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FastAPI Best Practices

This guide covers best practices for developing FastAPI applications.

Project Structure

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myproject/
├── app/
│   ├── __init__.py
│   ├── main.py
│   ├── api/
│   │   ├── __init__.py
│   │   ├── v1/
│   │   │   ├── __init__.py
│   │   │   ├── endpoints/
│   │   │   └── router.py
│   ├── core/
│   │   ├── __init__.py
│   │   ├── config.py
│   │   └── security.py
│   ├── db/
│   │   ├── __init__.py
│   │   └── session.py
│   ├── models/
│   │   └── __init__.py
│   └── schemas/
│       └── __init__.py
├── tests/
│   └── __init__.py
├── alembic/
├── requirements.txt
└── README.md

Code Organization

  1. API Versioning 

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    from fastapi import APIRouter

api_router = APIRouter()
api_router.include_router(v1_router, prefix="/v1")

  2. Configuration Management 

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    from pydantic_settings import BaseSettings

class Settings(BaseSettings):
    PROJECT_NAME: str = "My API"
    VERSION: str = "1.0.0"
    API_V1_STR: str = "/v1"

    class Config:
        env_file = ".env"

  3. Database Session Management 

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    from sqlalchemy.orm import sessionmaker
from contextlib import contextmanager

@contextmanager
def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()

Security Best Practices

  1. Environment Variables
  2. Never hardcode sensitive information
  3. Use .env files for development

  4. Use secure secret management in production

  5. Authentication

  6. Use JWT tokens for stateless authentication
  7. Implement proper token refresh mechanisms

  8. Use secure password hashing (e.g., bcrypt)

  9. Authorization

  10. Implement role-based access control
  11. Use dependency injection for permission checks
  12. Validate user permissions at the API level

Performance Optimization

  1. Database Operations
  2. Use connection pooling
  3. Implement proper indexing

  4. Use async database drivers when possible

  5. Caching

  6. Implement response caching
  7. Use Redis for distributed caching

  8. Cache expensive computations

  9. Response Optimization

  10. Use response compression
  11. Implement pagination for large datasets
  12. Use proper HTTP caching headers

Testing

  1. Unit Tests 

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    from fastapi.testclient import TestClient

def test_read_main():
    response = client.get("/")
    assert response.status_code == 200

  2. Integration Tests

  3. Test database operations
  4. Test authentication flows

  5. Test error handling

  6. Load Testing

  7. Use tools like locust for load testing
  8. Monitor performance metrics
  9. Set up proper monitoring

Documentation

  1. API Documentation
  2. Use descriptive docstrings
  3. Include examples in documentation

  4. Document error responses

  5. Code Documentation

  6. Follow PEP 257 for docstrings
  7. Document complex algorithms
  8. Keep documentation up to date

Error Handling

  1. Custom Exceptions 

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    from fastapi import HTTPException

class ItemNotFound(HTTPException):
    def __init__(self):
        super().__init__(
            status_code=404,
            detail="Item not found"
        )

  2. Error Responses

  3. Use consistent error response format
  4. Include helpful error messages
  5. Log errors appropriately

Deployment

  1. Containerization
  2. Use Docker for containerization
  3. Implement proper health checks

  4. Use multi-stage builds

  5. CI/CD

  6. Set up automated testing
  7. Implement deployment pipelines
  8. Use infrastructure as code

Monitoring and Logging

  1. Logging 

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    import logging

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)

  2. Monitoring

  3. Set up application metrics
  4. Monitor system resources
  5. Implement alerting

Next Steps