeps.txt apt-install