```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

...as `description` and `tax` are optional (with a default value of `None`), this JSON "`object`" would also be valid:

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

## Declare it as a parameter

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

...`description` et `tax` étant des attributs optionnels (avec `None` comme valeur par défaut), cet "objet" JSON serait aussi valide :

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

## Déclarez-le comme paramètre

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: Union[bool, None] = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):

   */
  public List<Long> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

  static class AsList extends AbstractList<Long> implements RandomAccess, Serializable {

   */
  public List<Integer> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

  static class AsList extends AbstractList<Integer> implements RandomAccess, Serializable {

```Python hl_lines="1  4"
{!> ../../docs_src/python_types/tutorial008.py!}
```

////

This means:

* The variable `prices` is a `dict`:
    * The keys of this `dict` are of type `str` (let's say, the name of each item).
    * The values of this `dict` are of type `float` (let's say, the price of each item).

#### Union

You can declare that a variable can be any of **several types**, for example, an `int` or a `str`.

   */
  public List<Integer> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

  static class AsList extends AbstractList<Integer> implements RandomAccess, Serializable {

   */
  public List<Double> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

  static class AsList extends AbstractList<Double> implements RandomAccess, Serializable {

	if !disk.ODirectPlatform {
		return errUnsupportedDisk
	}

	// We know XFS already supports O_DIRECT no need to check.
	if fsType == "XFS" {
		return nil
	}

	// For all other FS pay the price of not using our recommended filesystem.

	// Check if backend is writable and supports O_DIRECT
	uuid := mustGetUUID()
	filePath := pathJoin(s.drivePath, minioMetaTmpDeletedBucket, ".writable-check-"+uuid+".tmp")

from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


@app.get("/items/")
async def read_items() -> list[Item]:
    return [
        Item(name="Portal Gun", price=42.0),
        Item(name="Plumbus", price=32.0),
    ]
```

FastAPI will use the return type annotation to perform:

* Data validation