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  1. docs/en/docs/tutorial/extra-data-types.md

    * `frozenset`:
        * In requests and responses, treated the same as a `set`:
            * In requests, a list will be read, eliminating duplicates and converting it to a `set`.
            * In responses, the `set` will be converted to a `list`.
            * The generated schema will specify that the `set` values are unique (using JSON Schema's `uniqueItems`).
    * `bytes`:
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  2. docs/en/docs/tutorial/body-nested-models.md

        ```Python hl_lines="1  14"
        {!> ../../../docs_src/body_nested_models/tutorial003.py!}
        ```
    
    With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.
    
    And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.
    
    And it will be annotated / documented accordingly too.
    
    ## Nested Models
    
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  3. docs/en/docs/advanced/generate-clients.md

    ### Preprocess the OpenAPI Specification for the Client Generator
    
    The generated code still has some **duplicated information**.
    
    We already know that this method is related to the **items** because that word is in the `ItemsService` (taken from the tag), but we still have the tag name prefixed in the method name too. 😕
    
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  4. docs/de/docs/tutorial/body-nested-models.md

        ```
    
    Jetzt, selbst wenn Sie einen Request mit duplizierten Daten erhalten, werden diese zu einem Set eindeutiger Dinge konvertiert.
    
    Und wann immer Sie diese Daten ausgeben, selbst wenn die Quelle Duplikate hatte, wird es als Set von eindeutigen Dingen ausgegeben.
    
    Und es wird entsprechend annotiert/dokumentiert.
    
    ## Verschachtelte Modelle
    
    Jedes Attribut eines Pydantic-Modells hat einen Typ.
    
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  5. docs/en/docs/deployment/concepts.md

    will have to make sure that it's a single process running those previous steps *even* if afterwards, you start **multiple processes** (multiple workers) for the application itself. If those steps were run by **multiple processes**, they would **duplicate** the work by running it on **parallel**, and if the steps were something delicate like a database migration, they could cause conflicts with each other.
    
    Of course, there are some cases where there's no problem in running the previous...
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  6. docs/en/docs/release-notes.md

    ## 0.9.1
    
    * Document receiving [Multiple values with the same query parameter](https://fastapi.tiangolo.com/tutorial/query-params-str-validations/#query-parameter-list-multiple-values) and [Duplicate headers](https://fastapi.tiangolo.com/tutorial/header-params/#duplicate-headers). PR [#95](https://github.com/tiangolo/fastapi/pull/95).
    
    ## 0.9.0
    
    * Upgrade compatible Pydantic version to `0.21.0`. PR [#90](https://github.com/tiangolo/fastapi/pull/90).
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  7. docs/pt/docs/tutorial/extra-data-types.md

    * `frozenset`:
        * Em requisições e respostas, será tratado da mesma forma que um `set`:
            * Nas requisições, uma lista será lida, eliminando duplicadas e convertendo-a em um `set`.
            * Nas respostas, o `set` será convertido para uma `list`.
            * O esquema gerado vai especificar que os valores do `set` são unicos (usando o `uniqueItems` do JSON Schema).
    * `bytes`:
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  8. docs/pt/docs/tutorial/body-nested-models.md

    ```Python hl_lines="1  14"
    {!../../../docs_src/body_nested_models/tutorial003.py!}
    ```
    
    Com isso, mesmo que você receba uma requisição contendo dados duplicados, ela será convertida em um conjunto de itens exclusivos.
    
    E sempre que você enviar esses dados como resposta, mesmo se a fonte tiver duplicatas, eles serão gerados como um conjunto de itens exclusivos.
    
    E também teremos anotações/documentação em conformidade.
    
    ## Modelos aninhados
    
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  9. docs/en/docs/tutorial/header-params.md

    ## Duplicate headers
    
    It is possible to receive duplicate headers. That means, the same header with multiple values.
    
    You can define those cases using a list in the type declaration.
    
    You will receive all the values from the duplicate header as a Python `list`.
    
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  10. docs/pt/docs/tutorial/header-params.md

    !!! warning "Aviso"
        Antes de definir `convert_underscores` como `False`, lembre-se de que alguns proxies e servidores HTTP não permitem o uso de cabeçalhos com sublinhados.
    
    ## Cabeçalhos duplicados
    
    É possível receber cabeçalhos duplicados. Isso significa, o mesmo cabeçalho com vários valores.
    
    Você pode definir esses casos usando uma lista na declaração de tipo.
    
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