如何在FastAPI中灵活使用路径参数、查询参数和请求体参数进行接口设计

In FastAPI, you can handle different types of parameters in your endpoints, such as path parameters, query parameters, and request body parameters. Each type of parameter is handled differently depending on how it is defined in the endpoint function.

1. Path Parameters

Path parameters are part of the URL path. They are typically used to pass resources or identifiers that are part of the route, for example, /items/{item_id}.

Example:

python 复制代码
@app.put("/items/{item_id}")
async def read_item(item_id: int):
    return {"item_id": item_id}

2. Query Parameters

Query parameters are part of the URL after the ? symbol, and they are used to pass additional data to the request. They are typically used with GET or PUT requests and are defined as function parameters without braces.

Example with a single query parameter:

python 复制代码
@app.put("/items/")
async def read_item(item_id: int):
    return {"item_id": item_id}

To test this with requests:

python 复制代码
import requests
url = 'http://127.0.0.1:8009/items/?item_id=5'
res = requests.put(url)
print(res.text)  # Output: {"item_id": 5}

3. Request Body Parameters

Request body parameters are used when you need to send structured data as the body of the request. These can be either single or multiple parameters passed as JSON in the request body.

Single Request Body Parameter

To specify that a parameter should be in the request body, you use Body().

Example:

python 复制代码
from fastapi import Body, FastAPI

@app.put("/items/")
async def read_item(item_id: int = Body(...)):
    return {"item_id": item_id}

To test with requests:

python 复制代码
import requests
url = 'http://127.0.0.1:8009/items/'
res = requests.put(url, json={"item_id": 5})
print(res.text)  # Output: {"item_id": 5}
Multiple Request Body Parameters

You can also define multiple parameters in the request body by using Body() for each one.

Example:

python 复制代码
from fastapi import Body, FastAPI

@app.put("/items/")
async def read_item(item_id: int = Body(...), name: str = Body(...)):
    return {"item_id": item_id, "name": name}

To test with requests:

python 复制代码
import requests
url = 'http://127.0.0.1:8009/items/'
res = requests.put(url, json={"item_id": 5, "name": "张三"})
print(res.text)  # Output: {"item_id": 5, "name": "张三"}

4. Using Pydantic Models for Request Body

You can also use Pydantic models to define request bodies, which gives you more control and validation over the incoming data.

Example:

python 复制代码
from fastapi import FastAPI
from pydantic import BaseModel

class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None

@app.put("/items/")
async def read_item(item: Item):
    return {"name": item.name, "price": item.price}

To test with requests:

python 复制代码
import requests
url = 'http://127.0.0.1:8009/items/'
data = {"name": "细胞生物学", "description": "考研书籍", "price": 35.8, "tax": 0.6}
res = requests.put(url, json=data)
print(res.text)  # Output: {"name": "细胞生物学", "price": 35.8}

5. Mixed Parameters (Path, Query, and Body)

You can also mix path, query, and body parameters in a single endpoint. FastAPI will automatically handle them correctly.

Example:

python 复制代码
from fastapi import Body, FastAPI

@app.put("/items/{name}")
async def read_item(name: str, age: int, item_id: int = Body(...)):
    return {"name": name, "age": age, "item_id": item_id}

Testing via FastAPI's Documentation

FastAPI also provides a built-in interactive docs interface at /docs that allows you to test all your endpoints directly in the browser. You can input values for query parameters, request body parameters, and see the results.

To access the docs:

  1. Run the FastAPI app.
  2. Open http://127.0.0.1:8009/docs in a browser.
  3. Test your endpoints using the interactive interface by clicking on "Try it out", filling in the parameters, and clicking "Execute".
相关推荐
大牧师27 分钟前
MySQL 学习教程
数据库·sql·mysql·docker·node·全栈·后端数据
Elastic 中国社区官方博客29 分钟前
如何通过一条 ES|QL 查询为 Elasticsearch 中的每个指标构建指标图表
大数据·运维·数据库·elasticsearch·搜索引擎·全文检索·kibana
数据库小学妹1 小时前
MySQL redo刷盘实测:innodb_flush_log_at_trx_commit与故障矩阵
运维·数据库·mysql
ByteRock1 小时前
ClickHouse 表的生老“并”死:表实例、表元数据与并发 DDL
数据库
哈__1 小时前
破除数据库排障碎片化:一体化全链路故障根因诊断实践
数据库
严同学正在努力1 小时前
SQL Server 15.0.2000.5(2019 CU5)性能分析基线构建实战教程
数据库·ai·oracle·dba
青 春 记 忆2 小时前
零基础入门python69:为 FastAPI 项目构建可复现 Docker 镜像
python·fastapi·后端开发
MC丶科2 小时前
软考架构师90天冲刺|DAY44·Redis高级应用
数据库·数据仓库·redis·缓存·oracle·容器·规格说明书
Boop_wu2 小时前
[redis] redis 快速入门
数据库·redis·github
reasonsummer3 小时前
【办公类-115-01】20260906育儿知识(家园小报)批量制作(2026年9月-2027年6月)
开发语言·数据库·c#