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  1. docs/en/docs/alternatives.md

    It used custom types in its declarations instead of standard Python types, but it was still a huge step forward.
    
    It also was one of the first frameworks to generate a custom schema declaring the whole API in JSON.
    
    It was not based on a standard like OpenAPI and JSON Schema. So it wouldn't be straightforward to integrate it with other tools, like Swagger UI. But again, it was a very innovative idea.
    
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  2. docs/en/docs/benchmarks.md

    * **FastAPI**:
        * The same way that Starlette uses Uvicorn and cannot be faster than it, **FastAPI** uses Starlette, so it cannot be faster than it.
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  3. docs/en/docs/tutorial/middleware.md

    * It takes each **request** that comes to your application.
    * It can then do something to that **request** or run any needed code.
    * Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
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  4. docs/en/docs/advanced/behind-a-proxy.md

    You can check it at <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>:
    
    <img src="/img/tutorial/behind-a-proxy/image01.png">
    
    But if we access the docs UI at the "official" URL using the proxy with port `9999`, at `/api/v1/docs`, it works correctly! 🎉
    
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  5. docs/en/docs/contributing.md

    ```console
    $ pip install -r requirements.txt
    
    ---> 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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  6. docs/en/docs/tutorial/testing.md

    It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.
    
    With it, you can use <a href="https://docs.pytest.org/" class="external-link" target="_blank">pytest</a> directly with **FastAPI**.
    
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  7. docs/en/docs/tutorial/response-model.md

    * Add a **JSON Schema** for the response, in the OpenAPI *path operation*.
        * This will be used by the **automatic docs**.
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  8. docs/en/docs/advanced/generate-clients.md

    #### Generate Client Code
    
    To generate the client code you can use the command line application `openapi-ts` that would now be installed.
    
    Because it is installed in the local project, you probably wouldn't be able to call that command directly, but you would put it on your `package.json` file.
    
    It could look like this:
    
    ```JSON  hl_lines="7"
    {
      "name": "frontend-app",
      "version": "1.0.0",
      "description": "",
      "main": "index.js",
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  9. docs/en/docs/advanced/testing-database.md

    ```Python hl_lines="8-13"
    {!../../../docs_src/sql_databases/sql_app/tests/test_sql_app.py!}
    ```
    
    !!! tip
        You could reduce duplication in that code by putting it in a function and using it from both `database.py` and `tests/test_sql_app.py`.
    
        For simplicity and to focus on the specific testing code, we are just copying it.
    
    ## Create the database
    
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  10. docs/en/docs/how-to/graphql.md

    # GraphQL
    
    As **FastAPI** is based on the **ASGI** standard, it's very easy to integrate any **GraphQL** library also compatible with ASGI.
    
    You can combine normal FastAPI *path operations* with GraphQL on the same application.
    
    !!! tip
        **GraphQL** solves some very specific use cases.
    
        It has **advantages** and **disadvantages** when compared to common **web APIs**.
    
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