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  1. docs/en/docs/img/deployment/https/https08.drawio

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  2. docs/en/docs/img/deployment/https/https04.drawio

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  3. docs/en/docs/img/deployment/https/https07.drawio

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  4. docs/en/docs/img/deployment/https/https.drawio

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  5. docs/en/docs/img/deployment/https/https06.drawio

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  6. docs/en/docs/img/deployment/https/https05.drawio

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  7. docs/en/docs/img/deployment/https/https03.drawio

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  8. docs/en/docs/img/deployment/concepts/process-ram.drawio

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  9. fastapi/openapi/docs.py

        <meta charset="utf-8"/>
        <meta name="viewport" content="width=device-width, initial-scale=1">
        """
        if with_google_fonts:
            html += """
        <link href="https://fonts.googleapis.com/css?family=Montserrat:300,400,700|Roboto:300,400,700" rel="stylesheet">
        """
        html += f"""
        <link rel="shortcut icon" href="{redoc_favicon_url}">
        <!--
        ReDoc doesn't change outer page styles
        -->
    Python
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  10. docs/en/docs/alternatives.md

    * Dependency Injection system.
    
    It doesn't use a data validation, serialization and documentation third-party library like Pydantic, it has its own. So, these data type definitions would not be reusable as easily.
    
    It requires a little bit more verbose configurations. And as it is based on WSGI (instead of ASGI), it is not designed to take advantage of the high performance provided by tools like Uvicorn, Starlette and Sanic.
    
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