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  1. docs/en/docs/benchmarks.md

        * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still have the same overhead...
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  2. docs/en/docs/alternatives.md

    But as TypeScript data is not preserved after compilation to JavaScript, it cannot rely on the types to define validation, serialization and documentation at the same time. Due to this and some design decisions, to get validation, serialization and automatic schema generation, it's needed to add decorators in many places. So, it becomes quite verbose.
    
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  3. docs/zh/docs/tutorial/response-model.md

    !!! info
        你还可以使用:
    
        * `response_model_exclude_defaults=True`
        * `response_model_exclude_none=True`
    
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  4. docs/en/docs/advanced/dataclasses.md

    And of course, it supports the same:
    
    * data validation
    * data serialization
    * data documentation, etc.
    
    This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.
    
    !!! info
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  5. docs/ja/docs/tutorial/response-model.md

    !!! info "情報"
        以下も使用することができます:
    
        * `response_model_exclude_defaults=True`
        * `response_model_exclude_none=True`
    
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  6. docs/en/docs/tutorial/response-model.md

    !!! info
        You can also use:
    
        * `response_model_exclude_defaults=True`
        * `response_model_exclude_none=True`
    
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  7. docs/en/docs/tutorial/path-params.md

    ```
    
    In this case, `item_id` is declared to be an `int`.
    
    !!! check
        This will give you editor support inside of your function, with error checks, completion, etc.
    
    ## Data <abbr title="also known as: serialization, parsing, marshalling">conversion</abbr>
    
    If you run this example and open your browser at <a href="http://127.0.0.1:8000/items/3" class="external-link" target="_blank">http://127.0.0.1:8000/items/3</a>, you will see a response of:
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  8. docs/ja/docs/tutorial/extra-data-types.md

    * `datetime.timedelta`:
        * Pythonの`datetime.timedelta`です。
        * リクエストとレスポンスでは合計秒数の`float`で表現されます。
        * Pydanticでは「ISO 8601 time diff encoding」として表現することも可能です。<a href="https://docs.pydantic.dev/latest/concepts/serialization/" class="external-link" target="_blank">詳細はドキュメントを参照してください</a>。
    * `frozenset`:
        * リクエストとレスポンスでは`set`と同じように扱われます:
            * リクエストでは、リストが読み込まれ、重複を排除して`set`に変換されます。
            * レスポンスでは`set`が`list`に変換されます。
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  9. docs/pt/docs/tutorial/extra-data-types.md

        * Em requisições e respostas será representado como um `float` de segundos totais.
        * O Pydantic também permite representá-lo como uma "codificação ISO 8601 diferença de tempo", <a href="https://docs.pydantic.dev/latest/concepts/serialization/" class="external-link" target="_blank">cheque a documentação para mais informações</a>.
    * `frozenset`:
        * Em requisições e respostas, será tratado da mesma forma que um `set`:
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  10. docs/ru/docs/tutorial/extra-data-types.md

        * В запросах и ответах будет представлен в виде общего количества секунд типа `float`.
        * Pydantic также позволяет представить его как "Кодировку разницы во времени ISO 8601", <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">см. документацию для получения дополнительной информации</a>.
    * `frozenset`:
        * В запросах и ответах обрабатывается так же, как и `set`:
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