Building a FastAPI RESTful API from Scratch

1.​Introduction to FastAPI​

Why FastAPI?

• High Performance:
  FastAPI is built on Starlette and Pydantic, supports async features, and its performance is close to Node.js and Go, far surpassing traditional frameworks like Flask and Django.

• Asynchronous Support:
  Native support for async/await, suitable for high-concurrency scenarios.

• Automatic Documentation:
  With simple annotations, FastAPI automatically generates interactive API docs (Swagger UI and ReDoc), making development and testing much easier.

2.​Project Setup

pip install fastapi uvicorn

3.​Creating Your First API​

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def root():
    return {"message": "Hello World"}

4.​​Adding Routes and Pydantic Models

 from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: float

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

5.A Simple FastAPI Application Example

from fastapi import FastAPI
from pydantic import BaseModel
import uvicorn
app = FastAPI()


class Item(BaseModel):
    name: str
    price: float

@app.get("/")
async def root():
    return {"message": "Hello World"}

@app.post("/items/")
async def create_item(item: Item):
    return f'{item.name} {item.price}'

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

The following image shows the interactive API documentation (Swagger UI) automatically generated by FastAPI, where developers can directly test the endpoints.