FastAPI basiert auf **Pydantic** und ich habe Ihnen gezeigt, wie Sie Pydantic-Modelle verwenden können, um Requests und Responses zu deklarieren.

Aber FastAPI unterstützt auf die gleiche Weise auch die Verwendung von <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a>:

{* ../../docs_src/dataclasses/tutorial001.py hl[1,7:12,19:20] *}

Все те же правила, которые применяются к path-параметрам, также применяются и query-параметрам:

* Поддержка от редактора кода (очевидно)
* <abbr title="преобразование строки, полученной из HTTP запроса в Python данные">"Парсинг"</abbr> данных
* Проверка на соответствие данных (Валидация)
* Автоматическая документация

## Значения по умолчанию

{* ../../docs_src/custom_request_and_route/tutorial001.py hl[18:26] *}

/// note | Technische Details

Ein `Request` hat ein `request.scope`-Attribut, welches einfach ein Python-`dict` ist, welches die mit dem Request verbundenen Metadaten enthält.

Ein `Request` hat auch ein `request.receive`, welches eine Funktion ist, die den Hauptteil des Requests empfängt.

## 🔧

⤴️ 👤 💸 🕰 🔧 👩‍💻 "🛠️" 👤 💚 ✔️ 👩‍💻 (👩‍💻 ⚙️ FastAPI).

👤 💯 📚 💭 🏆 🌟 🐍 👨‍🎨: 🗒, 🆚 📟, 🎠 🧢 👨‍🎨.

🏁 <a href="https://www.jetbrains.com/research/python-developers-survey-2018/#development-tools" class="external-link" target="_blank">🐍 👩‍💻 🔬</a>, 👈 📔 🔃 8️⃣0️⃣ 💯 👩‍💻.

⚫️ ⛓ 👈 **FastAPI** 🎯 💯 ⏮️ 👨‍🎨 ⚙️ 8️⃣0️⃣ 💯 🐍 👩‍💻. &amp; 🏆 🎏 👨‍🎨 😑 👷 ➡, 🌐 🚮 💰 🔜 👷 🌖 🌐 👨‍🎨.

{* ../../docs_src/middleware/tutorial001.py hl[10,12:13] *}

/// tip | Consejo

Aquí usamos <a href="https://docs.python.org/3/library/time.html#time.perf_counter" class="external-link" target="_blank">`time.perf_counter()`</a> en lugar de `time.time()` porque puede ser más preciso para estos casos de uso. 🤓

///

## Otros middlewares

## Install `PyJWT` { #install-pyjwt }

We need to install `PyJWT` to generate and verify the JWT tokens in Python.

Make sure you create a [virtual environment](../../virtual-environments.md){.internal-link target=_blank}, activate it, and then install `pyjwt`:

<div class="termy">

```console
$ pip install pyjwt

  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

    // These XLA flags are needed to trigger XLA properly from C (more generally
    // non-Python) clients. If this API is called again with `enable` set to
    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();

{* ../../docs_src/body_updates/tutorial001.py hl[30:35] *}

`PUT` ⚙️ 📨 💽 👈 🔜 ❎ ♻ 💽.

### ⚠ 🔃 ❎

👈 ⛓ 👈 🚥 👆 💚 ℹ 🏬 `bar` ⚙️ `PUT` ⏮️ 💪 ⚗:

```Python
{
    "name": "Barz",
    "price": 3,
    "description": None,
}
```

↩️ ⚫️ 🚫 🔌 ⏪ 🏪 🔢 `"tax": 20.2`, 🔢 🏷 🔜 ✊ 🔢 💲 `"tax": 10.5`.

& 📊 🔜 🖊 ⏮️ 👈 "🆕" `tax` `10.5`.

## 🍕 ℹ ⏮️ `PATCH`

But when checking benchmarks and comparisons you should keep the following in mind.

{* ../../docs_src/events/tutorial003.py hl[1,13] *}

파이썬에서 **컨텍스트 매니저**는 `with` 문에서 사용할 수 있는 것입니다. 예를 들어, `open()`은 컨텍스트 매니저로 사용할 수 있습니다:

```Python
with open("file.txt") as file:
    file.read()
```
최근 버전의 파이썬에서는 **비동기 컨텍스트 매니저**도 있습니다. 이를 `async with`와 함께 사용합니다:

```Python
async with lifespan(app):
    await do_stuff()
```