//  2. Only the node hosting the disk is responsible to perform the heal
func monitorLocalDisksAndHeal(ctx context.Context, z *erasureServerPools) {
	// Perform automatic disk healing when a disk is replaced locally.
	diskCheckTimer := time.NewTimer(defaultMonitorNewDiskInterval)
	defer diskCheckTimer.Stop()

	for {
		select {
		case <-ctx.Done():
			return
		case <-diskCheckTimer.C:

import java.net.InetAddress;
import java.net.NetworkInterface;
import java.net.SocketException;
import java.net.UnknownHostException;
import java.nio.ByteBuffer;
import java.util.Arrays;
import java.util.Locale;
import org.jspecify.annotations.Nullable;

/**
 * Static utility methods pertaining to {@link InetAddress} instances.
 *

Este será el archivo principal en tu aplicación que conecta todo.

### Importar `FastAPI`

Importas y creas una clase `FastAPI` como de costumbre.

Y podemos incluso declarar [dependencias globales](dependencies/global-dependencies.md){.internal-link target=_blank} que se combinarán con las dependencias para cada `APIRouter`:

```Python hl_lines="1  3  7" title="app/main.py"

	if err = verifyBinary(u, sha256Sum, releaseInfo, mode, bytes.NewReader(bin)); err != nil {
		peerResults[local] = madmin.ServerPeerUpdateStatus{
			Host:           local,
			Err:            err.Error(),
			CurrentVersion: Version,
		}
	} else {
		peerResults[local] = madmin.ServerPeerUpdateStatus{
			Host:           local,
			CurrentVersion: Version,
			UpdatedVersion: lrTime.Format(MinioReleaseTagTimeLayout),
		}
	}

  /** The exception that explains [errorCode]. Null if no exception was provided. */
  internal var errorException: IOException? = null

  init {
    if (headers != null) {
      check(!isLocallyInitiated) { "locally-initiated streams shouldn't have headers yet" }
      headersQueue += headers
    } else {
      check(isLocallyInitiated) { "remotely-initiated streams should have headers" }
    }
  }

  /**

@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):
    return {"item_name": item.name, "item_id": item_id}
```

Serwer powinien przeładować się automatycznie (ponieważ dodałeś `--reload` do komendy `uvicorn` powyżej).

### Zaktualizowana interaktywna dokumentacja API

Wejdź teraz na <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

    *   For TensorFlow versions prior v.2.18.0: Add CUDA paths to
        LD_LIBRARY_PATH and add the `cuda` option flag.

        ```bash
        export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
        export flags="--config=linux --config=cuda -k"
        ```

    For example, to run all tests under tensorflow/python, do:

    ```bash

### Auf einem entfernten Server

Wenn Sie einen entfernten Server (einen Cloud-Server, eine virtuelle Maschine, usw.) einrichten, können Sie am einfachsten Uvicorn (oder ähnliches) manuell ausführen, genau wie bei der lokalen Entwicklung.

Und es wird funktionieren und **während der Entwicklung** nützlich sein.

Wenn Ihre Verbindung zum Server jedoch unterbrochen wird, wird der **laufende Prozess** wahrscheinlich abstürzen.

          <description>
            The frequency for downloading updates - can be "always",
            "daily" (default), "interval:XXX" (in minutes) or "never"
            (only if it doesn't exist locally).
          </description>
          <type>String</type>
        </field>
        <field>
          <name>checksumPolicy</name>
          <version>1.0.0+</version>
          <description>

        .build()
    }

    companion object {
      /** Synthetic response header: the local time when the request was sent. */
      private val SENT_MILLIS = "${Platform.get().getPrefix()}-Sent-Millis"

      /** Synthetic response header: the local time when the response was received. */
      private val RECEIVED_MILLIS = "${Platform.get().getPrefix()}-Received-Millis"
    }
  }