Full Stack Development with Python: Building Cloud-Native Applications with FastAPI and Docker

1. Practical Steps for Full Stack Development with FastAPI and Docker

1. 1. Project Initialization and Basic Configuration of FastAPI

   # main.py
   from fastapi import FastAPI
   from pydantic import BaseModel
   
   app = FastAPI(title="Cloud-Native API Service")  # Automatically generate Swagger documentation
   
   class Item(BaseModel):
       name: str
       price: float
   
   @app.post("/items/")
   async def create_item(item: Item):
       """Asynchronously handle POST requests with type validation"""
       return {"item_name": item.name, "price": item.price}

   Code Analysis：

• • Use <span>pydantic</span> models to implement request parameter validation, avoiding illegal data
• • The <span>async</span> keyword supports asynchronous processing, improving concurrency (3 times faster than Flask synchronous interfaces)

# Dockerfile
FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt  # Optimize image size
COPY . .
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "80"]  # Expose port

• • Use <span>slim</span> base image to reduce layer size (40% smaller than standard image)
• • Stage-wise copying of dependency files to leverage Docker cache for faster builds

# docker-compose.yml
version: '3.8'
services:
  api:
    build: .
    ports:
      - "8000:80"
    depends_on:
      - redis
  redis:
    image: redis:alpine
    volumes:
      - redis_data:/data
volumes:
  redis_data:

• • Use <span>docker-compose logs api</span> to view real-time logs
• • <span>depends_on</span> only controls the startup order; health checks are needed to ensure service availability

2. Common Error Debugging Guide

3. Advanced Practices for Cloud-Native Deployment

1. 1. CI/CD Pipeline Configuration

   # .github/workflows/deploy.yml
   jobs:
     deploy:
       runs-on: ubuntu-latest
       steps:
         - name: Login to Aliyun Container Registry
           uses: aliyun/acr-login@v1

• • Automatically trigger image builds and ACK cluster deployments with GitHub Actions

• • Integrate Prometheus to collect API performance metrics (QPS/latency/error rate)
• • Use Grafana dashboards for real-time visualization of monitoring data

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