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  1. docs/it/docs/index.md

    ---
    
    FastAPI è un web framework moderno e veloce (a prestazioni elevate) che serve a creare API con Python 3.6+ basato sulle annotazioni di tipo di Python.
    
    Le sue caratteristiche principali sono:
    
    * **Velocità**: Prestazioni molto elevate, alla pari di **NodeJS** e **Go** (grazie a Starlette e Pydantic). [Uno dei framework Python più veloci in circolazione](#performance).
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  2. docs/en/docs/benchmarks.md

    Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).
    
    The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.
    
    The hierarchy is like:
    
    * **Uvicorn**: an ASGI server
        * **Starlette**: (uses Uvicorn) a web microframework
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  3. docs/en/docs/tutorial/response-model.md

    * Add a **JSON Schema** for the response, in the OpenAPI *path operation*.
        * This will be used by the **automatic docs**.
        * It will also be used by automatic client code generation tools.
    
    But most importantly:
    
    * It will **limit and filter** the output data to what is defined in the return type.
        * This is particularly important for **security**, we'll see more of that below.
    
    ## `response_model` Parameter
    
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  4. docs/en/docs/alternatives.md

    ## Previous tools
    
    ### <a href="https://www.djangoproject.com/" class="external-link" target="_blank">Django</a>
    
    It's the most popular Python framework and is widely trusted. It is used to build systems like Instagram.
    
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  5. docs/en/docs/deployment/manually.md

    <font color="#4E9A06">INFO</font>:     Application startup complete.
    <font color="#4E9A06">INFO</font>:     Uvicorn running on <b>http://0.0.0.0:8000</b> (Press CTRL+C to quit)
    ```
    
    </div>
    
    That would work for most of the cases. 😎
    
    You could use that command for example to start your **FastAPI** app in a container, in a server, etc.
    
    ## ASGI Servers
    
    Let's go a little deeper into the details.
    
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  6. docs/en/docs/fastapi-people.md

    A round of applause to them. 👏 🙇
    
    ## FastAPI Experts
    
    These are the users that have been [helping others the most with questions in GitHub](help-fastapi.md#help-others-with-questions-in-github){.internal-link target=_blank}. 🙇
    
    They have proven to be **FastAPI Experts** by helping many others. ✨
    
    !!! tip
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  7. docs/en/docs/deployment/concepts.md

    ## Running on Startup
    
    In most cases, when you create a web API, you want it to be **always running**, uninterrupted, so that your clients can always access it. This is of course, unless you have a specific reason why you want it to run only in certain situations, but most of the time you want it constantly running and **available**.
    
    ### In a Remote Server
    
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  8. docs/hu/docs/index.md

    * A `/items/{item_id}` _útvonalnak_ még van egy opcionális, `str` típusú _query paramétere_ is, a `q`.
    
    ### Interaktív API dokumentáció
    
    Most nyisd meg a <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a> címet.
    
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  9. docs/en/docs/tutorial/security/first-steps.md

            * So, the user will have to log in again at some point later.
            * And if the token is stolen, the risk is less. It is not like a permanent key that will work forever (in most of the cases).
    * The frontend stores that token temporarily somewhere.
    * The user clicks in the frontend to go to another section of the frontend web app.
    * The frontend needs to fetch some more data from the API.
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  10. .github/actions/people/app/main.py

    
    def get_top_users(
        *,
        counter: Counter,
        authors: Dict[str, Author],
        skip_users: Container[str],
        min_count: int = 2,
    ):
        users = []
        for commenter, count in counter.most_common(50):
            if commenter in skip_users:
                continue
            if count >= min_count:
                author = authors[commenter]
                users.append(
                    {
    Python
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