Python Developer Tooling Handbook – Python Development Tooling Tutorials

Build a Python library with a C extension

Tim Hopper — Wed, 29 Apr 2026 07:06:23 -0400

Python handles strings well. C handles them faster. In this tutorial, you’ll write three string functions in C, compile them into a shared library, and call them from Python using cffi. The result is a normal Python package that anyone can import.

Prerequisites

You need two things installed:

uv (installation guide)
A C compiler

Most macOS and Linux systems already have a C compiler. Check by running:

Build a Python library with a C++ extension

Tim Hopper — Fri, 08 May 2026 03:18:44 -0400

Python handles most tasks well, but numerical code and tight loops can hit its performance ceiling. C++ removes that ceiling. This tutorial walks you through creating a Python package where the performance-critical code lives in C++, compiled into a native extension module that Python imports like any other module.

You’ll use three tools together:

uv manages the Python project, dependencies, and virtual environment
scikit-build-core is the build backend that drives CMake to compile C++ code into a Python extension module
pybind11 is the C++ library that bridges C++ and Python, letting you write C++ functions callable from Python

Prerequisites

uv installed (installation guide)
A C++ compiler (g++ or clang++)
CMake 3.15 or later

Most macOS and Linux systems ship with a C++ compiler. On macOS, install the Xcode Command Line Tools (xcode-select --install). On Ubuntu/Debian, install the build-essential and cmake packages.

Build a Python library with a Rust extension

Tim Hopper — Sun, 12 Apr 2026 07:17:52 -0400

Python is flexible and productive, but sometimes a function needs to run faster than Python allows. Rust gives you that speed with memory safety and no garbage collector. This tutorial walks you through creating a Python package where the performance-critical code lives in Rust, compiled into a native extension module that Python imports like any other module.

You’ll use three tools together:

uv manages the Python project, dependencies, and virtual environment
maturin is the build backend that compiles Rust code into a Python extension module
PyO3 is the Rust library that bridges Rust and Python, letting you write Rust functions callable from Python

Prerequisites

uv installed (installation guide)
Rust installed via rustup

Verify both are working:

Create your first Python project with pixi

Tim Hopper — Fri, 10 Apr 2026 12:46:15 -0400

This tutorial builds a weather data analysis tool that reads CSV data, computes statistics with pandas, and produces a chart with matplotlib. Every dependency comes from conda-forge and is managed by pixi.

Prerequisites

Install pixi following the official installation instructions. No separate Python install is required.

Create the project

pixi init weather_analysis
cd weather_analysis

This creates a directory with a pixi.toml file that stores project metadata, dependencies, and task definitions:

Create your first Python project with uv

Tim Hopper — Mon, 04 May 2026 10:58:58 -0400

This Python uv tutorial walks you through building a text analysis tool that counts words, measures sentence length, and reports word frequency. No prior Python experience required; uv handles the Python install, project scaffolding, and dependency management for you.

Prerequisites

Before we begin, make sure you have uv installed on your system. You can install it following the directions from the uv documentation.

Tip

Getting started with uv

Tim Hopper — Mon, 04 May 2026 08:09:53 -0400

uv handles Python installation, project setup, dependency management, and script execution in a single tool. This tutorial walks through each of those capabilities so you can start using uv for any Python project.

Prerequisites

You need a terminal (Terminal on macOS, PowerShell on Windows, or any Linux shell). No prior Python installation is required.

Installing uv

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

Alternatively, install with Homebrew:

Migrate a conda project to pixi

Tim Hopper — Wed, 29 Apr 2026 13:11:49 -0400

This tutorial converts a conda project (defined by an environment.yml) into a pixi project. The result: project-local environments, an automatic lockfile, a built-in task runner, and access to the same conda-forge packages.

Prerequisites

pixi installed (installation instructions)
An environment.yml file from an existing conda project
Familiarity with conda workflows (see Take Over an Existing Conda Environment if you’re new to conda)

Why migrate

Conda works, but pixi solves several friction points:

Publishing Your First Python Package to PyPI

Tim Hopper — Tue, 28 Apr 2026 08:41:30 -0400

This tutorial guides you through publishing a Python package to the Python Package Index (PyPI) using uv. You’ll learn the essential steps of building and uploading a package that others can install with pip or uv.

Since this is your first package, we’ll start by uploading to TestPyPI, a “separate instance of the Python Package Index that allows you to try distribution tools and processes without affecting the real index.”

Prerequisites

uv installed (installation guide)
A TestPyPI account (register here)
A Python project ready for distribution

Setting Up Your Project

Create a new project with a name that is not currently taken on Test PyPI. You might try something like your name followed by a random number, e.g. timhopper2456543. Browse the project’s URL at https://test.pypi.org/project/<PACKAGE_NAME>/ first; if it returns a project page rather than a 404, the name is taken and uv publish will fail later.

Run your first Python script with uv

Tim Hopper — Thu, 07 May 2026 07:15:18 -0400

uv can run Python scripts without any prior Python installation. This tutorial starts with a one-line script and builds up to using a third-party package through inline script metadata.

Prerequisites

Install uv on your system.

Tip

Set up a data science project with uv

Tim Hopper — Tue, 05 May 2026 06:58:20 -0400

This tutorial sets up a data analysis project with uv so that every dependency is pinned, notebooks run in the right environment, and a collaborator can reproduce your setup with a single command.

Prerequisites

Install uv following the installation guide. No separate Python install is required.

Create the project

$ uv init weather_analysis
Initialized project `weather-analysis` at `/path/to/weather_analysis`
$ cd weather_analysis

This creates a project directory with a pyproject.toml, a main.py, and a README.md. The pyproject.toml stores all project metadata and dependencies:

Set up a Django project with uv

Tim Hopper — Tue, 05 May 2026 06:57:20 -0400

Most Django setup guides still tell you to install Python and a virtual environment by hand before you reach runserver. This tutorial uses uv for the Python install and the virtual environment. Every manage.py command runs against a pinned interpreter.

Confirm uv is installed

If you do not already have uv, follow the installation guide. No separate Python install is required; uv will download an interpreter on first use.

Set up a GPU data science project with pixi

Tim Hopper — Fri, 10 Apr 2026 12:46:15 -0400

This tutorial builds a PyTorch image classification project managed by pixi. It loads a pretrained ResNet model, classifies a sample image, and prints the top-5 predictions. The project uses pixi’s multi-environment feature to support both GPU (CUDA) and CPU-only machines from a single pixi.toml.

Prerequisites

pixi installed (installation instructions)
Familiarity with pixi basics (see Create Your First Python Project with pixi)
For GPU: an NVIDIA GPU with a recent driver. For CPU-only: everything works, just slower.

Why conda-forge for PyTorch

PyTorch on conda-forge shares the CUDA runtime with other packages. When you install PyTorch and cuDNN from conda-forge, they use the same cuda-toolkit package rather than each bundling its own copy. This produces smaller environments and avoids version conflicts between CUDA-dependent libraries.

Set up Ruff for formatting and checking your code

Tim Hopper — Sat, 02 May 2026 08:50:33 -0400

This tutorial helps you set up Ruff to automatically format your Python code and check it for common errors and style issues.

Prerequisites

Before starting, make sure you have uv installed on your system. You can install it following the installation guide.

You do not need Python installed - uv will handle installing it automatically.

Creating a sample project

Let’s create a new project to demonstrate Ruff:

Setting up GitHub Actions with uv

Tim Hopper — Wed, 06 May 2026 06:25:49 -0400

Every push to main and every pull request should be tested and linted automatically. This tutorial sets up that pipeline using GitHub Actions and uv, running pytest and Ruff across multiple Python versions.

Prerequisites

uv installed (installation guide)
A GitHub account
Familiarity with setting up testing with pytest and uv

Clone the Example Project

This tutorial uses a small temperature-converter project with code and tests already written but no CI configured. Clone it and move into the directory:

Setting up testing with pytest and uv

Tim Hopper — Tue, 28 Apr 2026 16:07:14 -0400

Every Python project needs tests, but setting up a test suite from scratch involves decisions about project layout, dependency management, and configuration. This tutorial walks through the full setup using pytest and uv: creating a project, writing tests, using fixtures, measuring coverage, and configuring defaults.

Prerequisites

Install uv on your system.

Creating a Project with Tests

Start by creating a sample project with a test directory structure:

Take over an existing conda environment

Tim Hopper — Mon, 04 May 2026 08:00:31 -0400

You just joined a team or lab that uses conda. Someone handed you an environment.yml and told you to conda activate. This tutorial walks through the day-to-day operations: creating an environment from a file, exploring what’s installed, adding packages, handling the conda+pip boundary, and exporting a reproducible environment for teammates.

Prerequisites

Install Miniforge following the Miniforge installation instructions.

Important

Try Free-Threaded Python with uv

Tim Hopper — Fri, 17 Apr 2026 09:32:42 -0400

Python threads usually don’t make CPU-bound code faster. The Global Interpreter Lock lets only one thread execute Python bytecode at a time, so four threads crunching through CPU work run no faster than one. Python 3.14 is the first release where the free-threaded build, proposed in PEP 703: Making the Global Interpreter Lock Optional in CPython, ships as officially supported under PEP 779: Criteria for supported status for free-threaded Python. This tutorial walks you through installing both the standard and free-threaded builds with uv, running the same threaded benchmark on each, and measuring the speedup.