* Farklı bir syntax öğrenmenize gerek kalmaz,
    * Eğer Python typelarını nasıl kullanacağını biliyorsan Pydantic kullanmayı da biliyorsundur.
* Kullandığın geliştirme araçları ile iyi çalışır **<abbr title="Integrated Development Environment, kod editörüne benzer">IDE</abbr>/<abbr title="Code errorlarınızı inceleyen program">linter</abbr>/brain**:

            intentionally vague and interpretable. It normally refers to permissions,
            in cases to roles.

            These scopes are integrated with OpenAPI (and the API docs at `/docs`).
            So they are visible in the OpenAPI specification.
            )
            """
        ),
    ] = None,
    use_cache: Annotated[
        bool,

/// tip

We are using an invented header to simplify this example.

But in real cases you will get better results using the integrated [Security utilities](security/index.md){.internal-link target=_blank}.

///

## Another module with `APIRouter` { #another-module-with-apirouter }

反之亦然，在很多情況下，你也可以把從資料庫中獲取的物件**直接傳給客戶端**。

通過 **FastAPI** 你可以獲得所有 **Pydantic** 的特性（FastAPI 基於 Pydantic 做了所有的資料處理）：

* **更簡單**：
    * 不需要學習新的 micro-language 來定義結構。
    * 如果你知道 Python 型別，你就知道如何使用 Pydantic。
* 和你的 **<abbr title="Integrated Development Environment，和程式碼編輯器類似">IDE</abbr>/<abbr title="一個檢查程式碼錯誤的工具">linter</abbr>/brain** 都能好好配合：
    * 因為 Pydantic 的資料結構其實就是你自己定義的類別實例，所以自動補齊、linting、mypy 以及你的直覺都能很好地在經過驗證的資料上發揮作用。
* 驗證**複雜結構**：

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.

Later, for your production application, you might want to use a database server like **PostgreSQL**.

/// tip

Up to here, everything would work as normally.

But then, when you open the integrated docs UI (the frontend), it would expect to get the OpenAPI schema at `/openapi.json`, instead of `/api/v1/openapi.json`.

This isn't even Python, NestJS is a JavaScript (TypeScript) NodeJS framework inspired by Angular.

It achieves something somewhat similar to what can be done with Flask-apispec.

It has an integrated dependency injection system, inspired by Angular 2. It requires pre-registering the "injectables" (like all the other dependency injection systems I know), so, it adds to the verbosity and code repetition.

## Opinions { #opinions }

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

## Opinions

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

    }

    @Override
    public boolean isLoading() {
      return false;
    }
  }

  // Queues

  /**
   * A custom queue for managing eviction order. Note that this is tightly integrated with {@code
   * ReferenceEntry}, upon which it relies to perform its linking.
   *
   * <p>Note that this entire implementation makes the assumption that all elements which are in the