from fastapi.responses import JSONResponse
from pydantic import BaseModel


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)

from typing import Annotated, Union

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: Annotated[int, Path(title="The ID of the item to get")],
    q: Annotated[Union[str, None], Query(alias="item-query")] = None,
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

from fastapi import BackgroundTasks, FastAPI

app = FastAPI()


def write_notification(email: str, message=""):
    with open("log.txt", mode="w") as email_file:
        content = f"notification for {email}: {message}"
        email_file.write(content)


@app.post("/send-notification/{email}")
async def send_notification(email: str, background_tasks: BackgroundTasks):

from fastapi import FastAPI, Query
from pydantic import BaseModel, Field

app = FastAPI()


class FilterParams(BaseModel):
    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: list[str] = []


@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):

from fastapi import FastAPI, Query
from pydantic import BaseModel, Field

app = FastAPI()


class FilterParams(BaseModel):
    model_config = {"extra": "forbid"}

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: list[str] = []


@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):

from typing import Union

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/{item_id}")
async def read_item(item_id: str, q: Union[str, None] = None, short: bool = False):
    item = {"item_id": item_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

# 响应模型

你可以在任意的*路径操作*中使用 `response_model` 参数来声明用于响应的模型：

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* 等等。

{* ../../docs_src/response_model/tutorial001_py310.py hl[17,22,24:27] *}

/// note

注意，`response_model`是「装饰器」方法（`get`，`post` 等）的一个参数。不像之前的所有参数和请求体，它不属于*路径操作函数*。

///

它接收的类型与你将为 Pydantic 模型属性所声明的类型相同，因此它可以是一个 Pydantic 模型，但也可以是一个由 Pydantic 模型组成的 `list`，例如 `List[Item]`。

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


class User(BaseModel):
    username: str
    full_name: str | None = None


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

from fastapi import FastAPI
from pydantic.v1 import BaseModel

app = FastAPI()


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

    class Config:
        schema_extra = {
            "examples": [
                {
                    "name": "Foo",
                    "description": "A very nice Item",
                    "price": 35.4,

workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. _Netflix_, for example, developed two new staging committers - the Directory staging committer and the Partitioned staging committer - to take full...