print(user_dict)
```

we would get a Python `dict` with:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    '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.

print(user_dict)
```

我們會得到一個 Python `dict`：

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

#### 解包 `dict` { #unpacking-a-dict }

若將像 `user_dict` 這樣的 `dict` 以 `**user_dict` 傳給函式（或類別），Python 會將其「解包」，把 `user_dict` 的鍵和值直接當作具名引數傳入。

因此，延續上面的 `user_dict`，寫成：

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

效果等同於：

```Python

  # "Tag: <new whl tag>"
  sed -i "s/^Tag:.*/Tag: ${whl_tag}/g" "${pkg_name}"/"${pkg_name}".dist-info/WHEEL

  # Repack the wheel. When repacking, the wheel would be automatically tagged
  # with the new tag we provided in ${whl_tag}. Repacking also regnerates the
  # RECORD file which contains hashes of all included files.
  python3 -m wheel pack "${pkg_name}"
done

You might want to have some predefined responses that apply to many *path operations*, but you want to combine them with custom responses needed by each *path operation*.

For those cases, you can use the Python technique of "unpacking" a `dict` with `**dict_to_unpack`:

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

	AmzObjectLockBypassGovernance = "X-Amz-Bypass-Governance-Retention"
	AmzBucketReplicationStatus    = "X-Amz-Replication-Status"

	// AmzSnowballExtract will trigger unpacking of an archive content
	AmzSnowballExtract = "X-Amz-Meta-Snowball-Auto-Extract"
	// MinIOSnowballIgnoreDirs will skip creating empty directory objects.
	MinIOSnowballIgnoreDirs = "X-Amz-Meta-Minio-Snowball-Ignore-Dirs"

import org.jspecify.annotations.Nullable;

/**
 * A hash function is a collision-averse pure function that maps an arbitrary block of data to a
 * number called a <i>hash code</i>.
 *
 * <h3>Definition</h3>
 *
 * <p>Unpacking this definition:
 *
 * <ul>
 *   <li><b>block of data:</b> the input for a hash function is always, in concept, an ordered byte
 *       array. This hashing API accepts an arbitrary sequence of byte and multibyte values (via

      if (casValue(this, null, valueToSet)) {
        // the listener is responsible for calling completeWithFuture, directExecutor is appropriate
        // since all we are doing is unpacking a completed future which should be fast.
        try {
          future.addListener(valueToSet, DirectExecutor.INSTANCE);
        } catch (Throwable t) {

```

ми отримаємо Python `dict` з:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

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

Якщо взяти `dict`, наприклад `user_dict`, і передати його у функцію (або клас) як `**user_dict`, Python «розпакує» його. Ключі та значення `user_dict` будуть передані безпосередньо як іменовані аргументи.

nous obtiendrions un `dict` Python contenant :

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

#### Déballer un `dict` { #unpacking-a-dict }

print(user_dict)
```

输出的就是 Python `dict`：

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

#### 解包 `dict` { #unpacking-a-dict }

把 `dict`（如 `user_dict`）以 `**user_dict` 形式传递给函数（或类），Python 会执行“解包”。它会把 `user_dict` 的键和值作为关键字参数直接传递。

因此，接着上面的 `user_dict` 继续编写如下代码：

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

就会生成如下结果：