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  1. docs/en/docs/tutorial/testing.md

    Use the `TestClient` object the same way as you do with `httpx`.
    
    Write simple `assert` statements with the standard Python expressions that you need to check (again, standard `pytest`).
    
    ```Python hl_lines="2  12  15-18"
    {!../../../docs_src/app_testing/tutorial001.py!}
    ```
    
    !!! tip
        Notice that the testing functions are normal `def`, not `async def`.
    
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  2. docs/en/docs/advanced/dataclasses.md

    !!! info
        Keep in mind that dataclasses can't do everything Pydantic models can do.
    
        So, you might still need to use Pydantic models.
    
        But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓
    
    ## Dataclasses in `response_model`
    
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  3. docs/en/docs/advanced/testing-database.md

    ## Create the database
    
    Because now we are going to use a new database in a new file, we need to make sure we create the database with:
    
    ```Python
    Base.metadata.create_all(bind=engine)
    ```
    
    That is normally called in `main.py`, but the line in `main.py` uses the database file `sql_app.db`, and we need to make sure we create `test.db` for the tests.
    
    So we add that line here, with the new file.
    
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  4. docs/en/docs/how-to/graphql.md

        * With <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>
    
    ## GraphQL with Strawberry
    
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  5. docs/en/docs/how-to/index.md

    # How To - Recipes
    
    Here you will see different recipes or "how to" guides for **several topics**.
    
    Most of these ideas would be more or less **independent**, and in most cases you should only need to study them if they apply directly to **your project**.
    
    If something seems interesting and useful to your project, go ahead and check it, but otherwise, you might probably just skip them.
    
    !!! tip
    
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  6. docs/en/docs/tutorial/path-params.md

    And then you can also have a path `/users/{user_id}` to get data about a specific user by some user ID.
    
    Because *path operations* are evaluated in order, you need to make sure that the path for `/users/me` is declared before the one for `/users/{user_id}`:
    
    ```Python hl_lines="6  11"
    {!../../../docs_src/path_params/tutorial003.py!}
    ```
    
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  7. docs/en/docs/deployment/manually.md

    FastAPI uses a standard for building Python web frameworks and servers called <abbr title="Asynchronous Server Gateway Interface">ASGI</abbr>. FastAPI is an ASGI web framework.
    
    The main thing you need to run a **FastAPI** application (or any other ASGI application) in a remote server machine is an ASGI server program like **Uvicorn**, this is the one that comes by default in the `fastapi` command.
    
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  8. docs/en/docs/advanced/behind-a-proxy.md

    # Behind a Proxy
    
    In some situations, you might need to use a **proxy** server like Traefik or Nginx with a configuration that adds an extra path prefix that is not seen by your application.
    
    In these cases you can use `root_path` to configure your application.
    
    The `root_path` is a mechanism provided by the ASGI specification (that FastAPI is built on, through Starlette).
    
    The `root_path` is used to handle these specific cases.
    
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  9. docs/en/docs/tutorial/response-model.md

        * This is particularly important for **security**, we'll see more of that below.
    
    ## `response_model` Parameter
    
    There are some cases where you need or want to return some data that is not exactly what the type declares.
    
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  10. docs/en/docs/benchmarks.md

        * The same way that Starlette uses Uvicorn and cannot be faster than it, **FastAPI** uses Starlette, so it cannot be faster than it.
        * FastAPI provides more features on top of Starlette. Features that you almost always need when building APIs, like data validation and serialization. And by using it, you get automatic documentation for free (the automatic documentation doesn't even add overhead to running applications, it is generated on startup).
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