second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

/// info

`**second_user_data` nghĩa là:

Truyền các khóa và giá trị của dict `second_user_data` trực tiếp như các tham số kiểu key-value, tương đương với: `User(id=4, name="Mary", joined="2018-11-30")`

///

### Được hỗ trợ từ các trình soạn thảo

        return redirect(getClass());
    }

    // ===================================================================================
    //                                                                        Assist Logic
    //                                                                        ============
    public static OptionalEntity<DataConfig> getEntity(final CreateForm form, final String username, final long currentTime) {

  virtual std::vector<tensorflow::Device*> ListAllTfDevices() = 0;

  //===--------------------------------------------------------------------===//
  // Following are helper functions to assist integrating TFRT with current
  // TF eager runtime.
  // TODO(b/172877902): These helper functions are currently used to support
  // PyFuncOp on TFRT, and might be useful for ops that directly use low

   *
   * <pre>{@code
   * for (List<String> perm : orderedPermutations(asList("b", "c", "a"))) {
   *   println(perm);
   * }
   * // -> ["a", "b", "c"]
   * // -> ["a", "c", "b"]
   * // -> ["b", "a", "c"]
   * // -> ["b", "c", "a"]
   * // -> ["c", "a", "b"]
   * // -> ["c", "b", "a"]
   *
   * for (List<Integer> perm : orderedPermutations(asList(1, 2, 2, 1))) {
   *   println(perm);
   * }
   * // -> [1, 1, 2, 2]

The same as when declaring query parameters, when a model attribute has a default value, it is not required. Otherwise, it is required. Use `None` to make it just optional.

For example, this model above declares a JSON "`object`" (or Python `dict`) like:

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

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
}
```

👆 💪 📣 🔢 🆎 `Response` 👆 *➡ 🛠️ 🔢*.

& ⤴️ 👆 💪 ⚒ 🍪 👈 *🔀* 📨 🎚.

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

& ⤴️ 👆 💪 📨 🙆 🎚 👆 💪, 👆 🛎 🔜 ( `dict`, 💽 🏷, ♒️).

& 🚥 👆 📣 `response_model`, ⚫️ 🔜 ⚙️ ⛽ & 🗜 🎚 👆 📨.

**FastAPI** 🔜 ⚙️ 👈 *🔀* 📨 ⚗ 🍪 (🎚 & 👔 📟), & 🔜 🚮 👫 🏁 📨 👈 🔌 💲 👆 📨, ⛽ 🙆 `response_model`.

import org.eclipse.aether.resolution.VersionRangeRequest;
import org.eclipse.aether.resolution.VersionRangeResolutionException;
import org.eclipse.aether.resolution.VersionRangeResult;

/**
 * A model resolver to assist building of dependency POMs. This resolver gives priority to those repositories that have
 * been initially specified and repositories discovered in dependency POMs are recessively merged into the search chain.
 *

func httpTracerMiddleware(h http.Handler) http.Handler {
	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
		// Setup a http request response recorder - this is needed for
		// http stats requests and audit if enabled.
		respRecorder := xhttp.NewResponseRecorder(w)

		// Setup a http request body recorder
		reqRecorder := &xhttp.RequestRecorder{Reader: r.Body}
		r.Body = reqRecorder

```Python hl_lines="1  7-8"
{!../../docs_src/response_headers/tutorial002.py!}
```

Posteriormente, puedes devolver cualquier objeto que necesites, como normalmente harías (un `dict`, un modelo de base de datos, etc).

Si declaraste un `response_model`, este se continuará usando para filtrar y convertir el objeto que devolviste.