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  1. docs/en/docs/tutorial/cors.md

    Even if they are all in `localhost`, they use different protocols or ports, so, they are different "origins".
    
    ## Steps
    
    So, let's say you have a frontend running in your browser at `http://localhost:8080`, and its JavaScript is trying to communicate with a backend running at `http://localhost` (because we don't specify a port, the browser will assume the default port `80`).
    
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  2. docs/en/docs/advanced/security/http-basic-auth.md

        ...
    ```
    
    But by using the `secrets.compare_digest()` it will be secure against a type of attacks called "timing attacks".
    
    ### Timing Attacks
    
    But what's a "timing attack"?
    
    Let's imagine some attackers are trying to guess the username and password.
    
    And they send a request with a username `johndoe` and a password `love123`.
    
    Then the Python code in your application would be equivalent to something like:
    
    ```Python
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  3. docs/en/docs/deployment/docker.md

    So, if your application consumes a lot of memory (for example with machine learning models), and your server has a lot of CPU cores **but little memory**, then your container could end up trying to use more memory than what is available, and degrading performance a lot (or even crashing). 🚨
    
    ### Create a `Dockerfile`
    
    Here's how you would create a `Dockerfile` based on this image:
    
    ```Dockerfile
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  4. docs/en/docs/async.md

    It would take the same amount of time to finish with or without turns (concurrency) and you would have done the same amount of work.
    
    But in this case, if you could bring the 8 ex-cashier/cooks/now-cleaners, and each one of them (plus you) could take a zone of the house to clean it, you could do all the work in **parallel**, with the extra help, and finish much sooner.
    
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  5. docs/en/docs/help-fastapi.md

    * In many cases, it's better to understand their **underlying problem or use case**, because there might be a better way to solve it than what they are trying to do.
    
    ### Ask to close
    
    If they reply, there's a high chance you would have solved their problem, congrats, **you're a hero**! 🦸
    
    * Now, if that solved their problem, you can ask them to:
    
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  6. docs/en/docs/tutorial/dependencies/index.md

    And then it just returns a `dict` containing those values.
    
    !!! info
        FastAPI added support for `Annotated` (and started recommending it) in version 0.95.0.
    
        If you have an older version, you would get errors when trying to use `Annotated`.
    
        Make sure you [Upgrade the FastAPI version](../../deployment/versions.md#upgrading-the-fastapi-versions){.internal-link target=_blank} to at least 0.95.1 before using `Annotated`.
    
    ### Import `Depends`
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  7. docs/en/docs/tutorial/query-params-str-validations.md

        ```
    
    !!! info
        FastAPI added support for `Annotated` (and started recommending it) in version 0.95.0.
    
        If you have an older version, you would get errors when trying to use `Annotated`.
    
        Make sure you [Upgrade the FastAPI version](../deployment/versions.md#upgrading-the-fastapi-versions){.internal-link target=_blank} to at least 0.95.1 before using `Annotated`.
    
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  8. docs/en/docs/advanced/generate-clients.md

    client it will error out if you have any **mismatch** in the data used.
    
    So, you would **detect many errors** very early in the development cycle instead of having to wait for the errors to show up to your final users in production and then trying to debug where the problem is. ✨...
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  9. docs/en/docs/deployment/concepts.md

    And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨
    
    ### Multiple Processes - An Example
    
    In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.
    
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  10. docs/en/docs/release-notes.md

    ### Upgrades
    
    * 📌 Update minimum version of Pydantic to >=1.7.4. This fixes an issue when trying to use an old version of Pydantic. PR [#9567](https://github.com/tiangolo/fastapi/pull/9567) by [@Kludex](https://github.com/Kludex).
    
    ### Refactors
    
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