You open a project to contribute code and quickly realize it requires a specific Python version you don’t have. Not only that, but it’s managing dependencies with some tool you don’t have, like Pipenv or Poetry. What are your options? You could spend a while setting up your machine with a fancy Python development environment , or you could get up and running right away using Docker as a Python version manager - which works the same across MacOS, Windows, and Linux .
👍 Use this Docker strategy if you:
👎 Use the traditional setup with
pyenv if you:
⚠️ If you’re trying to install a CLI tool or script written in Python, you’ll want to explore tools like Pipx . It’s possible to run scripts in containers, but I wouldn’t recommend for everyone.
Why would you bother managing Python versions and environments with Docker when there are tools built to do it for you?
Enough chatter, now shut up and tell me how!
#Step 1 git clone <your-repo>.git cd <your-repo> # Step 2 & 3: creates container that is destroyed after session docker run -it --rm --name python-runner -v "$PWD":/usr/src/myapp -w /usr/src/myapp python:3.7 bash # OPTIONAL ALTERNATIVE> Step 2,3,& 3a: retain container between sessions docker run -it --name <project-name> -v "$PWD":/usr/src/myapp -w /usr/src/myapp python:3.7 bash # .... many hours later... docker start -i <project-name> # Step 4 # install dependencies following the directions based on your project
3.6, 3.7, 3.8, 3.9,or
3.10, but you can find every available option on Docker Hub . Your image will then be
docker runcommand to create a transient container (swap version if needed). The
bashon the end, along with
-ittells Docker to give us an interactive shell, just like when you open a new terminal prompt. The
-wmake the current directory available inside the container, so you’ll need to always run this command from the project.
--namethat you will recognize and remove the
--rm(which removes the container when the current run finishes). Now in the future, you can use
docker start -i project-nameto pop open the shell, rather than needing to create a brand new container and install dependencies again.
Now you’ve got a container running with the Python version the project needs, how can you handle required dependencies? You may need to install a tool inside your running container depending on how the project is configured, directions for the most common options are below. These commands should be run in the container shell created by the
docker run command, not on your local system.
Nothing special needed here, run
pip install --user -r requirement.txt and you’re off the the races.
Couple extra steps needed to get a Pipenv project running.
pip install --user pipenv # Ensure tool is available in your container's PATH echo "export PATH=~/.local/bin:$PATH" >> ~/.bashrc . ~/.bashrc # equivalent to 'source ~/.bashrc' pipenv install --dev
Check the Poetry docs to ensure install command is up to date.
curl -sSL <https://install.python-poetry.org> | python3 - # Ensure tool is available in your container's PATH echo "export PATH=~/.local/bin:$PATH" >> ~/.bashrc . ~/.bashrc # equivalent to 'source ~/.bashrc' poetry install
runcommand to expose the port. Something like
-p 8080:80 -p 443:443is the recommended route to map :. Read more on StackOverflow .
This simpler approach to managing Python versions is another tool in your toolbox, and it can be applied for other languages as well. Hopefully you find success using this to get up and running on projects rather than fiddling with system configurations. Let me know if you have suggestions on ways to make it even simpler and improve it for future users.
Do you want to be more than a code monkey? Learn to avoid blunders and become a superhero to your team.
Lessons learned from a couple days spent debugging everything BUT the problem.
It's so easy as a developer to dismiss the idea of learning no-code tools. After all, you know how to code, why spend time learning tools designed for those who can't?