logging.info(
        f"Sleeping for {sleep_time} seconds to avoid "
        "race conditions and multiple comments"
    )
    time.sleep(sleep_time)

    # Get PR
    logging.debug(f"Processing PR: #{github_event.pull_request.number}")
    pr = repo.get_pull(github_event.pull_request.number)
    label_strs = {label.name for label in pr.get_labels()}
    langs = []
    for label in label_strs:

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.

!!! tip
    If you use Python 3.9 or above, you don't have to import `List` from `typing`, you can use the same regular `list` type instead.

By doing that, your editor can provide support even while processing items from the list:

<img src="/img/python-types/image05.png">

Without types, that's almost impossible to achieve.

Notice that the variable `item` is one of the elements in the list `items`.

Et comme la plupart du temps d'exécution est pris par du "vrai" travail (et non de l'attente), et que le travail dans un ordinateur est fait par un <abbr title="Central Processing Unit">CPU</abbr>, ce sont des problèmes dits "CPU bound".

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Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes.

Par exemple :

このシナリオでは、清掃員 (あなたを含む) のそれぞれがプロセッサとなり、それぞれの役割を果たします。

また、実行時間のほとんどは (待機ではなく) 実際の作業に費やされ、コンピュータでの作業は<abbr title="Central Processing Unit">CPU</abbr>によって行われます。これらの問題は「CPUバウンド」と言います。

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CPUバウンド操作の一般的な例は、複雑な数学処理が必要なものです。

例えば:

* **オーディオ** や **画像処理**。

!!! tip
    As FastAPI is an async framework, one request could start being processed, and before finishing, another request could be received and start processing as well, and it all could be processed in the same thread.

That way, you don't have to read it all first in memory, and you can pass that generator function to the `StreamingResponse`, and return it.

This includes many libraries to interact with cloud storage, video processing, and others.

```{ .python .annotate hl_lines="2  10-12  14" }
{!../../../docs_src/custom_response/tutorial008.py!}
```

Bu senaryoda, temizlikçilerin her biri (siz dahil) birer işlemci olacak ve üzerine düşeni yapacaktır.

Yürütme süresinin çoğu (beklemek yerine) iş yapıldığından ve bilgisayardaki iş bir <abbr title="Central Processing Unit">CPU</abbr> tarafından yapıldığından, bu sorunlara "CPU bound" diyorlar".

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CPU'ya bağlı işlemlerin yaygın örnekleri, karmaşık matematik işlemleri gerektiren işlerdir.

Örneğin:

    And then we close it in the `finally` block.

    This way we make sure the database session is always closed after the request. Even if there was an exception while processing the request.

Und da die meiste Ausführungszeit durch tatsächliche Arbeit (anstatt durch Warten) in Anspruch genommen wird und die Arbeit in einem Computer von einer <abbr title="Central Processing Unit – Zentrale Recheneinheit">CPU</abbr> erledigt wird, werden diese Probleme als „CPU-lastig“ („CPU bound“) bezeichnet.

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