Python¶

Reproducible environments for scripts, notebooks, and small projects.

Modern Python development is about creating consistent, reproducible environments that work the same way across different machines and team members. This section covers the essential tools and patterns for clean Python development.

🎯 Goals¶

Reproducible environments with pyenv and uv
Clean project structure that scales from scripts to packages
Effective workflows for notebooks, testing, and CLI tools
Modern tooling that actually makes development faster

🔍 Quick Verification¶

Test your Python environment:

# Check Python version management
pyenv --version
pyenv versions

# Check fast package manager
uv --version

# Check current Python and pip
python --version
python -m pip --version

# Test virtual environment creation
uv venv test-env --python 3.12
source test-env/bin/activate  # Linux/macOS
deactivate && rm -rf test-env

📚 Essential Guides¶

Environment & Setup¶

Install & Setup - Get pyenv and uv working properly
pyenv - Python version management and project-specific versions
uv - Fast Python package manager and environment creation
Environments & Dependencies - Virtual environments and package management
Project Structure - src/ layout, .gitignore, and README patterns

Development Workflows¶

Notebooks - Jupyter and VS Code notebook best practices
Data Workflow - Pandas quickstart for data projects
CLI Basics - python -m usage and argparse patterns
Testing - pytest fundamentals and test organization

Advanced (Optional)¶

Lint & Format - ruff and black setup (coming soon)
Packaging - Building and distributing Python packages (coming soon)

🚀 Common Workflows¶

New Project Setup¶

Create directory → mkdir my-project && cd my-project
Initialize environment → Install & Setup
Set up structure → Project Structure
Install dependencies → Environments & Dependencies
Start coding → Choose notebooks, scripts, or packages

Typical Project Structure¶

my-project/
├── .gitignore           # Python-specific ignores
├── .python-version      # pyenv version pinning  
├── README.md           # Project documentation
├── pyproject.toml      # Modern Python configuration
├── requirements.txt    # or uv.lock for dependencies
├── src/               # Source code directory
│   └── my_project/    # Main package
├── tests/             # Test files
├── notebooks/         # Jupyter notebooks (optional)
└── scripts/           # Utility scripts (optional)

Data Analysis - Using Python for data exploration and analysis
Git - Version control workflow for Python projects
AI Tools - Using Claude Code and other AI tools with Python
Toolkit - VS Code and development environment setup

⚡ Quick References¶

Environment Management:

# Create and activate virtual environment
uv venv .venv --python 3.12
source .venv/bin/activate  # Linux/macOS
# .venv\Scripts\activate   # Windows

# Install dependencies
uv pip install pandas matplotlib jupyter
uv pip install -r requirements.txt

# Generate requirements
uv pip freeze > requirements.txt

Project Initialization:

# Quick project setup
mkdir my-project && cd my-project
echo "3.12" > .python-version
uv venv .venv --python 3.12
source .venv/bin/activate
mkdir src tests
touch README.md .gitignore pyproject.toml

Common Commands:

# Run Python module
python -m my_package

# Run tests
python -m pytest

# Install in development mode
pip install -e .

# Start Jupyter
jupyter lab

Basic Script Template:

#!/usr/bin/env python3
"""
Brief description of what this script does.
"""

def main():
    """Main function."""
    print("Hello, World!")

if __name__ == "__main__":
    main()

Start here: If you're new to modern Python development, begin with Install & Setup to get pyenv and uv working, then follow Project Structure for organizing your code.