Summary and Schedule

This lesson teaches how to share Python code, both in the form of packages, and reproducible scripts. The teaching philosophy is to cover “good enough” practices, with more content linked out when necessary.

Prerequisite

• Basic understanding of Python syntax
• Basic understanding of Shell scripts

Do I know enough Python?

Knowledge of the interactive terminal or a Jupyter instance suffices.

PYTHON

a = [3,5,6.0]

def mysquarer(_a):
    for x in _a:
        x=x**2
    return _a

mysquarer(a)

Do I know enough Shell scripting?

Navigation of the file system through a terminal will suffice, as well as remembering that everything is a file on Unix systems, as far as the contents of the lesson at any rate.

BASH

# get files in directory
ls
# get directory name
pwd
# view first few lines of a file
head readme.org

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. Writing Reproducible Python	What is the difference between the standard library and third-party packages? How do I share a script so that it runs on someone else’s computer? :::
Duration: 00h 30m	2. Modules, Packages, and The Search Path	How does Python know where to find the libraries you import? What distinguishes a python “script” from a python “package”? What is an __init__.py file? :::
Duration: 00h 50m	3. The Project Standard: pyproject.toml	How do I turn my folder of code into an installable library? What is pyproject.toml and why is it the standard? How does uv simplify project management? Why use the src layout? :::
Duration: 01h 20m	4. Quality Assurance: Testing and Linting	How do I keep development tools separate from my library dependencies? How can I automatically fix style errors? How do I ensure my code works as expected? What are pre-commit hooks? :::
Duration: 01h 50m	5. release_engineering.md	How do I manage release notes without merge conflicts? How do I publish my package to the world (safely)? :::
Duration: 02h 00m	6. If It Isn’t Documented, It Doesn’t Exist	How do I generate professional documentation for my Python package? What are docstrings, and how do they become web pages? How do I link my documentation to other projects like NumPy? :::
Duration: 02h 40m	7. The Gatekeeper: Continuous Integration	What happens if I forget to run the tests before pushing? How do I ensure my code works on Windows, Linux, and macOS? How do I automate uv in the cloud? :::
Duration: 03h 10m	8. Compiled Extensions: The Shared Object Pipeline	How does the Python ecosystem deliver high-performance binaries to users? What distinguishes a “Source Distribution” from a “Binary Wheel”? What role does cibuildwheel play in software distribution? :::
Duration: 04h 00m	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

Software setup

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Discussion

Details

We basically require pixi and uv. For conciseness, we reproduce the most direct instructions below.

Technically any Python interpreter suffices, here we use pixi to handle system dependencies and run tasks, with uv for managing Python dependencies and environments.

Windows

Following along with the pixi instructions upstream here.

BASH

powershell -ExecutionPolicy Bypass -c "irm -useb https://pixi.sh/install.ps1 | iex"

Along with uv from the official installation documentation.

BASH

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

MacOS and Linux

Following along with the pixi instructions upstream here.

BASH

curl -fsSL https://pixi.sh/install.sh | sh

Along with uv from the official documentation.

BASH

curl -LsSf https://astral.sh/uv/install.sh | sh

Accounts required

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To finalize publishing to an index ¹ we need:

A Git instance in the cloud

Any of Github, Gitlab, Sourcehut etc. would work, Github is recommended.

An index account

For the tutorial Test PyPI will suffice, for production, an account on PyPI would be required as well.

Checklist

• I have an account on a Git server
• I have an account on Test PyPI

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1. Making the code widely available over the net↩︎