import importlib

import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient


@pytest.fixture(
    name="app",
    params=[
        "tutorial001_py39",
        "tutorial001_an_py39",
    ],
)
def get_app(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.request_forms_and_files.{request.param}")

    return mod.app


@pytest.fixture(name="client")

from functools import partial
from typing import Optional

from fastapi import FastAPI
from fastapi.testclient import TestClient


def main(some_arg, q: Optional[str] = None):
    return {"some_arg": some_arg, "q": q}


endpoint = partial(main, "foo")

app = FastAPI()

app.get("/")(endpoint)


client = TestClient(app)


def test_partial():
    response = client.get("/?q=bar")
    data = response.json()

from fastapi.testclient import TestClient

from docs_src.path_operation_advanced_configuration.tutorial006_py39 import app

client = TestClient(app)


def test_post():
    response = client.post("/items/", content=b"this is actually not validated")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "size": 30,
        "content": {
            "name": "Maaaagic",
            "price": 42,

В некоторых случаях может потребоваться преобразование типа данных (например, Pydantic-модели) в тип, совместимый с JSON (например, `dict`, `list` и т.д.).

Например, если необходимо хранить его в базе данных.

Для этого **FastAPI** предоставляет функцию `jsonable_encoder()`.

## Использование `jsonable_encoder` { #using-the-jsonable-encoder }

Представим, что у вас есть база данных `fake_db`, которая принимает только JSON-совместимые данные.

from typing import Union

import pytest
from fastapi import Body, Cookie, FastAPI, Header, Path, Query
from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.testclient import TestClient
from pydantic import BaseModel, ConfigDict


def create_app():
    app = FastAPI()

    class Item(BaseModel):
        data: str

        model_config = ConfigDict(

from typing import Annotated

import pytest
from dirty_equals import IsOneOf
from fastapi import FastAPI, Query
from fastapi.testclient import TestClient
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/required-list-str")
async def read_required_list_str(p: Annotated[list[str], Query()]):
    return {"p": p}

from fastapi import FastAPI
from fastapi.responses import FileResponse
from pydantic import BaseModel


class Item(BaseModel):
    id: str
    value: str


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={
        200: {
            "content": {"image/png": {}},
            "description": "Return the JSON item or an image.",
        }
    },
)

Isso é possível desde a versão `0.115.0` do FastAPI. 🤓

///

## Parâmetros do Cabeçalho com um Modelo Pydantic { #header-parameters-with-a-pydantic-model }

Declare os **parâmetros de cabeçalho** que você precisa em um **modelo do Pydantic**, e então declare o parâmetro como `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

/// note | Nota

Esto es compatible desde la versión `0.115.0` de FastAPI. 🤓

///

## Parámetros de Header con un Modelo Pydantic { #header-parameters-with-a-pydantic-model }

Declara los **parámetros de header** que necesitas en un **modelo Pydantic**, y luego declara el parámetro como `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

这里说的不是类本身（类本就是可调用项），而是类实例。

为此，需要声明 `__call__` 方法：

{* ../../docs_src/dependencies/tutorial011.py hl[10] *}

本例中，**FastAPI**  使用 `__call__` 检查附加参数及子依赖项，稍后，还要调用它向*路径操作函数*传递值。

## 参数化实例

接下来，使用 `__init__` 声明用于**参数化**依赖项的实例参数：

{* ../../docs_src/dependencies/tutorial011.py hl[7] *}

本例中，**FastAPI** 不使用 `__init__`，我们要直接在代码中使用。

## 创建实例

使用以下代码创建类实例：

{* ../../docs_src/dependencies/tutorial011.py hl[16] *}