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  1. docs/en/docs/reference/request.md

    You can import it directly from `fastapi`:
    
    ```python
    from fastapi import Request
    ```
    
    !!! tip
        When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.
    
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  2. docs/en/docs/tutorial/body-fields.md

        `Body` also returns objects of a subclass of `FieldInfo` directly. And there are others you will see later that are subclasses of the `Body` class.
    
        Remember that when you import `Query`, `Path`, and others from `fastapi`, those are actually functions that return special classes.
    
    !!! tip
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  3. docs/en/docs/how-to/graphql.md

    It was deprecated from Starlette, but if you have code that used it, you can easily **migrate** to <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>, that covers the same use case and has an **almost identical interface**.
    
    !!! tip
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  4. fastapi/security/http.py

            return HTTPAuthorizationCredentials(scheme=scheme, credentials=credentials)
    
    
    class HTTPBasic(HTTPBase):
        """
        HTTP Basic authentication.
    
        ## Usage
    
        Create an instance object and use that object as the dependency in `Depends()`.
    
        The dependency result will be an `HTTPBasicCredentials` object containing the
        `username` and the `password`.
    
        Read more about it in the
    Python
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  5. tests/test_tutorial/test_query_params_str_validations/test_tutorial010_an.py

                        "operationId": "read_items_items__get",
                        "parameters": [
                            {
                                "description": "Query string for the items to search in the database that have a good match",
                                "required": False,
                                "deprecated": True,
                                "schema": IsDict(
                                    {
    Python
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  6. docs/en/docs/tutorial/extra-models.md

    We could do better.
    
    We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).
    
    All the data conversion, validation, documentation, etc. will still work as normally.
    
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  7. docs_src/websockets/tutorial002_an_py310.py

        WebSocketException,
        status,
    )
    from fastapi.responses import HTMLResponse
    
    app = FastAPI()
    
    html = """
    <!DOCTYPE html>
    <html>
        <head>
            <title>Chat</title>
        </head>
        <body>
            <h1>WebSocket Chat</h1>
            <form action="" onsubmit="sendMessage(event)">
                <label>Item ID: <input type="text" id="itemId" autocomplete="off" value="foo"/></label>
    Python
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  8. fastapi/params.py

            decimal_places: Union[int, None] = _Unset,
            examples: Optional[List[Any]] = None,
            example: Annotated[
                Optional[Any],
                deprecated(
                    "Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, "
                    "although still supported. Use examples instead."
                ),
            ] = _Unset,
            openapi_examples: Optional[Dict[str, Example]] = None,
    Python
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  9. docs/de/docs/tutorial/body-nested-models.md

        ```Python hl_lines="9  14  20  23  27"
        {!> ../../../docs_src/body_nested_models/tutorial007.py!}
        ```
    
    !!! info
        Beachten Sie, wie `Offer` eine Liste von `Item`s hat, von denen jedes seinerseits eine optionale Liste von `Image`s hat.
    
    ## Bodys aus reinen Listen
    
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  10. docs_src/query_params_str_validations/tutorial010.py

    @app.get("/items/")
    async def read_items(
        q: Union[str, None] = Query(
            default=None,
            alias="item-query",
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
            max_length=50,
            pattern="^fixedquery$",
            deprecated=True,
        ),
    ):
        results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
        if q:
    Python
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