Python Project Setup: A Step-by-Step Guide to Industry Best Practices
Learn how to properly setup and kickstart your python project. And all the nitty-gritty details of which tools to use and how to configure them together, through building a simple CLI.
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As you start working on your python project, you’ll likely need to set it up in a consistent and collaboration-friendly way. In this article, I’ll describe a setup that works great for our projects at Turo, and also my personal ones. It includes many industry best practices (semantic versioning, pre-commit, linting, or how to release code to mention but a few).
In short, we’ll cover how to properly install python, structure your code, run automated checks both on local with pre-commit and the server side with GitHub Actions (aka GHA).
This article covers quite a few topics. To ease the reading, each section will usually be split in two parts:
- 📚 for the theory part
- 🛠️ for the practical part (i.e. the commands you need to run to reproduce).
Sometimes a 💡 section will also indicate a coding tip or trick.
Table of Contents
- Install a Python version manage (pyenv)
- Choose an environment manager (poetry)
- Otherwise, use Docker to isolate dependencies
- Add Some Code
- Write Some Tests
- Linting our code
- Automate checks on local with pre-commit
- Automate checks on remote with GitHub Actions
- Automate our release with GitHub Actions
- Enjoy the benefits of your new code practices
1. Install a Python version manager (pyenv)
📚 The first thing we’ll need to do is to install a python version manager which will enable us to have multiple versions of python installed on our machine and switch between them easily.
To illustrate this, let’s say we have a project that requires python 3.6 and another project that…
