</plugin>
      <plugin>
        <artifactId>maven-dependency-plugin</artifactId>
        <executions>
          <execution>
            <id>unpack-failureaccess-sources</id>
            <phase>generate-resources</phase>
            <goals><goal>unpack-dependencies</goal></goals>
            <configuration>
              <includeArtifactIds>failureaccess</includeArtifactIds>
              <classifier>sources</classifier>

      <plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-dependency-plugin</artifactId>
        <executions>
          <execution>
            <id>unpack-jline-native</id>
            <goals>
              <goal>unpack-dependencies</goal>
            </goals>
            <configuration>
              <includeArtifactIds>jline-native</includeArtifactIds>

    'full_name': None,
}
```

#### Unpacking a `dict` { #unpacking-a-dict }

If we take a `dict` like `user_dict` and pass it to a function (or class) with `**user_dict`, Python will "unpack" it. It will pass the keys and values of the `user_dict` directly as key-value arguments.

So, continuing with the `user_dict` from above, writing:

```Python
UserInDB(**user_dict)
```

    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

#### `dict` 언패킹(Unpacking)

`user_dict`와 같은 `dict`를 함수(또는 클래스)에 `**user_dict`로 전달하면, Python은 이를 "언팩(unpack)"합니다. 이 과정에서 `user_dict`의 키와 값을 각각 키-값 인자로 직접 전달합니다.

따라서, 위에서 생성한 `user_dict`를 사용하여 다음과 같이 작성하면:

```Python
UserInDB(**user_dict)
```

다음과 같은 결과를 생성합니다:

```Python
UserInDB(
    username="john",

				</configuration>
			</plugin>
			<plugin>
				<artifactId>maven-dependency-plugin</artifactId>
				<executions>
					<execution>
						<id>unpack-provided</id>
						<phase>generate-resources</phase>
						<goals>
							<goal>unpack-dependencies</goal>
						</goals>
						<configuration>
							<includeScope>provided</includeScope>

        }

        iterator = topMetaIterator.next();

        if (iterator instanceof ConcatenatedIterator) {
          // Instead of taking linear time in the number of nested concatenations, unpack
          // them into the queue
          @SuppressWarnings("unchecked")
          ConcatenatedIterator<T> topConcat = (ConcatenatedIterator<T>) iterator;
          iterator = topConcat.iterator;

import okio.buffer

/**
 * Read and write HPACK v10.
 *
 * http://tools.ietf.org/html/draft-ietf-httpbis-header-compression-12
 *
 * This implementation uses an array for the dynamic table and a list for indexed entries. Dynamic
 * entries are added to the array, starting in the last position moving forward. When the array
 * fills, it is doubled.
 */
@Suppress("NAME_SHADOWING")
object Hpack {
  private const val PREFIX_4_BITS = 0x0f

  //   system scheduling and as such we could either miss our deadline, or unpark() could be delayed
  //   so that it looks like we timed out even though we didn't. For comparison FutureTask respects
  //   completion preferably and AQS is non-deterministic (depends on where in the queue the waiter
  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node

  //   system scheduling and as such we could either miss our deadline, or unpark() could be delayed
  //   so that it looks like we timed out even though we didn't. For comparison FutureTask respects
  //   completion preferably and AQS is non-deterministic (depends on where in the queue the waiter
  //   is). If we wanted to be strict about it, we could store the unpark() time in the Waiter node

            guidToHandle.put(guid, info);

            if (type == HandleType.PERSISTENT) {
                persistHandle(info);
            }
        } finally {
            lock.writeLock().unlock();
        }

        log.debug("Requested {} handle for path: {}", type, path);
        return guid;
    }

    /**
     * Update the file ID for a handle after successful create response