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  1. docs/en/docs/tutorial/first-steps.md

    You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.
    
    ### Deploy your app (optional) { #deploy-your-app-optional }
    
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  2. docs/en/docs/async.md

    But then, even though you still don't have your burgers, your work with the cashier is "on pause" ⏸, because you have to wait 🕙 for your burgers to be ready.
    
    But as you go away from the counter and sit at the table with a number for your turn, you can switch 🔀 your attention to your crush, and "work" ⏯ 🤓 on that. Then you are again doing something very "productive" as is flirting with your crush 😍.
    
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  3. docs/en/docs/tutorial/debugging.md

    ///
    
    ## Run your code with your debugger { #run-your-code-with-your-debugger }
    
    Because you are running the Uvicorn server directly from your code, you can call your Python program (your FastAPI application) directly from the debugger.
    
    ---
    
    For example, in Visual Studio Code, you can:
    
    * Go to the "Debug" panel.
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  4. docs/en/docs/advanced/async-tests.md

    You have already seen how to test your **FastAPI** applications using the provided `TestClient`. Up to now, you have only seen how to write synchronous tests, without using `async` functions.
    
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  5. docs/en/docs/advanced/openapi-webhooks.md

    # OpenAPI Webhooks { #openapi-webhooks }
    
    There are cases where you want to tell your API **users** that your app could call *their* app (sending a request) with some data, normally to **notify** of some type of **event**.
    
    This means that instead of the normal process of your users sending requests to your API, it's **your API** (or your app) that could **send requests to their system** (to their API, their app).
    
    This is normally called a **webhook**.
    
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  6. docs/en/docs/deployment/concepts.md

    ### Server Memory { #server-memory }
    
    For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.
    
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  7. docs/en/docs/advanced/openapi-callbacks.md

    The process that happens when your API app calls the *external API* is named a "callback". Because the software that the external developer wrote sends a request to your API and then your API *calls back*, sending a request to an *external API* (that was probably created by the same developer).
    
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  8. docs/en/docs/how-to/custom-docs-ui-assets.md

    * `title`: the title of your API.
    * `oauth2_redirect_url`: you can use `app.swagger_ui_oauth2_redirect_url` here to use the default.
    * `swagger_js_url`: the URL where the HTML for your Swagger UI docs can get the **JavaScript** file. This is the custom CDN URL.
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  9. docs/en/docs/contributing.md

    ---> 100%
    ```
    
    </div>
    
    ////
    
    It will install all the dependencies and your local FastAPI in your local environment.
    
    ### Using your local FastAPI
    
    If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code.
    
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  10. docs/en/docs/advanced/behind-a-proxy.md

    In many situations, you would use a **proxy** like Traefik or Nginx in front of your FastAPI app.
    
    These proxies could handle HTTPS certificates and other things.
    
    ## Proxy Forwarded Headers { #proxy-forwarded-headers }
    
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