<div class="termy">

    ```console
    $ pip install "uvicorn[standard]"

    ---> 100%
    ```

    </div>

    !!! tip
        By adding the `standard`, Uvicorn will install and use some recommended extra dependencies.

        That including `uvloop`, the high-performance drop-in replacement for `asyncio`, that provides the big concurrency performance boost.

---> 100%
```

</div>

<a href="https://github.com/mpdavis/python-jose" class="external-link" target="_blank">Python-jose</a> requires a cryptographic backend as an extra.

Here we are using the recommended one: <a href="https://cryptography.io/" class="external-link" target="_blank">pyca/cryptography</a>.

!!! tip

    {!> ../../../docs_src/query_params_str_validations/tutorial009_py310.py!}
    ```

## 😛 🔢

🔜 ➡️ 💬 👆 🚫 💖 👉 🔢 🚫🔜.

👆 ✔️ 👈 ⚫️ 📤 ⏪ ↩️ 📤 👩‍💻 ⚙️ ⚫️, ✋️ 👆 💚 🩺 🎯 🎦 ⚫️ <abbr title="obsolete, recommended not to use it">😢</abbr>.

⤴️ 🚶‍♀️ 🔢 `deprecated=True` `Query`:

=== "🐍 3️⃣.6️⃣ &amp; 🔛"

    ```Python hl_lines="18"
    {!> ../../../docs_src/query_params_str_validations/tutorial010.py!}
    ```

This can be used as a quick shortcut if you have only one Pydantic model and want to remove some data from the output.

!!! tip
    But it is still recommended to use the ideas above, using multiple classes, instead of these parameters.

It is the recommended server for Starlette and **FastAPI**.

!!! check "**FastAPI** recommends it as"
    The main web server to run **FastAPI** applications.

    You can combine it with Gunicorn, to have an asynchronous multi-process server.

```Python hl_lines="22"
{!../../../docs_src/events/tutorial003.py!}
```

## Alternative Events (deprecated)

!!! warning

```Python
q: Annotated[str, Query()] = "rick"
```

...or in older code bases you will find:

```Python
q: str = Query(default="rick")
```

### Advantages of `Annotated`

**Using `Annotated` is recommended** instead of the default value in function parameters, it is **better** for multiple reasons. 🤓

The **default** value of the **function parameter** is the **actual default** value, that's more intuitive with Python in general. 😌

app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)
    return {"result": result}
```

**Note**: This is the recommended way going forward, instead of using `startup` and `shutdown` events.

Read more about it in the new docs: [Advanced User Guide: Lifespan Events](https://fastapi.tiangolo.com/advanced/events/).

### Docs

    If you are just starting, the tutorial [SQL (Relational) Databases](../tutorial/sql-databases.md){.internal-link target=_blank} that uses SQLAlchemy should be enough.

    Feel free to skip this.

    Peewee is not recommended with FastAPI as it doesn't play well with anything async Python. There are several better alternatives.

!!! info
    These docs assume Pydantic v1.

hon-sdk/2.5/async-programming.html#asyncio-python-3-5" class="external-link" target="_blank">experimental Python <code>await</code> support</a>, we should declare our function with normal `def` instead of `async def`.

Also, Couchbase recommends not using a single `Bucket` object in multiple "<abbr title="A sequence of code being executed by the program, while at the same time, or at intervals, there can be others being executed too.">thread</abbr>s", so, we can just get the bucket directly...