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  1. docs/en/docs/tutorial/middleware.md

    And also after the `response` is generated, before returning it.
    
    For example, you could add a custom header `X-Process-Time` containing the time in seconds that it took to process the request and generate a response:
    
    ```Python hl_lines="10  12-13"
    {!../../../docs_src/middleware/tutorial001.py!}
    ```
    
    ## Other middlewares
    
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  2. docs/en/docs/tutorial/extra-data-types.md

    * `datetime.timedelta`:
        * A Python `datetime.timedelta`.
        * In requests and responses will be represented as a `float` of total seconds.
        * Pydantic also allows representing it as a "ISO 8601 time diff encoding", <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">see the docs for more info</a>.
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  3. docs/en/docs/how-to/sql-databases-peewee.md

    Then, for the request in the next tab, your app will wait for one second less, and so on.
    
    This means that it will end up finishing some of the last tabs' requests earlier than some of the previous ones.
    
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  4. docs/en/docs/tutorial/cors.md

    * `expose_headers` - Indicate any response headers that should be made accessible to the browser. Defaults to `[]`.
    * `max_age` - Sets a maximum time in seconds for browsers to cache CORS responses. Defaults to `600`.
    
    The middleware responds to two particular types of HTTP request...
    
    ### CORS preflight requests
    
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  5. docs/fr/docs/advanced/additional-responses.md

    ```Python
    old_dict = {
        "old key": "old value",
        "second old key": "second old value",
    }
    new_dict = {**old_dict, "new key": "new value"}
    ```
    
    Ici, `new_dict` contiendra toutes les paires clé-valeur de `old_dict` plus la nouvelle paire clé-valeur :
    
    ```Python
    {
        "old key": "old value",
        "second old key": "second old value",
        "new key": "new value",
    }
    ```
    
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  6. docs/vi/docs/features.md

    ```Python
    my_user: User = User(id=3, name="John Doe", joined="2018-07-19")
    
    second_user_data = {
        "id": 4,
        "name": "Mary",
        "joined": "2018-11-30",
    }
    
    my_second_user: User = User(**second_user_data)
    ```
    
    !!! info
        `**second_user_data` nghĩa là:
    
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  7. docs/fr/docs/tutorial/query-params-str-validations.md

    Cela va valider les données, montrer une erreur claire si ces dernières ne sont pas valides, et documenter le paramètre dans le schéma `OpenAPI` de cette *path operation*.
    
    ## Rajouter plus de validation
    
    Vous pouvez aussi rajouter un second paramètre `min_length` :
    
    ```Python hl_lines="9"
    {!../../../docs_src/query_params_str_validations/tutorial003.py!}
    ```
    
    ## Ajouter des validations par expressions régulières
    
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  8. docs/fr/docs/tutorial/path-params.md

    Quand vous créez des *fonctions de chemins*, vous pouvez vous retrouver dans une situation où vous avez un chemin fixe.
    
    Tel que `/users/me`, disons pour récupérer les données sur l'utilisateur actuel.
    
    Et vous avez un second chemin : `/users/{user_id}` pour récupérer de la donnée sur un utilisateur spécifique grâce à son identifiant d'utilisateur
    
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  9. docs/en/docs/tutorial/background-tasks.md

    This includes, for example:
    
    * Email notifications sent after performing an action:
        * As connecting to an email server and sending an email tends to be "slow" (several seconds), you can return the response right away and send the email notification in the background.
    * Processing data:
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  10. docs/de/docs/features.md

    ```Python
    my_user: User = User(id=3, name="John Doe", joined="2018-07-19")
    
    second_user_data = {
        "id": 4,
        "name": "Mary",
        "joined": "2018-11-30",
    }
    
    my_second_user: User = User(**second_user_data)
    ```
    
    !!! info
        `**second_user_data` bedeutet:
    
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