response = client.put(
        "/items/5",
        json={"description": "A very nice Item"},
    )
    assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", "name"],
                "input": {"description": "A very nice Item"},
                "msg": "Field required",
                "type": "missing",
            },

    response = client.put(
        "/items/5",
        json={"description": "A very nice Item"},
    )
    assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", "name"],
                "input": {"description": "A very nice Item"},
                "msg": "Field required",
                "type": "missing",
            },

            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,
            "tags": ["foo", "bar", "foo"],
        },
    )
    assert response.status_code == 200, response.text
    assert response.json() == {
        "item_id": 123,
        "item": {
            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,

Here are the general instructions for the tasks you can perform.

Thanks a lot for your help. 🙇

## Be Nice

First of all, be nice. 😊

You probably are super nice if you were added to the team, but it's worth mentioning it. 🤓

### When Things are Difficult

    Function<Float, Boolean> c1 = Functions.compose(Functions.compose(h, g), f);
    Function<Float, Boolean> c2 = Functions.compose(h, Functions.compose(g, f));

    // Might be nice (eventually) to have:
    //     assertEquals(c1, c2);

    // But for now, settle for this:
    assertEquals(c1.hashCode(), c2.hashCode());

    assertEquals(c1.apply(1.0f), c2.apply(1.0f));

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model` { #dataclasses-in-response-model }

You can also use `dataclasses` in the `response_model` parameter:

        "jnr.constants.ConstantResolver",
    ),
)
plugins.withId("java-base") {
    dependencies {
        attributesSchema {
            attribute(minified)
        }
        // It would be nice if we could be more selective about which variants to apply this to.
        // TODO https://github.com/gradle/gradle/issues/11831#issuecomment-580686994
        artifactTypes.getByName("jar") {

    implements ListenableFuture<V> {
  // TODO(cpovirk): explore ways of making ListenableFutureTask final. There are some valid reasons
  // such as BoundedQueueExecutorService to allow extends but it would be nice to make it final to
  // avoid unintended usage.

  // The execution list to hold our listeners.
  private final ExecutionList executionList = new ExecutionList();

  /**

    Function<Float, Boolean> c1 = Functions.compose(Functions.compose(h, g), f);
    Function<Float, Boolean> c2 = Functions.compose(h, Functions.compose(g, f));

    // Might be nice (eventually) to have:
    //     assertEquals(c1, c2);

    // But for now, settle for this:
    assertEquals(c1.hashCode(), c2.hashCode());

    assertEquals(c1.apply(1.0f), c2.apply(1.0f));

class Item(BaseModel):
    name: str
    description: str | None = None


@app.get("/items/me", response_model=Item)
async def get_item() -> Any:
    return {"name": "Foo", "description": "A very nice Item"}
```

This can be particularly useful when filtering data to expose only the public fields and avoid exposing sensitive information.

```python
from typing import Any

from fastapi import FastAPI