"message/vnd.si.simp",
				"model/example",
				"model/iges",
				"model/mesh",
				"model/vnd.dwf",
				"model/vnd.dwfx+xps",
				"model/vnd.flatland.3dml",
				"model/vnd.gdl",
				"model/vnd.gs-gdl",
				"model/vnd.gs.gdl",
				"model/vnd.gtw",
				"model/vnd.moml+xml",
				"model/vnd.mts",
				"model/vnd.parasolid.transmit.binary",
				"model/vnd.parasolid.transmit.text",

Se você já clonou o repositório e precisa mergulhar no código, aqui estão algumas orientações para configurar seu ambiente.

### Ambiente virtual com `venv`

Você pode criar um ambiente virtual em um diretório utilizando o módulo `venv` do Python:

<div class="termy">

```console
$ python -m venv env
```

</div>

### Virtuelle Umgebung mit `venv`

Sie können mit dem Python-Modul `venv` in einem Verzeichnis eine isolierte virtuelle lokale Umgebung erstellen. Machen wir das im geklonten Repository (da wo sich die `requirements.txt` befindet):

<div class="termy">

```console
$ python -m venv env
```

    *   `Model.fit_generator`, `Model.evaluate_generator`,
        `Model.predict_generator`, `Model.train_on_batch`,
        `Model.test_on_batch`, and `Model.predict_on_batch` methods now respect
        the `run_eagerly` property, and will correctly run using `tf.function`
        by default. Note that `Model.fit_generator`, `Model.evaluate_generator`,

			} else {
				value /= divisor
			}
		case '%':
			p.next()
			divisor := p.factor()
			if int64(value) < 0 {
				p.errorf("modulo of value with high bit set")
			}
			if divisor == 0 {
				p.errorf("modulo by zero")
			} else {
				value %= divisor
			}
		case lex.LSH:
			p.next()
			shift := p.factor()
			if int64(shift) < 0 {

    full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | "说明"

`user_dict` 的说明，详见[**更多模型**一章](../extra-models.md#user_indict){.internal-link target=_blank}。

///

## 返回 Token

`token` 端点的响应必须是 JSON 对象。

响应返回的内容应该包含 `token_type`。本例中用的是**Bearer**Token，因此， Token 类型应为**`bearer`**。

inside and make sure it is serializable as JSON, using the same [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank} explained in the tutorial. This is what allows you to return **arbitrary objects**, for example database models.

But if you are certain that the content that you are returning is **serializable with JSON**, you can pass it directly to the response class and avoid the extra overhead that FastAPI would have by passing your return content through the...

### Environnement virtuel avec `venv`

Vous pouvez créer un environnement virtuel dans un répertoire en utilisant le module `venv` de Python :

<div class="termy">

```console
$ python -m venv env
```

</div>

          <name>aggregator</name>
          <version>1.0.0+</version>
          <type>boolean</type>
          <description>
            Flags this Mojo to run it in a multi-module way, i.e. aggregate the build with the set of projects
            listed as modules.
          </description>
          <defaultValue>false</defaultValue>
        </field>
        <field>
          <name>inheritedByDefault</name>

</div>

<details markdown="1">
<summary>Informazioni sul comando <code>uvicorn main:app --reload</code>...</summary>

Vediamo il comando `uvicorn main:app` in dettaglio:

* `main`: il file `main.py` (il "modulo" Python).
* `app`: l'oggetto creato dentro `main.py` con la riga di codice `app = FastAPI()`.
* `--reload`: ricarica il server se vengono rilevati cambiamenti del codice. Usalo solo durante la fase di sviluppo.

</details>