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 Bionic operation system.

Available images

Tag	Purpose	Features
modern	build stage	modern python versions (3.5, 3.6, 3.7, 3.8, 3.9), libpython headers and compiler
modern-pillow	build stage	modern python versions (3.5, 3.6, 3.7, 3.8, 3.9), libpython headers, graphics libraries headers and compiler
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
3.9	pure python 3.9
3.8	target stage	pure python 3.8
3.7	target stage	pure python 3.7
3.6	target stage	pure python 3.6
3.5	target stage	pure python 3.5
3.4	target stage	pure python 3.4
3.3	target stage	pure python 3.3
3.2	target stage	pure python 3.2
3.1	target stage	pure python 3.1
2.7	target stage	pure python 2.7
2.6	target stage	pure python 2.6
2.5	target stage	pure python 2.5
2.4	target stage	pure python 2.4
2.3	target stage	pure python 2.3
3.8-pillow	target stage	pure python 3.8 with graphics libraries binaries
3.9-pillow	target stage	pure python 3.9 with graphics libraries binaries
3.7-pillow	target stage	pure python 3.7 with graphics libraries binaries
3.6-pillow	target stage	pure python 3.6 with graphics libraries binaries
3.5-pillow	target stage	pure python 3.5 with graphics libraries binaries
3.4-pillow	target stage	pure python 3.4 with graphics libraries binaries
2.7-pillow	target stage	pure python 3.3 with graphics libraries binaries
pylama	ready to use	pylama application image (useful for drone.ci)
pylava	ready to use	pylava application image (useful for drone.ci)
ipython	ready to use	ipython application image
certbot	ready to use	certbot application image
base

Concept

The main idea of this method is to build a virtualenv for your package using heavy full-powered image (e.g. 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 image accidentally. Thus, python would try to rewrite .pyc with correct ones each time when Docker image would be started. If you would run Docker image in read-only mode - your application would break.
Large possibility that you would also pack garbage files: pytest and tox cache, developer's virtualenv and other files, that just increate the size of the resulting image.
No explicit entrypoint. It is not obvious what commands end user is able to run (we hope you've implemented -h or --help arguments).
By default, tox interprets your package as python module, e.g. it tries to run 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 snakepacker/python:modern as builder

# Create virtualenv on python 3.7
# Target folder should be the same on the build stage and on the target stage
RUN python3.7 -m venv /usr/share/python3/app

RUN /usr/share/python3/app/bin/pip install -U pip 'ipython[notebook]'

#################################################################
####################### TARGET STAGE ############################
#################################################################
# Use the image version used on the build stage
FROM snakepacker/python:3.7

# Copy virtualenv to the target image
COPY --from=builder /usr/share/python3/app /usr/share/python3/app

# 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.

dlancer/python