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  1. docs/bucket/versioning/DESIGN.md

    | ...header_n     | msgp bin array              | Header of last version
    | ...metadata_n   | msgp bin array              | Metadata of last version
    
    Each header contains a mspg array (tuple) encoded object:
    
    xlHeaderVersion version == 1:
    
    ```
    //msgp:tuple xlMetaV2VersionHeader
    type xlMetaV2VersionHeader struct {
     VersionID [16]byte  // Version UUID, raw.
    Registered: Sun Sep 07 19:28:11 UTC 2025
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  2. docs/pt/docs/tutorial/extra-data-types.md

        * O `Decimal` padrão do Python.
        * Em requisições e respostas será representado como um `float`.
    * Você pode checar todos os tipos de dados válidos do Pydantic aqui: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Tipos de dados do Pydantic</a>.
    
    ## Exemplo
    
    Aqui está um exemplo de *operação de rota* com parâmetros utilizando-se de alguns dos tipos acima.
    
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  3. docs/ru/docs/tutorial/extra-data-types.md

    * `Decimal`:
        * Встроенный в Python `Decimal`.
        * В запросах и ответах обрабатывается так же, как и `float`.
    * Вы можете проверить все допустимые типы данных pydantic здесь: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Типы данных Pydantic</a>.
    
    ## Пример
    
    Вот пример *операции пути* с параметрами, который демонстрирует некоторые из вышеперечисленных типов.
    
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  4. docs/em/docs/tutorial/extra-data-types.md

        * 🏗 🔗 🔜 ✔ 👈 ⚫️ `str` ⏮️ `binary` "📁".
    * `Decimal`:
        * 🐩 🐍 `Decimal`.
        * 📨 &amp; 📨, 🍵 🎏 `float`.
    * 👆 💪 ✅ 🌐 ☑ Pydantic 📊 🆎 📥: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic 📊 🆎</a>.
    
    ## 🖼
    
    📥 🖼 *➡ 🛠️* ⏮️ 🔢 ⚙️ 🔛 🆎.
    
    {* ../../docs_src/extra_data_types/tutorial001.py hl[1,3,12:16] *}
    
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  5. docs/ja/docs/tutorial/extra-data-types.md

    * `Decimal`:
        * Pythonの標準的な`Decimal`です。
        * リクエストやレスポンスでは`float`と同じように扱います。
    
    * Pydanticの全ての有効な型はこちらで確認できます: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic data types</a>。
    ## 例
    
    ここでは、上記の型のいくつかを使用したパラメータを持つ*path operation*の例を示します。
    
    {* ../../docs_src/extra_data_types/tutorial001.py hl[1,2,12:16] *}
    
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  6. docs/ko/docs/tutorial/extra-data-types.md

        * 생성된 스키마는 이것이 `binary` "형식"의 `str`임을 명시합니다.
    * `Decimal`:
        * 표준 파이썬의 `Decimal`.
        * 요청과 응답에서 `float`와 동일하게 다뤄집니다.
    * 여기에서 모든 유효한 pydantic 데이터 자료형을 확인할 수 있습니다: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic 데이터 자료형</a>.
    
    ## 예시
    
    위의 몇몇 자료형을 매개변수로 사용하는 *경로 작동* 예시입니다.
    
    {* ../../docs_src/extra_data_types/tutorial001_an_py310.py hl[1,3,12:16] *}
    
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  7. dbflute_fess/dfprop/classificationDeploymentMap.dfprop

    # classificationDeploymentMap: (NotRequired - Default map:{})
    #
    # The relation between column and classification.
    #
    # This property uses classification names of classificationDefinitionMap.
    # The table name '$$ALL$$' means all tables are target.
    # The table names and column names are treated as case insensitive.
    #
    # You don't need specify here about table classifications.
    # Because table classifications are auto-deployed by relation information.
    #
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  8. docs/fr/docs/deployment/https.md

    * Pour le HTTPS, le serveur a besoin de "certificats" générés par une tierce partie.
        * Ces certificats sont en fait acquis auprès de la tierce partie, et non "générés".
    * Les certificats ont une durée de vie.
        * Ils expirent.
        * Puis ils doivent être renouvelés et acquis à nouveau auprès de la tierce partie.
    * Le cryptage de la connexion se fait au niveau du protocole TCP.
        * C'est une couche en dessous de HTTP.
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  9. docs/en/docs/tutorial/extra-data-types.md

    Up to now, you have been using common data types, like:
    
    * `int`
    * `float`
    * `str`
    * `bool`
    
    But you can also use more complex data types.
    
    And you will still have the same features as seen up to now:
    
    * Great editor support.
    * Data conversion from incoming requests.
    * Data conversion for response data.
    * Data validation.
    * Automatic annotation and documentation.
    
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  10. docs/es/docs/tutorial/extra-data-types.md

    * `Decimal`:
        * `Decimal` estándar de Python.
        * En requests y responses, manejado igual que un `float`.
    * Puedes revisar todos los tipos de datos válidos de Pydantic aquí: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Tipos de datos de Pydantic</a>.
    
    ## Ejemplo
    
    Aquí tienes un ejemplo de una *path operation* con parámetros usando algunos de los tipos anteriores.
    
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