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Results 271 - 280 of 396 for pydantic (3.82 sec)

  1. docs/pt/docs/tutorial/testing.md

    /// info | Informação
    
    Observe que o `TestClient` recebe dados que podem ser convertidos para JSON, não para modelos Pydantic.
    
    Se você tiver um modelo Pydantic em seu teste e quiser enviar seus dados para o aplicativo durante o teste, poderá usar o `jsonable_encoder` descrito em [Codificador compatível com JSON](encoder.md){.internal-link target=_blank}.
    
    ///
    
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  2. docs/em/docs/advanced/security/oauth2-scopes.md

    ## ✔ `username` & 💽 💠
    
    👥 ✔ 👈 👥 🤚 `username`, & ⚗ ↔.
    
    & ⤴️ 👥 ✔ 👈 📊 ⏮️ Pydantic 🏷 (✊ `ValidationError` ⚠), & 🚥 👥 🤚 ❌ 👂 🥙 🤝 ⚖️ ⚖ 📊 ⏮️ Pydantic, 👥 🤚 `HTTPException` 👥 ✍ ⏭.
    
    👈, 👥 ℹ Pydantic 🏷 `TokenData` ⏮️ 🆕 🏠 `scopes`.
    
    ⚖ 📊 ⏮️ Pydantic 👥 💪 ⚒ 💭 👈 👥 ✔️, 🖼, ⚫️❔ `list` `str` ⏮️ ↔ & `str` ⏮️ `username`.
    
    ↩️, 🖼, `dict`, ⚖️ 🕳 🙆, ⚫️ 💪 💔 🈸 ☝ ⏪, ⚒ ⚫️ 💂‍♂ ⚠.
    
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  3. docs/en/docs/tutorial/handling-errors.md

    ///
    
    `RequestValidationError` is a sub-class of Pydantic's <a href="https://docs.pydantic.dev/latest/concepts/models/#error-handling" class="external-link" target="_blank">`ValidationError`</a>.
    
    **FastAPI** uses it so that, if you use a Pydantic model in `response_model`, and your data has an error, you will see the error in your log.
    
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  4. docs/de/docs/tutorial/query-params-str-validations.md

    ### Pydantic v1 `regex` statt `pattern`
    
    Vor Pydantic Version 2 und vor FastAPI Version 0.100.0, war der Name des Parameters `regex` statt `pattern`, aber das ist jetzt <abbr title="deprecated – obsolet, veraltet: Es soll nicht mehr verwendet werden">deprecated</abbr>.
    
    Sie könnten immer noch Code sehen, der den alten Namen verwendet:
    
    //// tab | Pydantic v1
    
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  5. docs/en/docs/how-to/conditional-openapi.md

    If you want to secure your API, there are several better things you can do, for example:
    
    * Make sure you have well defined Pydantic models for your request bodies and responses.
    * Configure any required permissions and roles using dependencies.
    * Never store plaintext passwords, only password hashes.
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  6. docs/fa/docs/index.md

    FastAPI مبتنی بر ابزارهای قدرتمند زیر است:
    
    * فریم‌ورک <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> برای بخش وب.
    * کتابخانه <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> برای بخش داده‌.
    
    ## نصب
    
    <div class="termy">
    
    ```console
    $ pip install fastapi
    
    ---> 100%
    ```
    
    </div>
    
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  7. docs/bn/docs/index.md

    Python 3.7+
    
    FastAPI কিছু দানবেদের কাঁধে দাঁড়িয়ে আছে:
    
    - <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> ওয়েব অংশের জন্য.
    - <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> ডেটা অংশগুলির জন্য.
    
    ## ইনস্টলেশন প্রক্রিয়া
    
    <div class="termy">
    
    ```console
    $ pip install fastapi
    
    ---> 100%
    ```
    
    </div>
    
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  8. docs/ja/docs/python-types.md

    ## Pydanticのモデル
    
    <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> はデータ検証を行うためのPythonライブラリです。
    
    データの「形」を属性付きのクラスとして宣言します。
    
    そして、それぞれの属性は型を持ちます。
    
    さらに、いくつかの値を持つクラスのインスタンスを作成すると、その値を検証し、適切な型に変換して(もしそうであれば)全てのデータを持つオブジェクトを提供してくれます。
    
    また、その結果のオブジェクトですべてのエディタのサポートを受けることができます。
    
    Pydanticの公式ドキュメントから引用:
    
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  9. docs/es/docs/advanced/using-request-directly.md

    Aunque cualquier otro parámetro declarado normalmente (por ejemplo, el cuerpo con un modelo de Pydantic) seguiría siendo validado, convertido, anotado, etc.
    
    Pero hay casos específicos donde es útil obtener el objeto `Request`.
    
    ## Usa el objeto `Request` directamente
    
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  10. docs/ko/docs/tutorial/sql-databases.md

    `SQLModel`을 가져오고 데이터베이스 모델을 생성합니다:
    
    {* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}
    
    `Hero` 클래스는 Pydantic 모델과 매우 유사합니다 (실제로 내부적으로 *Pydantic 모델이기도 합니다*).
    
    몇 가지 차이점이 있습니다:
    
    * `table=True`는 SQLModel에 이 모델이 *테이블 모델*이며, 단순한 데이터 모델이 아니라 SQL 데이터베이스의 **테이블**을 나타낸다는 것을 알려줍니다. (다른 일반적인 Pydantic 클래스처럼) 단순한 *데이터 모델*이 아닙니다.
    
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