import org.apache.maven.api.annotations.Experimental;
import org.apache.maven.api.annotations.Nonnull;

/**
 * Service for detecting and providing information about the operating system (OS)
 * on which the application is running.
 * <p>
 * This service provides a platform-independent way to:
 * <ul>
 * <li>Query basic OS information like name, architecture, and version</li>
 * <li>Determine the OS family (e.g., Windows, Unix, Mac)</li>

	return &Reader{
		args:       args,
		decoder:    d,
		valueCh:    d.Stream(),
		readCloser: readCloser,
	}
}

// syncReadCloser will wrap a readcloser and make it safe to call Close while
// reads are running.
type syncReadCloser struct {
	rc io.ReadCloser
	mu sync.Mutex
}

func (pr *syncReadCloser) Read(p []byte) (n int, err error) {
	// This ensures that Close will block until Read has completed.

             Logs:

     <span style="background-color:#007166"><font color="#D3D7CF"> INFO </font></span>  Uvicorn running on <font color="#729FCF"><u style="text-decoration-style:solid">http://0.0.0.0:8000</u></font> <b>(</b>Press CTRL+C to
             quit<b>)</b>

EOF
    find . | tr '[A-Z]' '[a-z]' | sort | uniq -d | tee $BATS_FILE_TMPDIR/repeats
    [[ ! -s $BATS_FILE_TMPDIR/repeats ]]
}

# It's unclear why, but running this on //tensorflow/... is faster than running
# only on affected targets, usually. There are targets in //tensorflow/lite that
# don't pass --nobuild, so they're on their own.
#

          @Override
          public void tearDown() throws Exception {
            synchronized (result.lock) {
              assertEquals(
                  "The test should have cleared the stack (say, by virtue of running runTearDown)",
                  0,
                  result.stack.size());
            }
          }
        });
    return result;
  }

Ahora, ejecuta el comando `fastapi` con tu archivo:

<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>

Y abre la documentación en <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

Agora, execute o comando `fastapi` com o seu arquivo:

<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>

E abra a documentação em <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

### 자동으로 생성된 API 문서 확인

이제, `uvicorn`으로 메인 응용프로그램을 실행하십시오. 당신의 파일이 `main.py`라면, 이렇게 실행합니다:

<div class="termy">

```console
$ uvicorn main:app --reload

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

</div>

그리고 <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>에서 문서를 여십시오.

You also need to run `mvn clean verify` with Java 8 before committing changes.

If you have ktlint errors, you can automatically fix them by running `mvn com.github.gantsign.maven:ktlint-maven-plugin:1.1.1:format`.

## How the configuration works

We use Kotlin portable DSL to store TeamCity configuration, which means you can easily create a new pipeline

 |
 |                 NOTE: This location can be overridden with the CLI option:
 |
 |                 -it /path/to/installation/toolchains.xml
 |
 | The sections in this sample file are intended to give you a running start at
 | getting the most out of your Maven installation.
 |-->
<toolchains xmlns="http://maven.apache.org/TOOLCHAINS/1.1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"