* example is when a server has just booted, and it is mostly busy with getting itself up to
   * speed).
   *
   * To deal with such scenarios, we add an extra dimension, that of "past underutilization",
   * modeled by "storedPermits" variable. This variable is zero when there is no underutilization,
   * and it can grow up to maxStoredPermits, for sufficiently large underutilization. So, the

* 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 [Strawberry](https://strawberry.rocks) und anderen Bibliotheken.
* Viele zusätzliche Features (dank Starlette) wie:
    * **WebSockets**

<img src="/img/python-types/image06.png">

これは「`one_person` はクラス `Person` の **インスタンス** である」ことを意味します。

「`one_person` は `Person` という名前の **クラス** である」という意味ではありません。

## Pydantic のモデル { #pydantic-models }

[Pydantic](https://docs.pydantic.dev/) はデータ検証を行うための Python ライブラリです。

データの「形」を属性付きのクラスとして宣言します。

そして、それぞれの属性は型を持ちます。

さらに、いくつかの値を持つクラスのインスタンスを作成すると、その値を検証し、適切な型に変換して（もしそうであれば）すべてのデータを持つオブジェクトを提供してくれます。

//
//	// 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{})

        "//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/...",

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

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).

### Concorrência + Paralelismo: Web + Aprendizado de Máquina { #concurrency-parallelism-web-machine-learning }

			}
		},
	}
	session := DB.Session(&gorm.Session{Logger: tracer})

	DB.Migrator().DropTable(model1)
	var modifySql []string
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	if err := session.AutoMigrate(model1); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}
	tracer2 := Tracer{

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