Se sua aplicação for **simples**, isso provavelmente **não será um problema**, e você pode não precisar especificar limites de memória rígidos. Mas se você estiver **usando muita memória** (por exemplo, com **modelos de aprendizado de máquina**), deve verificar quanta memória está consumindo e ajustar o **número de contêineres** que executa em **cada máquina** (e talvez adicionar mais máquinas ao seu cluster).

* Sicherheit und Authentifizierung, einschließlich Unterstützung für **OAuth2** mit **JWT-Tokens** und **HTTP-Basic**-Authentifizierung.
* Fortgeschrittenere (aber ebenso einfache) Techniken zur Deklaration **tief verschachtelter JSON-Modelle** (dank Pydantic).
* **GraphQL** Integration mit <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> und anderen Bibliotheken.
* Viele zusätzliche Funktionen (dank Starlette) wie:

    * Przetwarzanie Pythonowych typów (`str`, `int`, `float`, `bool`, `list`, itp).
    * Obiekty `datetime`.
    * Obiekty `UUID`.
    * Modele baz danych.
    * ...i wiele więcej.
* Automatyczne interaktywne dokumentacje API, wliczając 2 alternatywne interfejsy użytkownika:
    * Swagger UI.
    * ReDoc.

---

//
//	// CREATE VIEW `user_view` AS SELECT * FROM `users` WHERE age > 20
//	q := DB.Model(&User{}).Where("age > ?", 20)
//	DB.Debug().Migrator().CreateView("user_view", gorm.ViewOption{Query: q})
//
//	// CREATE OR REPLACE VIEW `users_view` AS SELECT * FROM `users` WITH CHECK OPTION
//	q := DB.Model(&User{})

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented and validated.

/// check | Inspired **FastAPI** to

        "//third_party/py/tf_keras/...",
        "//third_party/yggdrasil_decision_forests/...",
        "//waymo/accelerator/...",
        "//waymo/ml/cn/...",
        "//waymo/ml/models/...",
    ],
)

package_group(
    name = "ndarray_tensor_allow_list",
    packages = [
        "//learning/gemini/gemax/...",
        "//third_party/py/courier/...",

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

If your application is **simple**, this will probably **not be a problem**, and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more machines to your cluster).

Hepsi sadece **Python** standartlarına dayalıdır.

Örnek olarak, `int` tanımlamak için:

```Python
item_id: int
```

ya da daha kompleks herhangi bir python modelini tanımlayabiliriz, örneğin `Item` modeli için:

```Python
item: Item
```

...ve sadece kısa bir parametre tipi belirterek elde ettiklerimiz:

* Editör desteğiyle birlikte:
    * Otomatik tamamlama.
    * Tip kontrolü.

### Concurrence + Parallélisme : Web + Machine Learning

Avec **FastAPI** vous pouvez bénéficier de la concurrence qui est très courante en développement web (c'est l'attrait principal de NodeJS).