This interaction pattern causes significant loss of performance because of the write amplification. _Netflix_, for example, developed two new staging committers - the Directory staging committer and the Partitioned staging committer - to take full advantage of native object storage operations. These committers do not require rename operation. The two staging committers were evaluated, along with another new addition called the Magic committer for benchmarking.

It was found that the directory...

```Python
q: Annotated[str, Query()] = "rick"
```

... oder in älteren Codebasen finden Sie:

```Python
q: str = Query(default="rick")
```

### Vorzüge von `Annotated` { #advantages-of-annotated }

**Es wird empfohlen, `Annotated` zu verwenden**, anstelle des Defaultwertes in Funktionsparametern, es ist aus mehreren Gründen **besser**. 🤓

```Python
q: Annotated[str, Query()] = "rick"
```

...o en code bases más antiguas encontrarás:

```Python
q: str = Query(default="rick")
```

### Ventajas de `Annotated` { #advantages-of-annotated }

Usar `Annotated` es recomendado en lugar del valor por defecto en los parámetros de función, es mejor por múltiples razones. 🤓

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

And in those cases, we can use classes and inheritance to take advantage of function **type annotations** to get better support in the editor and tools, and still get the FastAPI **data filtering**.

{* ../../docs_src/response_model/tutorial003_01_py310.py hl[7:10,13:14,18] *}

For active-active replication, automatic failover occurs on `GET/HEAD` operations if object or object version requested qualifies for replication and is missing on one site, but present on the other. This allows the applications to take full advantage of two-way replication even before the two sites get fully synced.

Also note that `mc` version `RELEASE.2021-09-02T09-21-27Z` or older supports only a single remote target per bucket. To take advantage of multiple destination replication, use the latest version of `mc`

Et la fonction de dépendance `get_current_active_user` peut également déclarer des sous-dépendances, non seulement avec `Depends` mais aussi avec `Security`. En déclarant sa propre fonction de sous-dépendance (`get_current_user`), et davantage d’exigences de scopes.

Dans ce cas, elle nécessite le scope `me` (elle pourrait en exiger plusieurs).

/// note | Remarque

따라서 (가능하면) 다음과 같이 사용합니다:

```Python
q: Annotated[str, Query()] = "rick"
```

...또는 오래된 코드베이스에서는 다음과 같은 코드를 찾게 될 것입니다:

```Python
q: str = Query(default="rick")
```

### `Annotated`의 장점 { #advantages-of-annotated }

함수 매개변수의 기본값 방식 대신 **`Annotated`를 사용하는 것을 권장**합니다. 여러 이유로 **더 좋기** 때문입니다. 🤓

**함수 매개변수**의 **기본값**이 **실제 기본값**이 되므로, 전반적으로 Python에 더 직관적입니다. 😌

 * appropriate {@code copyOf} method itself.
 *
 * <p>Expressing the immutability guarantee directly in the type that user code references is a
 * powerful advantage. Although Java offers certain immutable collection factory methods, such as
 * {@link Collections#singleton(Object)} and <a
 * href="https://docs.oracle.com/en/java/javase/25/docs/api/java.base/java/util/Set.html#unmodifiable">{@code

因此，你应该这样用（推荐）：

```Python
q: Annotated[str, Query()] = "rick"
```

...或者在旧代码库中你会见到：

```Python
q: str = Query(default="rick")
```

### `Annotated` 的优势 { #advantages-of-annotated }

**推荐使用 `Annotated`**，而不是把 `Query` 放在函数参数的默认值里，这样做在多方面都**更好**。🤓

函数参数的**默认值**就是**真正的默认值**，这与 Python 的直觉更一致。😌