---
title: "GitHub Copilot Python FastAPI"
description: "Configures GitHub Copilot for efficient REST API development with FastAPI, async/await, and Pydantic validation."
category: "configuration"
tags: ["github-copilot", "python", "fastapi", "async", "api", "pydantic", "jwt", "sqlalchemy", "uvicorn"]
tech_stack: ["python", "fastapi", "pydantic", "uvicorn", "sqlalchemy", "jwt"]
---

This setup helps you make the most of GitHub Copilot while developing REST APIs with FastAPI, async/await, and Pydantic validation. 

### Configuration Overview
With this configuration, you can build strong REST APIs using Python's FastAPI. It supports async programming, automatic data validation through Pydantic, JWT authentication, and integrates with SQLAlchemy ORM.

### Prerequisites
Before you start, make sure you have the following:
- Python 3.7 or newer
- GitHub Copilot activated in your IDE, such as Visual Studio Code
- Basic understanding of Python and REST APIs
- The necessary libraries installed:
  - `fastapi`
  - `uvicorn`
  - `pydantic`
  - `sqlalchemy`
  - `python-jose` (for JWT)

You can install the required packages using pip:
```bash
pip install fastapi uvicorn pydantic sqlalchemy python-jose
```

### Installation & Setup
Here’s how to get everything set up:

1. **Create a new project directory**:
   ```bash
   mkdir fastapi_project
   cd fastapi_project
   ```

2. **Set up a virtual environment**:
   ```bash
   python -m venv venv
   source venv/bin/activate  # Use `venv\Scripts\activate` on Windows
   ```

3. **Install the necessary packages**:
   ```bash
   pip install fastapi uvicorn pydantic sqlalchemy python-jose
   ```

4. **Create your main application file**:
   - Create a file named `main.py` and add the following code:
   ```python
   from fastapi import FastAPI, Depends, HTTPException
   from sqlalchemy import create_engine
   from sqlalchemy.ext.declarative import declarative_base
   from sqlalchemy.orm import sessionmaker
   from pydantic import BaseModel
   from jose import JWTError, jwt

   DATABASE_URL = "sqlite:///./test.db"
   engine = create_engine(DATABASE_URL)
   SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
   Base = declarative_base()

   app = FastAPI()

   class Item(BaseModel):
       name: str
       description: str = None

   @app.post("/items/")
   async def create_item(item: Item):
       return item

   if __name__ == "__main__":
       import uvicorn
       uvicorn.run(app, host="127.0.0.1", port=8000)
   ```

5. **Run your application**:
   ```bash
   uvicorn main:app --reload
   ```

### File Structure
Your project should look like this:
```
fastapi_project/
├── venv/                  # Virtual environment
├── main.py                # Main FastAPI application
└── requirements.txt       # List of dependencies
```

### Key Configuration Files
- **`main.py`**: This file contains your FastAPI application and endpoints.
- **`requirements.txt`**: This file lists your dependencies for easy installation.
```plaintext
fastapi
uvicorn
pydantic
sqlalchemy
python-jose
```

### Advanced Options
- **Database Configuration**: For production applications, consider using PostgreSQL or MySQL instead of SQLite. Just update the `DATABASE_URL` to your chosen database.
- **JWT Authentication**: Implement JWT authentication to secure your API. Use `python-jose` for managing tokens.

### Troubleshooting
If you run into issues, here are some common errors and how to fix them:
- **"ModuleNotFoundError"**: Make sure all your dependencies are installed in the virtual environment.
- **"Address already in use"**: Change the port in the `uvicorn` command or stop the process that's using that port.
- **JWT Token Issues**: Double-check your secret key and the algorithm for encoding and decoding tokens.

### Best Practices
- **Use Environment Variables**: Keep sensitive information like database URLs and secret keys in environment variables.
- **Version Control**: Use Git for version control to maintain a clean commit history.
- **Documentation**: Take advantage of FastAPI’s automatic OpenAPI documentation by visiting `/docs` after starting your server.

### Performance Tuning and Workflow Optimization Tips
- **Enable CORS**: If your API will interact with a frontend application, be sure to configure CORS settings.
- **Asynchronous Database Calls**: Consider using async database libraries to improve performance.
- **Optimize Pydantic Models**: Use `@validator` decorators for complex validation logic to keep your models clean and efficient.