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  1. fastapi/params.py

                max_length=max_length,
                discriminator=discriminator,
                multiple_of=multiple_of,
                allow_nan=allow_inf_nan,
                max_digits=max_digits,
                decimal_places=decimal_places,
                **extra,
            )
            if examples is not None:
                kwargs["examples"] = examples
            if regex is not None:
                warnings.warn(
    Python
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  2. fastapi/param_functions.py

            Doc(
                """
                Maximum number of allow digits for strings.
                """
            ),
        ] = _Unset,
        decimal_places: Annotated[
            Union[int, None],
            Doc(
                """
                Maximum number of decimal places allowed for numbers.
                """
            ),
        ] = _Unset,
        examples: Annotated[
            Optional[List[Any]],
            Doc(
    Python
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  3. docs/en/docs/alternatives.md

    dependencies and the dependencies are solved based on the declared types. So, it's not possible to declare more than one "component" that provides a certain type.
    
    Routes are declared in a single place, using functions declared in other places (instead of using decorators that can be placed right on top of the function that handles the endpoint). This is closer to how Django does it than to how Flask (and Starlette) does it. It separates in the code things that are relatively tightly coupled....
    Plain Text
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  4. docs/fr/docs/advanced/additional-responses.md

        Gardez à l'esprit que vous devez renvoyer directement `JSONResponse`.
    
    !!! info
        La clé `model` ne fait pas partie d'OpenAPI.
    
        **FastAPI** prendra le modèle Pydantic à partir de là, générera le `JSON Schema` et le placera au bon endroit.
    
        Le bon endroit est :
    
        * Dans la clé `content`, qui a pour valeur un autre objet JSON (`dict`) qui contient :
    Plain Text
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  5. docs/en/docs/tutorial/first-steps.md

    ```Python hl_lines="8"
    {!../../../docs_src/first_steps/tutorial001.py!}
    ```
    
    You can return a `dict`, `list`, singular values as `str`, `int`, etc.
    
    You can also return Pydantic models (you'll see more about that later).
    
    There are many other objects and models that will be automatically converted to JSON (including ORMs, etc). Try using your favorite ones, it's highly probable that they are already supported.
    
    ## Recap
    
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  6. docs/en/docs/tutorial/response-model.md

    ### Return a Response Directly
    
    The most common case would be [returning a Response directly as explained later in the advanced docs](../advanced/response-directly.md){.internal-link target=_blank}.
    
    ```Python hl_lines="8  10-11"
    {!> ../../../docs_src/response_model/tutorial003_02.py!}
    ```
    
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  7. docs/de/docs/deployment/cloud.md

    * <a href="https://docs.porter.run/language-specific-guides/fastapi" class="external-link" target="_blank">Porter</a>
    Plain Text
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  8. docs/en/docs/tutorial/security/first-steps.md

        * A "token" is just a string with some content that we can use later to verify this user.
        * Normally, a token is set to expire after some time.
            * 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).
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  9. docs/en/docs/tutorial/security/oauth2-jwt.md

        But it was updated to use Python-jose instead as it provides all the features from PyJWT plus some extras that you might need later when building integrations with other tools.
    
    ## Password hashing
    
    "Hashing" means converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.
    
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  10. docs/en/docs/how-to/async-sql-encode-databases.md

    It is compatible with:
    
    * PostgreSQL
    * MySQL
    * SQLite
    
    In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.
    
    Later, for your production application, you might want to use a database server like **PostgreSQL**.
    
    !!! tip
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