fastapi Schema 添加注释

在 FastAPI 中，你可以通过使用 Pydantic 模块来定义数据模型和请求/响应体模式。为了添加注释，只需要在数据模型中添加字段的描述即可。

示例代码：

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str  # 商品名称
    price: float  # 商品价格
    description: str = None  # 商品描述
    tax: float = None  # 税费

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

在上面的示例中，我们为数据模型 `Item` 中的每个字段添加了注释。这些注释将会在自动生成的 API 文档中显示。

相关问题

fastapi Schema 设置必填

在 FastAPI 中，可以使用 Pydantic 模块来定义数据模型和数据验证规则。如果要将某些字段设置为必填，需要在模型类中将它们标记为 required。例如：

from fastapi import FastAPI
from pydantic import BaseModel

class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = None

app = FastAPI()

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

在上面的代码中，name 和 price 字段是必填的，因为它们没有默认值，并且没有标记为可选。is_offer 字段是可选的，因为它有默认值 None。如果客户端在请求时省略了必填字段，则会收到一个 422 Unprocessable Entity 错误响应。

Python fastapi graphql

Python fastapi is a modern, fast (high-performance) web framework for building APIs with Python 3.6+ based on standard Python type hints. Fastapi provides a built-in support for GraphQL via the `graphene` library.

GraphQL is a query language for APIs that provides a more efficient, powerful and flexible alternative to REST. With GraphQL, clients can specify exactly what they need, and they get only that information back. This reduces over-fetching and under-fetching of data, makes APIs faster and more efficient, and helps developers build better user interfaces.

To use Fastapi with GraphQL, you need to install `graphene` library and import it into your Fastapi application. Here's a simple example:

from fastapi import FastAPI
from graphene import ObjectType, String, Schema

app = FastAPI()

class Query(ObjectType):
    hello = String(name=String(default_value="World"))

    def resolve_hello(root, info, name):
        return f'Hello {name}!'

schema = Schema(query=Query)

@app.post("/graphql")
async def graphql(query: str):
    result = schema.execute(query)
    return result.data

In this example, we define a `Query` class that extends `graphene.ObjectType` and contains a single field called `hello`. The `hello` field takes an argument `name` with a default value of "World". When the `hello` field is resolved, it returns a string that says "Hello {name}!".

We then create a `Schema` object, passing in our `Query` class as the `query` argument. Finally, we define a Fastapi route that accepts a `POST` request with a GraphQL query as the `query` parameter. We execute the query using the `schema.execute()` method and return the `result.data` as the response.

This is just a simple example, but Fastapi with GraphQL provides a powerful platform for building APIs that are flexible, efficient and easy to use.