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  1. docs/en/docs/how-to/custom-request-and-route.md

    Doing this, our `GzipRequest` will take care of decompressing the data (if necessary) before passing it to our *path operations*.
    
    After that, all of the processing logic is the same.
    
    But because of our changes in `GzipRequest.body`, the request body will be automatically decompressed when it is loaded by **FastAPI** when needed.
    
    ## Accessing the request body in an exception handler
    
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  2. .github/actions/notify-translations/app/main.py

        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:
    Python
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  3. docs/en/docs/python-types.md

    !!! 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`.
    
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  4. docs/en/docs/tutorial/sql-databases.md

        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.
    
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  5. docs/fr/docs/async.md

    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".
    
    ---
    
    Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes.
    
    Par exemple :
    
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  6. docs/ja/docs/async.md

    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。
    
    ---
    
    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**。
    Plain Text
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  7. docs/em/docs/async.md

    👉 😐, 🔠 1️⃣ 🧹 (🔌 👆) 🔜 🕹, 🤸 👫 🍕 👨‍🏭.
    
    &amp; 🏆 🛠️ 🕰 ✊ ☑ 👷 (↩️ ⌛), &amp; 👷 💻 ⌛ <abbr title="Central Processing Unit">💽</abbr>, 👫 🤙 👫 ⚠ "💽 🎁".
    
    ---
    
    ⚠ 🖼 💽 🔗 🛠️ 👜 👈 🚚 🏗 🧪 🏭.
    
    🖼:
    
    * **🎧** ⚖️ **🖼 🏭**.
    * **💻 👓**: 🖼 ✍ 💯 🔅, 🔠 🔅 ✔️ 3️⃣ 💲 / 🎨, 🏭 👈 🛎 🚚 💻 🕳 🔛 📚 🔅, 🌐 🎏 🕰.
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  8. docs/en/docs/release-notes.md

    In some cases, for pure data validation and processing, you can get performance improvements of **20x** or more. This means 2,000% or more. 🤯
    
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  9. requirements-docs.txt

    mkdocs-material==9.5.18
    mdx-include >=1.4.1,<2.0.0
    mkdocs-redirects>=1.2.1,<1.3.0
    typer >=0.12.0
    pyyaml >=5.3.1,<7.0.0
    # For Material for MkDocs, Chinese search
    jieba==0.42.1
    # For image processing by Material for MkDocs
    pillow==10.3.0
    # For image processing by Material for MkDocs
    cairosvg==2.7.0
    mkdocstrings[python]==0.24.3
    griffe-typingdoc==0.2.2
    # For griffe, it formats with black
    black==24.3.0
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  10. docs_src/sql_databases_peewee/sql_app/main.py

    )
    def read_slow_users(skip: int = 0, limit: int = 100):
        global sleep_time
        sleep_time = max(0, sleep_time - 1)
        time.sleep(sleep_time)  # Fake long processing request
        users = crud.get_users(skip=skip, limit=limit)
    Python
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