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  1. docs/en/docs/advanced/openapi-callbacks.md

        When implementing the callback yourself, you could use something like <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a> or <a href="https://requests.readthedocs.io/" class="external-link" target="_blank">Requests</a>.
    
    ## Write the callback documentation code
    
    This code won't be executed in your app, we only need it to *document* how that *external API* should look like.
    
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  2. docs/en/docs/alternatives.md

    It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.
    
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  3. docs/en/docs/benchmarks.md

        * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself....
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  4. docs/en/docs/tutorial/security/oauth2-jwt.md

        For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.
    
        And be compatible with all of them at the same time.
    
    Create a utility function to hash a password coming from the user.
    
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  5. docs/en/docs/advanced/behind-a-proxy.md

                // More stuff here
        }
    }
    ```
    
    In this example, the "Proxy" could be something like **Traefik**. And the server would be something like FastAPI CLI with **Uvicorn**, running your FastAPI application.
    
    ### Providing the `root_path`
    
    To achieve this, you can use the command line option `--root-path` like:
    
    <div class="termy">
    
    ```console
    $ fastapi run main.py --root-path /api/v1
    
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  6. docs/en/docs/tutorial/first-steps.md

    ## Recap
    
    * Import `FastAPI`.
    * Create an `app` instance.
    * Write a **path operation decorator** (like `@app.get("/")`).
    * Write a **path operation function** (like `def root(): ...` above).
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  7. docs/en/docs/tutorial/response-model.md

        Notice that `response_model` is a parameter of the "decorator" method (`get`, `post`, etc). Not of your *path operation function*, like all the parameters and body.
    
    `response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.
    
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  8. docs/en/docs/tutorial/bigger-applications.md

    But that file doesn't exist, our dependencies are in a file at `app/dependencies.py`.
    
    Remember how our app/file structure looks like:
    
    <img src="/img/tutorial/bigger-applications/package.svg">
    
    ---
    
    The two dots `..`, like in:
    
    ```Python
    from ..dependencies import get_token_header
    ```
    
    mean:
    
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  9. docs/en/docs/advanced/custom-response.md

    ```Python hl_lines="2  14"
    {!../../../docs_src/custom_response/tutorial007.py!}
    ```
    
    #### Using `StreamingResponse` with file-like objects
    
    If you have a file-like object (e.g. the object returned by `open()`), you can create a generator function to iterate over that file-like object.
    
    That way, you don't have to read it all first in memory, and you can pass that generator function to the `StreamingResponse`, and return it.
    
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  10. docs/en/docs/tutorial/extra-models.md

    #### Unwrapping a `dict` and extra keywords
    
    And then adding the extra keyword argument `hashed_password=hashed_password`, like in:
    
    ```Python
    UserInDB(**user_in.dict(), hashed_password=hashed_password)
    ```
    
    ...ends up being like:
    
    ```Python
    UserInDB(
        username = user_dict["username"],
        password = user_dict["password"],
        email = user_dict["email"],
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