This repository contains a comprehensive tutorial demonstrating Warp's AI-powered terminal capabilities for Python development, including multi-agent workflows and computational biology examples.

Developed as part of Argonne's vibe coding hackathon

1. Open the main tutorial: warp-python-tutorial.md
2. Run the commands: Click on any warp-runnable-command block to execute it directly in Warp
3. Try the AI Agent: Use @agent commands to let AI write code for you

• warp-python-tutorial.md - Main tutorial with interactive examples
• sample_calculator.py - Example calculator with error handling
• requirements.txt - Python dependencies for tutorial examples
• README.md - This file

• Agentic Coding: Let AI write complete Python programs
• Multi-Agent Workflows: Coordinate multiple specialized agents for complex projects
• Interactive Development: Smart auto-completion and suggestions
• Debugging: AI-powered error resolution
• Workflows: Automated development processes
• Notebooks: Executable documentation
• Computational Biology: Real scientific workflows with molecular dynamics

• Setting up development environments
• Writing and testing Python code
• Error handling and debugging
• Working with APIs and databases
• Code quality and testing
• Git workflows
• Scientific computing with OpenMM
• Molecular dynamics simulations

1. Use Natural Language: Describe what you want to build, and let Warp's AI create the code
2. Ask for Help: When stuck, use @agent to get assistance with any coding problem
3. Experiment: The best way to learn is by trying different commands and examples
4. Save Your Work: Use Git to track your progress through the tutorial

• Basic terminal familiarity
• Python 3.7+ installed
• No prior Python experience required!
• For computational biology: conda/mamba recommended

1. Environment Setup - Virtual environments and project structure
2. Agentic Coding - Let AI write your code
3. Interactive Development - Real-time assistance features
4. Debugging - Error resolution with AI help
5. Testing - Automated testing and quality assurance
6. Workflows - Development automation
7. Advanced Features - APIs, databases, web scraping
8. Multi-Agent Workflows - Coordinate multiple agents for complex projects
9. Computational Biology - Molecular dynamics simulations with OpenMM
10. Notebooks - Interactive documentation
11. Troubleshooting - Common issues and solutions
12. Next Steps - Advanced topics and resources

Try these in Warp's terminal:

@agent Create a Python script that downloads and analyzes weather data
@agent Help me debug this error in my Python code
@agent Create unit tests for my calculator functions
@agent Set up a Flask web application with a REST API

@agent:backend Create a Flask API with user authentication
@agent:frontend Build a React interface that uses the backend API
@agent:testing Create comprehensive tests for both frontend and backend
@agent:devops Set up Docker containers and deployment scripts

@agent:structure Prepare protein structures for molecular dynamics
@agent:simulation Set up OpenMM molecular dynamics simulations
@agent:analysis Analyze MD trajectories and validate hypotheses
@agent:reporting Generate scientific reports and visualizations

• Warp Documentation
• Python Official Docs
• Python Package Index
• OpenMM Documentation
• MDTraj Documentation

This tutorial is provided as educational material. Feel free to use and modify for learning purposes.

Ready to start? Open warp-python-tutorial.md in Warp and begin your AI-powered Python development journey! 🐍✨