Python Recipes

Debug and Profile Python Apps from the CLI

6 steps|12 min|debugging, profiling, pdb

Use Python's built-in debugger (pdb), profiling tools (cProfile), and memory analysis to find bugs and performance bottlenecks from the command line.

$ python -m pdb script.py

Package Python Apps in Docker with Multi-Stage Builds

5 steps|15 min|docker, container, multi-stage

Containerize Python applications using Docker multi-stage builds for small, secure, production-ready images.

$ cat > Dockerfile << 'EOF'

Static Type Checking with mypy

5 steps|10 min|mypy, types, static-analysis

Add static type checking to your Python project with mypy to catch type errors before runtime and improve code documentation.

$ pip install mypy

Full Project Lifecycle with Poetry

6 steps|12 min|poetry, pyproject, packaging

Manage Python project dependencies, virtual environments, versioning, and publishing with Poetry's declarative pyproject.toml workflow.

$ pipx install poetry

Manage Multiple Python Versions with pyenv

6 steps|10 min|pyenv, python-versions, version-management

Install and switch between multiple Python versions on the same machine using pyenv, with per-project version pinning.

$ curl https://pyenv.run | bash

Testing Workflow with pytest, Fixtures, and Coverage

6 steps|15 min|pytest, testing, fixtures

Write and run Python tests with pytest, using fixtures for setup, parametrize for data-driven tests, and coverage for reporting.

$ pip install pytest pytest-cov pytest-xdist

Fast Linting and Formatting with Ruff

5 steps|6 min|ruff, linting, formatting

Use Ruff to lint and format Python code at extreme speed, replacing Flake8, isort, Black, and dozens of other tools in a single binary.

$ pip install ruff

Blazing-Fast Dependency Management with uv

6 steps|7 min|uv, pip, fast

Use uv from Astral as a drop-in replacement for pip and virtualenv with 10-100x faster installs and built-in project management.

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

Set Up a Python Project with Virtual Environment

6 steps|8 min|venv, virtualenv, setup

Create an isolated Python environment with dependencies, linting, and a reproducible project structure ready for collaboration.

$ mkdir myproject && cd myproject