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  1. docs/en/docs/alternatives.md

    !!! check "**FastAPI** uses it to"
        Handle all the core web parts. Adding features on top.
    
        The class `FastAPI` itself inherits directly from the class `Starlette`.
    
        So, anything that you can do with Starlette, you can do it directly with **FastAPI**, as it is basically Starlette on steroids.
    
    ### <a href="https://www.uvicorn.org/" class="external-link" target="_blank">Uvicorn</a>
    
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  2. docs/en/docs/tutorial/first-steps.md

    ### Step 5: return the content
    
    ```Python hl_lines="8"
    {!../../../docs_src/first_steps/tutorial001.py!}
    ```
    
    You can return a `dict`, `list`, singular values as `str`, `int`, etc.
    
    You can also return Pydantic models (you'll see more about that later).
    
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  3. fastapi/security/http.py

                    be `None`.
    
                    This is useful when you want to have optional authentication.
    
                    It is also useful when you want to have authentication that can be
                    provided in one of multiple optional ways (for example, in HTTP Basic
                    authentication or in an HTTP Bearer token).
                    """
                ),
            ] = True,
        ):
    Python
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  4. fastapi/param_functions.py

            Doc(
                """
                An alternative name for the parameter field.
    
                This will be used to extract the data and for the generated OpenAPI.
                It is particularly useful when you can't use the name you want because it
                is a Python reserved keyword or similar.
                """
            ),
        ] = None,
        alias_priority: Annotated[
            Union[int, None],
            Doc(
                """
    Python
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  5. docs/en/docs/benchmarks.md

        * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
    * **Starlette**:
        * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
        * But it provides you the tools to build simple web applications, with routing based on paths, etc.
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  6. fastapi/utils.py

                f"check that {type_} is a valid Pydantic field type. "
                "If you are using a return type annotation that is not a valid Pydantic "
                "field (e.g. Union[Response, dict, None]) you can disable generating the "
                "response model from the type annotation with the path operation decorator "
                "parameter response_model=None. Read more: "
    Python
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  7. tests/test_tutorial/test_bigger_applications/test_main_an.py

        response = client.put(
            "/items/bar?token=jessica", headers={"X-Token": "fake-super-secret-token"}
        )
        assert response.status_code == 403, response.text
        assert response.json() == {"detail": "You can only update the item: plumbus"}
    
    
    def test_admin(client: TestClient):
        response = client.post(
            "/admin/?token=jessica", headers={"X-Token": "fake-super-secret-token"}
        )
    Python
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  8. tests/test_tutorial/test_bigger_applications/test_main_an_py39.py

        response = client.put(
            "/items/bar?token=jessica", headers={"X-Token": "fake-super-secret-token"}
        )
        assert response.status_code == 403, response.text
        assert response.json() == {"detail": "You can only update the item: plumbus"}
    
    
    @needs_py39
    def test_admin(client: TestClient):
        response = client.post(
            "/admin/?token=jessica", headers={"X-Token": "fake-super-secret-token"}
        )
    Python
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  9. docs/pl/docs/index.md

    ---
    
    "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"
    
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  10. docs/it/docs/index.md

    ---
    
    "_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"
    
    Plain Text
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