<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)
```

      <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>

	}

	// Verify the header matches a known format.
	format := tr.blk.getFormat()
	if format == FormatUnknown {
		return nil, nil, ErrHeader
	}

	var p parser
	hdr := new(Header)

	// Unpack the V7 header.
	v7 := tr.blk.toV7()
	hdr.Typeflag = v7.typeFlag()[0]
	hdr.Name = p.parseString(v7.name())
	hdr.Linkname = p.parseString(v7.linkName())
	hdr.Size = p.parseNumeric(v7.size())

            "names (",
            n->name(),
            "). This is a bug. Please file an issue at "
            "https://github.com/tensorflow/tensorflow/issues.");
      }
    }
  }

  // Unpack the results from grad_outputs_arg.
  TFOutputsFromOutputs(dy_arg, dy);
#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

// TF_Session functions ----------------------------------------------

are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
`tf.pack` and `tf.unpack` are deprecated in favor of `tf.stack` and
`tf.unstack`. * `TensorArray.pack` and `TensorArray.unpack` are getting
deprecated in favor of `TensorArray.stack` and `TensorArray.unstack`. * The
following Python functions have had their arguments changed to use `axis` when

			delete(n.lockMap, resource)
		}
		n.lockMapMutex.Unlock()
	}

	return locked
}

// Unlock the namespace resource.
func (n *nsLockMap) unlock(volume string, path string, readLock bool) {
	resource := pathJoin(volume, path)

	n.lockMapMutex.Lock()
	defer n.lockMapMutex.Unlock()
	if _, found := n.lockMap[resource]; !found {
		return
	}
	if readLock {

		if recover() == nil {
			t.Fatalf("unlock of unlocked RWMutex did not panic")
		}
	}()
	mu := NewLRWMutex()
	mu.Unlock()
}

// Borrowed from rwmutex_test.go
func TestUnlockPanic2(t *testing.T) {
	defer func() {
		if recover() == nil {
			t.Fatalf("unlock of unlocked RWMutex did not panic")
		}
	}()
	mu := NewLRWMutex()
	mu.RLock()
	mu.Unlock()
}

// Borrowed from rwmutex_test.go

	defer func() {
		if recover() == nil {
			t.Fatalf("unlock of unlocked RWMutex did not panic")
		}
	}()
	mu := NewDRWMutex(ds, "test")
	mu.Unlock(t.Context())
}

// Borrowed from rwmutex_test.go
func TestUnlockPanic2(t *testing.T) {
	mu := NewDRWMutex(ds, "test-unlock-panic-2")
	defer func() {
		if recover() == nil {
			t.Fatalf("unlock of unlocked RWMutex did not panic")
		}

func (r *RingBuffer) Reset() {
	r.mu.Lock()
	defer r.mu.Unlock()

	// Set error so any readers/writers will return immediately.
	r.setErr(errors.New("reset called"), true)
	if r.block {
		r.readCond.Broadcast()
		r.writeCond.Broadcast()
	}

	// Unlock the mutex so readers/writers can finish.
	r.mu.Unlock()
	r.wg.Wait()
	r.mu.Lock()
	r.r = 0
	r.w = 0
	r.err = nil