from pydantic import BaseModel

app = FastAPI()


class Image(BaseModel):
    url: str
    name: str


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()
    image: Image | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

from fastapi import FastAPI, Path
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
    q: str | None = None,
    item: Item | None = None,
):

from typing import Annotated

from fastapi import FastAPI, Path
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(
    item_id: Annotated[int, Path(title="The ID of the item to get", ge=0, le=1000)],
    q: str | None = None,
    item: Item | None = None,

    public void test_evaluate_withSpecialCharacters() {
        String template = "Price: $${price} (with ${discount}% off)";
        Map<String, Object> paramMap = new HashMap<>();
        paramMap.put("price", "100");
        paramMap.put("discount", "20");

        Object result = scriptEngine.evaluate(template, paramMap);
        assertEquals("Price: $100 (with 20% off)", result);
    }

SSE 是一種透過 HTTP 從伺服器向用戶端串流傳送資料的標準。

每個事件都是一個小型文字區塊，包含 `data`、`event`、`id` 和 `retry` 等「欄位」，並以空白行分隔。

看起來像這樣：

```
data: {"name": "Portal Gun", "price": 999.99}

data: {"name": "Plumbus", "price": 32.99}

```

SSE 常用於 AI 聊天串流、即時通知、日誌與可觀察性，以及其他由伺服器主動推送更新給用戶端的情境。

/// tip

如果你要串流二進位資料，例如影片或音訊，請參考進階指南：[串流資料](../advanced/stream-data.md)。

///

SSE는 서버에서 클라이언트로 HTTP를 통해 데이터를 스트리밍하기 위한 표준입니다.

각 이벤트는 `data`, `event`, `id`, `retry`와 같은 "필드"를 가진 작은 텍스트 블록이며, 빈 줄로 구분됩니다.

다음과 같습니다:

```
data: {"name": "Portal Gun", "price": 999.99}

data: {"name": "Plumbus", "price": 32.99}

```

SSE는 AI 채팅 스트리밍, 실시간 알림, 로그와 관측성, 그리고 서버가 클라이언트로 업데이트를 푸시하는 여러 경우에 흔히 사용됩니다.

/// tip | 팁

from fastapi import FastAPI
from pydantic import BaseModel


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


app = FastAPI()


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

from dataclasses import dataclass

from fastapi import FastAPI


@dataclass
class Item:
    name: str
    price: float
    description: str | None = None
    tax: float | None = None


app = FastAPI()


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

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/", tags=["items"])
async def read_items():
    return [{"name": "Foo", "price": 42}]


@app.get("/users/", tags=["users"])
async def read_users():
    return [{"username": "johndoe"}]


@app.get("/elements/", tags=["items"], deprecated=True)
async def read_elements():

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
    results = {"item_id": item_id, "item": item}