```Python
from datetime import date

from pydantic import BaseModel

# Déclare une variable comme étant une str
# et profitez de l'aide de votre IDE dans cette fonction
def main(user_id: str):
    return user_id


# Un modèle Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```
Qui peuvent ensuite être utilisés comme cela:

```Python

	{"$1", "$1"},
	{"$1.0", "$(1.0)"},
	{"$10", "$10"},
	{"$1000", "$1000"},
	{"$1000000", "$1000000"},
	{"$1000000000", "$1000000000"},
	{"$__tsan_func_enter(SB)", "$__tsan_func_enter(SB)"},
	{"$main(SB)", "$main(SB)"},
	{"$masks<>(SB)", "$masks<>(SB)"},
	{"$setg_gcc<>(SB)", "$setg_gcc<>(SB)"},
	{"$shifts<>(SB)", "$shifts<>(SB)"},
	{"$~(1<<63)", "$9223372036854775807"},
	{"$~0x3F", "$-64"},
	{"$~15", "$-16"},

   * if Fire.run is called by delegate.addListener since addListener is called after the assignment
   * to timer, and importantly this is the main situation in which we need to be able to see the
   * write.
   *
   * 2. visibility of the writes to an afterDone() call triggered by cancel():
   *

        assertEquals("time.adjust.time.millis", FessEnv.TIME_ADJUST_TIME_MILLIS);
        assertEquals("mail.send.mock", FessEnv.MAIL_SEND_MOCK);
        assertEquals("mail.smtp.server.main.host.and.port", FessEnv.MAIL_SMTP_SERVER_MAIN_HOST_AND_PORT);
        assertEquals("mail.subject.test.prefix", FessEnv.MAIL_SUBJECT_TEST_PREFIX);
        assertEquals("mail.return.path", FessEnv.MAIL_RETURN_PATH);
    }

    // Test default values

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

              @Override
              public void run() {
                notifyStarted();
                // We need to wait for the main thread to leave the ServiceManager.startAsync call
                // to
                // ensure that the thread running the failure callbacks is not the main thread.
                Uninterruptibles.awaitUninterruptibly(afterStarted);
                notifyFailed(new Exception("boom"));
              }

**FastAPI**では、これを**OAuth2**を使用して構築できます。

ですが、ちょっとした必要な情報を探すために、長い仕様のすべてを読む必要はありません。

**FastAPI**が提供するツールを使って、セキュリティを制御してみましょう。

## どう見えるか

まずはこのコードを使って、どう動くか観察します。その後で、何が起こっているのか理解しましょう。

## `main.py`を作成

`main.py`に、下記の例をコピーします:

{* ../../docs_src/security/tutorial001.py *}

## 実行

/// info | 情報

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[66:73] hl[71] *}

### Ejecutar la App

Puedes ejecutar la aplicación:

<div class="termy">

```console
$ fastapi dev main.py

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

    }

    @Override
    public int hashCode() {
        return items.hashCode();
    }

    // CHECKSTYLE_OFF: LineLength

    /**
     * Main to test version parsing and comparison.
     * <p>
     * To check how "1.2.7" compares to "1.2-SNAPSHOT", for example, you can issue

***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.

### Contributing code

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).