Par exemple, le modèle ci-dessus déclare un "objet" JSON (ou `dict` Python) tel que :

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

Mais, **tout fonctionne** par défaut.

### Validation

* Validation pour la plupart (ou tous?) les **types de données** Python incluant:
    * objets JSON (`dict`).
    * listes JSON (`list`) définissant des types d'éléments.
    * Champs String (`str`), définition de longueur minimum ou maximale.
    * Nombres (`int`, `float`) avec valeur minimale and maximale, etc.

And then you can set cookies in that *temporal* response object.

```Python hl_lines="1  8-9"
{!../../docs_src/response_cookies/tutorial002.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

        target_url=run_url,
    )

    files = list(use_pr.get_files())
    docs_files = [f for f in files if f.filename.startswith("docs/")]

    deploy_url = settings.deploy_url.rstrip("/")
    lang_links: dict[str, list[str]] = {}
    for f in docs_files:
        match = re.match(r"docs/([^/]+)/docs/(.*)", f.filename)
        if not match:
            continue
        lang = match.group(1)
        path = match.group(2)

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.dict.kuromoji;

import org.codelibs.fess.unit.UnitFessTestCase;

public class KuromojiItemTest extends UnitFessTestCase {
    public void test_new1() {

fi

if [ "$sete" = true ]; then
	set -e
fi

pattern="$1"
if [ "$pattern" = "" ]; then
	pattern=.
fi

./make.bash || exit 1
GOROOT="$(cd .. && pwd)"

gettargets() {
	../bin/go tool dist list | sed -e 's|/|-|' |
		grep -E -v '^(android|ios)' # need C toolchain even for cross-compiling
	echo linux-arm-arm5
}

selectedtargets() {
	gettargets | grep -E "$pattern"
}

)

config_setting(
    name = "android_x86",
    constraint_values = if_google(
        ["//third_party/bazel_platforms/os:android"],
        [],
    ),
    values = dict(
        if_oss(
            {"crosstool_top": "//external:android/crosstool"},
        ),
        cpu = "x86",
    ),
    visibility = ["//visibility:public"],
)

config_setting(

Zum Beispiel deklariert das obige Modell ein JSON "`object`" (oder Python-`dict`) wie dieses:

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

Por exemplo, o modelo acima declara um JSON "`object`" (ou `dict` no Python) como esse:

```JSON
{
    "name": "Foo",
    "description": "Uma descrição opcional",
    "price": 45.2,
    "tax": 3.5
}
```

```Python hl_lines="5-9"
{!> ../../docs_src/body/tutorial001_py310.py!}
```

////

🎏 🕐❔ 📣 🔢 🔢, 🕐❔ 🏷 🔢 ✔️ 🔢 💲, ⚫️ 🚫 ✔. ⏪, ⚫️ ✔. ⚙️ `None` ⚒ ⚫️ 📦.

🖼, 👉 🏷 🔛 📣 🎻 "`object`" (⚖️ 🐍 `dict`) 💖:

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

... `description` & `tax` 📦 (⏮️ 🔢 💲 `None`), 👉 🎻 "`object`" 🔜 ☑: