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  1. docs/en/docs/deployment/concepts.md

    ### Small Errors Automatically Handled
    
    When building web APIs with FastAPI, if there's an error in our code, FastAPI will normally contain it to the single request that triggered the error. đŸ›¡
    
    The client will get a **500 Internal Server Error** for that request, but the application will continue working for the next requests instead of just crashing completely.
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  2. pyproject.toml

    ]
    context = '${CONTEXT}'
    omit = [
        "docs_src/response_model/tutorial003_04.py",
        "docs_src/response_model/tutorial003_04_py310.py",
    ]
    
    [tool.ruff.lint]
    select = [
        "E",  # pycodestyle errors
        "W",  # pycodestyle warnings
        "F",  # pyflakes
        "I",  # isort
        "B",  # flake8-bugbear
        "C4",  # flake8-comprehensions
        "UP",  # pyupgrade
    ]
    ignore = [
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  3. docs/en/docs/release-notes.md

            * [Install custom exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#install-custom-exception-handlers).
            * [Override the default exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#override-the-default-exception-handlers).
            * [Re-use **FastAPI's** exception handlers](https://fastapi.tiangolo.com/tutorial/handling-errors/#re-use-fastapis-exception-handlers).
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  4. docs/es/docs/index.md

    * Validar que existe un `item_id` en el path para requests usando `GET` y `PUT`.
    * Validar que el `item_id` es del tipo `int` para requests de tipo `GET` y `PUT`.
        * Si no lo es, el cliente verĂ¡ un mensaje de error Ăºtil y claro.
    * Revisar si existe un query parameter opcional llamado `q` (cĂ³mo en `http://127.0.0.1:8000/items/foo?q=somequery`) para requests de tipo `GET`.
        * Como el parĂ¡metro `q` fue declarado con `= None` es opcional.
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  5. docs/en/docs/features.md

        * If you know Python types you know how to use Pydantic.
    * Plays nicely with your **<abbr title="Integrated Development Environment, similar to a code editor">IDE</abbr>/<abbr title="A program that checks for code errors">linter</abbr>/brain**:
        * Because pydantic data structures are just instances of classes you define; auto-completion, linting, mypy and your intuition should all work properly with your validated data.
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  6. README.md

    * **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
    * **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
    * **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
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  7. docs/en/docs/index.md

    * **Fast to code**: Increase the speed to develop features by about 200% to 300%. *
    * **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
    * **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
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  8. docs/en/docs/advanced/settings.md

    !!! info
        In Pydantic version 1 the configuration was done in an internal class `Config`, in Pydantic version 2 it's done in an attribute `model_config`. This attribute takes a `dict`, and to get autocompletion and inline errors you can import and use `SettingsConfigDict` to define that `dict`.
    
    Here we define the config `env_file` inside of your Pydantic `Settings` class, and set the value to the filename with the dotenv file we want to use.
    
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