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

    This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.
    
    Those worker processes would be the ones running your application, they would perform the main computations to receive a **request** and return a **response**, and they would load anything you put in variables in RAM.
    
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  2. docs/en/docs/advanced/websockets.md

    ---
    
    But for this example, we'll use a very simple HTML document with some JavaScript, all inside a long string.
    
    This, of course, is not optimal and you wouldn't use it for production.
    
    In production you would have one of the options above.
    
    But it's the simplest way to focus on the server-side of WebSockets and have a working example:
    
    ```Python hl_lines="2  6-38  41-43"
    {!../../../docs_src/websockets/tutorial001.py!}
    ```
    
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  3. docs/en/docs/advanced/behind-a-proxy.md

    So, the frontend (that runs in the browser) would try to reach `/openapi.json` and wouldn't be able to get the OpenAPI schema.
    
    Because we have a proxy with a path prefix of `/api/v1` for our app, the frontend needs to fetch the OpenAPI schema at `/api/v1/openapi.json`.
    
    ```mermaid
    graph LR
    
    browser("Browser")
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  4. docs/en/docs/deployment/docker.md

    This is what you would want to do in **most cases**, for example:
    
    * Using **Kubernetes** or similar tools
    * When running on a **Raspberry Pi**
    * Using a cloud service that would run a container image for you, etc.
    
    ### Package Requirements
    
    You would normally have the **package requirements** for your application in some file.
    
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  5. docs/en/docs/advanced/settings.md

    But every time we do:
    
    ```Python
    Settings()
    ```
    
    a new `Settings` object would be created, and at creation it would read the `.env` file again.
    
    If the dependency function was just like:
    
    ```Python
    def get_settings():
        return Settings()
    ```
    
    we would create that object for each request, and we would be reading the `.env` file for each request. ⚠️
    
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  6. docs/en/docs/advanced/openapi-webhooks.md

    ```Python hl_lines="9-13  36-53"
    {!../../../docs_src/openapi_webhooks/tutorial001.py!}
    ```
    
    The webhooks that you define will end up in the **OpenAPI** schema and the automatic **docs UI**.
    
    !!! info
        The `app.webhooks` object is actually just an `APIRouter`, the same type you would use when structuring your app with multiple files.
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  7. docs/en/docs/deployment/manually.md

    <font color="#4E9A06">INFO</font>:     Application startup complete.
    <font color="#4E9A06">INFO</font>:     Uvicorn running on <b>http://0.0.0.0:8000</b> (Press CTRL+C to quit)
    ```
    
    </div>
    
    That would work for most of the cases. 😎
    
    You could use that command for example to start your **FastAPI** app in a container, in a server, etc.
    
    ## ASGI Servers
    
    Let's go a little deeper into the details.
    
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  8. docs/en/docs/advanced/openapi-callbacks.md

    # OpenAPI Callbacks
    
    You could create an API with a *path operation* that could trigger a request to an *external API* created by someone else (probably the same developer that would be *using* your API).
    
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  9. docs/en/docs/tutorial/first-steps.md

    #### What is OpenAPI for
    
    The OpenAPI schema is what powers the two interactive documentation systems included.
    
    And there are dozens of alternatives, all based on OpenAPI. You could easily add any of those alternatives to your application built with **FastAPI**.
    
    You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.
    
    ## Recap, step by step
    
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  10. docs/en/docs/fastapi-cli.md

    It will listen on the IP address `0.0.0.0`, which means all the available IP addresses, this way it will be publicly accessible to anyone that can communicate with the machine. This is how you would normally run it in production, for example, in a container.
    
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