这也是我们在接下来将看到的。

在下面的例子中，你将接受任意键为 `int` 类型并且值为 `float` 类型的 `dict`：

{* ../../docs_src/body_nested_models/tutorial009_py310.py hl[7] *}

/// tip | 提示

请记住 JSON 仅支持将 `str` 作为键。

但是 Pydantic 具有自动转换数据的功能。

这意味着，即使你的 API 客户端只能将字符串作为键发送，只要这些字符串内容仅包含整数，Pydantic 就会对其进行转换并校验。

然后你接收的名为 `weights` 的 `dict` 实际上将具有 `int` 类型的键和 `float` 类型的值。

///

## 总结 { #recap }

import pytest
from fastapi import FastAPI
from fastapi.exceptions import ResponseValidationError
from fastapi.testclient import TestClient
from pydantic import BaseModel


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


app = FastAPI()


@app.get("/items/stream-invalid")
async def stream_items_invalid() -> AsyncIterable[Item]:
    yield {"name": "valid", "price": 1.0}
    yield {"name": "invalid", "price": "not-a-number"}

                            <la:message key="labels.dict_protwords_title"/>
                        </h1>
                    </div>
                    <div class="col-sm-6">
                        <ol class="breadcrumb float-sm-right">
                            <li class="breadcrumb-item"><la:link href="/admin/dict">
                                <la:message key="labels.dict_list_link"/>
                            </la:link></li>

  @Override
  void writeShort(int v);

  @Override
  void writeChar(int v);

  @Override
  void writeInt(int v);

  @Override
  void writeLong(long v);

  @Override
  void writeFloat(float v);

  @Override
  void writeDouble(double v);

  @Override
  void writeChars(String s);

  @Override
  void writeUTF(String s);

  /**

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


@app.post("/items/", response_model=ResponseMessage, tags=["items"])
async def create_item(item: Item):
    return {"message": "Item received"}

Python has support for optional "type hints" (also called "type annotations").

These **"type hints"** or annotations are a special syntax that allow declaring the <dfn title="for example: str, int, float, bool">type</dfn> of a variable.

By declaring types for your variables, editors and tools can give you better support.

from fastapi import FastAPI, Header
from fastapi.sse import EventSourceResponse, ServerSentEvent
from pydantic import BaseModel

app = FastAPI()


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


items = [
    Item(name="Plumbus", price=32.99),
    Item(name="Portal Gun", price=999.99),
    Item(name="Meeseeks Box", price=49.99),
]


@app.get("/items/stream", response_class=EventSourceResponse)

     *
     * <p>It is strongly encouraged to use {@link #add(String, float)} instead and give value a
     * readable name.
     *
     * @since 18.0 (since 11.0 as {@code Objects.ToStringHelper.addValue}).
     */
    @CanIgnoreReturnValue
    public ToStringHelper addValue(float value) {
      return addUnconditionalHolder(String.valueOf(value));
    }

    /**

 */
public class SuggestQueryBuilder {

    private final ReadingConverter readingConverter;
    private final Normalizer normalizer;
    private final List<String> languages;
    private final float prefixMatchWeight;

    /**
     * Constructs a new SuggestQueryBuilder.
     *
     * @param readingConverter The reading converter.
     * @param normalizer The normalizer.

    @Max(value = 2147483647)
    @ValidateTypeFailure
    public Integer maxSize;

    /**
     * The boost score for matched results.
     */
    @Required
    @ValidateTypeFailure
    public Float boost;

    /**
     * The virtual host for the key match.
     */
    @Size(max = 1000)
    public String virtualHost;

    /**
     * The user who created this key match.
     */
    @Size(max = 255)