Python quick use of REST API

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Getting Started

Install fastapi and ASGI server (e.g. uvicorn):

Make sure you are using Python 3.6.7 If pip and python give you a python 2 version, you may have to use pip3

python3

pip install fastapi uvicorn

file:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def home():
    return {"Hello": "World"}

then To run for development, you can run uvicorn main:app --reload That’s all a simple server does! Now you can check //localhost:8000/ to see the "Home Page". And, as you can see, the JSON response "just works"! You can also get Swagger UI for free at //localhost:8000/docs.

As mentioned before, it is easy to validate the data (and generate Swagger documentation for the accepted data formats). Just add the

import from fastapi and use it to force validation: <div class="code" style="position:relative; padding:0px; margin:0px;"><pre class="brush:php;toolbar:false">from fastapi import FastAPI, Query @app.get('/user') async def user(     *,     user_id: int = Query(..., title=&quot;The ID of the user to get&quot;, gt=0) ):   return { 'user_id': user_id }</pre><div class="contentsignin">Copy after login</div></div> The first parameter ... is the default value if the user does not provide a value This default value is provided. If set to None, there is no default value and the parameter is optional. In order that there is no default value and the parameter is mandatory, use Ellipsis, or

instead. If you run this code, you will automatically see the update on the swagger UI:

/user/1, then just enter and use Path

Query. It is also possible to combine both Post routes

POST route, you can just define the input

@app.post('/user/update')
async def update_user(
    *,
    user_id: int,
    really_update: int = Query(...)
):
    pass

Request and Response Models You can use Pydantic models to record and declare detailed Request and response models. Not only does this allow you to have automatic OpenAPI documentation for all your models, but it also validates the request and response models to ensure that any POST data entered is correct and that the data returned conforms to the model.

from pydantic import BaseModel

class User(BaseModel):
    id:: int
    name: str
    email: str

async def update_user(*, user: User):
    pass

Copy after login

Or if you want to Used as output:

@app.get('/user')
async def user(
    *,
    user_id: int = Query(..., title="The ID of the user to get", gt=0),
    response_model=User
):
  my_user = get_user(user_id)
  return my_user

Copy after login

Routing and decomposing a larger API

from fastapi import APIRouter
from .user import router as user_router

router = APIRouter()

router.include_router(
    user_router,
    prefix='/user',
    tags=['users'],
)

from fastapi import APIRouter

router = APIRouter()

@router.get('/')
async def user(
    *,
    user_id: int = Query(..., title="The ID of the user to get", gt=0),
    response_model=User
):
  my_user = get_user(user_id)
  return my_user

from fastapi import FastAPI
from app.routers import v1

app = FastAPI()

app.include_router(
    v1.router,
    prefix="/api/v1"
)

FROM tiangolo/uvicorn-gunicorn-fastapi:python3.7

COPY ./app /app

是否想通过自动重新加载进行 Dockerize 开发？这是我在撰写文件中使用的秘方：

version: "3"
services:
  test-api:
    build: ..
    entrypoint: '/start-reload.sh'
    ports:
        - 8080:80
    volumes:
        - ./:/app

这会将当前目录挂载为app并将在任何更改时自动重新加载。您可能还想将app / app用于更大的应用程序。

有用的网址

所有这些信息都来自 Fastapi网站，该文档具有出色的文档，我鼓励您阅读。此外，作者在 Gitter 上非常活跃并乐于助人！

结论

就是这样-我希望本指南对您有所帮助，并且您会像我一样喜欢使用 Fastapi。

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