path_params=dependant.path_params.copy(),
        query_params=dependant.query_params.copy(),
        header_params=dependant.header_params.copy(),
        cookie_params=dependant.cookie_params.copy(),
        body_params=dependant.body_params.copy(),
        name=dependant.name,
        call=dependant.call,
        request_param_name=dependant.request_param_name,

def _get_openapi_operation_parameters(
    *,
    dependant: Dependant,
    model_name_map: ModelNameMap,
    field_mapping: dict[
        tuple[ModelField, Literal["validation", "serialization"]], dict[str, Any]
    ],
    separate_input_output_schemas: bool = True,
) -> list[dict[str, Any]]:
    parameters = []
    flat_dependant = get_flat_dependant(dependant, skip_repeats=True)

    return func


@dataclass
class Dependant:
    path_params: list[ModelField] = field(default_factory=list)
    query_params: list[ModelField] = field(default_factory=list)
    header_params: list[ModelField] = field(default_factory=list)
    cookie_params: list[ModelField] = field(default_factory=list)
    body_params: list[ModelField] = field(default_factory=list)
    dependencies: list["Dependant"] = field(default_factory=list)

This is quite simple (not very useful), but will help us focus on how the sub-dependencies work.

## Second dependency, "dependable" and "dependant" { #second-dependency-dependable-and-dependant }

Then you can create another dependency function (a "dependable") that at the same time declares a dependency of its own (so it is a "dependant" too):

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[13] *}

Let's focus on the parameters declared:

async def run_endpoint_function(
    *, dependant: Dependant, values: dict[str, Any], is_coroutine: bool
) -> Any:
    # Only called by get_request_handler. Has been split into its own function to
    # facilitate profiling endpoints, since inner functions are harder to profile.
    assert dependant.call is not None, "dependant.call must be a function"

    if is_coroutine:

///

### `Depends`のインポート { #import-depends }

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[3] *}

### 「dependant」での依存関係の宣言 { #declare-the-dependency-in-the-dependant }

*path operation 関数*のパラメータに`Body`や`Query`などを使用するのと同じように、新しいパラメータに`Depends`を使用することができます:

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[13,18] *}

     * address, isPermanent, isBeingDeleted, ...etc. This information can only
     * be retrieved with the Node Status request.
     *
     * The degree of state that an NbtAddress has is dependant on how it was
     * created and what is required of it. The second degree of state is the
     * most common. This is the state information that would be retrieved from

* the header
* the headers
* the authorization header
* the `Authorization` header
* the forwarded header

* the dependency injection system
* the dependency
* the dependable
* the dependant

* I/O bound
* CPU bound
* concurrency
* parallelism
* multiprocessing

* the env var
* the environment variable
* the `PATH`
* the `PATH` variable

* the authentication

* クラス
* 基底クラス
* 親クラス
* サブクラス
* 子クラス
* 兄弟クラス
* クラスメソッド

* ヘッダー
* ヘッダー（複数）
* 認可ヘッダー
* `Authorization` ヘッダー
* Forwarded ヘッダー

* 依存性注入システム
* 依存関係
* dependable
* dependant

* I/O バウンド
* CPU バウンド
* 同時実行性
* 並列性
* マルチプロセッシング

* env var
* 環境変数
* `PATH`
* `PATH` 環境変数

* 認証
* 認証プロバイダ
* 認可
* 認可フォーム
* 認可プロバイダ
* ユーザーが認証する

Це досить просто (не дуже корисно), але допоможе зосередитися на тому, як працюють підзалежності.

## Друга залежність, «dependable» і «dependant» { #second-dependency-dependable-and-dependant }

Далі ви можете створити іншу функцію залежності («dependable»), яка водночас оголошує власну залежність (тож вона також є «dependant»):

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[13] *}

Зосередьмося на оголошених параметрах: