When you check the benchmarks, it is common to see several tools of different types compared as equivalent.

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server

This helps to make sure that:

* The documentation is up-to-date.
* The documentation examples can be run as is.
* Most of the features are covered by the documentation, ensured by test coverage.

#### Apps and docs at the same time

If you run the examples with, e.g.:

<div class="termy">

```console
$ uvicorn tutorial001:app --reload

But I'll show you how to improve that next. 🤓

## Custom Operation IDs and Better Method Names

You can **modify** the way these operation IDs are **generated** to make them simpler and have **simpler method names** in the clients.

In this case you will have to ensure that each operation ID is **unique** in some other way.

            max_digits=max_digits,
            decimal_places=decimal_places,
            deprecated=deprecated,
            example=example,
            examples=examples,
            openapi_examples=openapi_examples,
            include_in_schema=include_in_schema,
            json_schema_extra=json_schema_extra,
            **extra,
        )


class Query(Param):

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python

        multiple_of=multiple_of,
        allow_inf_nan=allow_inf_nan,
        max_digits=max_digits,
        decimal_places=decimal_places,
        example=example,
        examples=examples,
        openapi_examples=openapi_examples,
        deprecated=deprecated,
        include_in_schema=include_in_schema,
        json_schema_extra=json_schema_extra,
        **extra,
    )


def Query(  # noqa: N802

# First Steps

The simplest FastAPI file could look like this:

```Python
{!../../../docs_src/first_steps/tutorial001.py!}
```

Copy that to a file `main.py`.

Run the live server:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

    * Pero te proporciona las herramientas para crear aplicaciones web simples, con <abbr title="también conocido en español como: enrutamiento">routing</abbr> basado en <abbr title="tambien conocido en español como: rutas">paths</abbr>, etc.

                                "schema": IsDict(
                                    {
                                        "$ref": "#/components/schemas/Item",
                                        "examples": [
                                            {
                                                "name": "Foo",
                                                "description": "A very nice Item",

    "name": "Foo",
    "price": 50.2
}
```

!!! info
    In Pydantic v1 the method was called `.dict()`, it was deprecated (but still supported) in Pydantic v2, and renamed to `.model_dump()`.

    The examples here use `.dict()` for compatibility with Pydantic v1, but you should use `.model_dump()` instead if you can use Pydantic v2.

!!! info