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  1. docs/en/docs/release-notes.md

        * These `dependencies` are run before the normal parameter dependencies. And normal dependencies are run too. They can be combined.
        * Dependencies declared in a router are executed first, then the ones defined in *path operation decorators*, and then the ones declared in normal parameters. They are all combined and executed.
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  2. docs/en/docs/deployment/docker.md

    * <a href="https://hub.docker.com/_/redis" class="external-link" target="_blank">Redis</a>, etc.
    
    By using a pre-made container image it's very easy to **combine** and use different tools. For example, to try out a new database. In most cases, you can use the **official images**, and just configure them with environment variables.
    
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  3. docs/en/docs/features.md

    You will get completion in code you might even consider impossible before. As for example, the `price` key inside a JSON body (that could have been nested) that comes from a request.
    
    No more typing the wrong key names, coming back and forth between docs, or scrolling up and down to find if you finally used `username` or `user_name`.
    
    ### Short
    
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  4. README.md

        * Automatic and clear errors when the data is invalid.
        * Validation even for deeply nested JSON objects.
    * <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
        * JSON.
        * Path parameters.
        * Query parameters.
        * Cookies.
        * Headers.
        * Forms.
        * Files.
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  5. docs/en/docs/advanced/settings.md

    ## Pydantic `Settings`
    
    Fortunately, Pydantic provides a great utility to handle these settings coming from environment variables with <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" class="external-link" target="_blank">Pydantic: Settings management</a>.
    
    ### Install `pydantic-settings`
    
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  6. docs/en/docs/index.md

        * Automatic and clear errors when the data is invalid.
        * Validation even for deeply nested JSON objects.
    * <abbr title="also known as: serialization, parsing, marshalling">Conversion</abbr> of input data: coming from the network to Python data and types. Reading from:
        * JSON.
        * Path parameters.
        * Query parameters.
        * Cookies.
        * Headers.
        * Forms.
        * Files.
    Plain Text
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