buf    bytes.Buffer
}

func newExitCodeFilter(w io.Writer) (*exitCodeFilter, string) {
	const exitStr = "exitcode="

	// Build a regexp that matches any prefix of the exit string at the end of
	// the input. We do it this way to avoid assuming anything about the
	// subcommand output (e.g., it might not be \n-terminated).
	var exitReStr strings.Builder
	for i := 1; i <= len(exitStr); i++ {

    private val responseHeaders: Headers
    private val handshake: Handshake?
    private val sentRequestMillis: Long
    private val receivedResponseMillis: Long

    /**
     * Reads an entry from an input stream. A typical entry looks like this:
     *
     * ```
     * http://google.com/foo
     * GET
     * 2
     * Accept-Language: fr-CA
     * Accept-Charset: UTF-8
     * HTTP/1.1 200 OK
     * 3

  /**
   * Returns a {@link Collector} that accumulates elements into an {@code ImmutableBiMap} whose keys
   * and values are the result of applying the provided mapping functions to the input elements.
   * Entries appear in the result {@code ImmutableBiMap} in encounter order.
   *
   * <p>If the mapped keys or values contain duplicates (according to {@link

接下来，它 🤖 完成第一个任务（比如是我们的"慢文件"📝) 并继续与之相关的一切。

这个"等待其他事情"通常指的是一些相对较慢（与处理器和 RAM 存储器的速度相比）的 <abbr title="Input and Output">I/O</abbr> 操作，比如说：

* 通过网络发送来自客户端的数据
* 客户端接收来自网络中的数据
* 磁盘中要由系统读取并提供给程序的文件的内容
* 程序提供给系统的要写入磁盘的内容
* 一个 API 的远程调用
* 一个数据库操作，直到完成
* 一个数据库查询，直到返回结果
* 等等.

这个执行的时间大多是在等待 <abbr title="Input and Output">I/O</abbr> 操作，因此它们被叫做 "I/O 密集型" 操作。

}

// Maximum 4KiB size per object retention config.
const maxObjectRetentionSize = 1 << 12

// ParseObjectRetention constructs ObjectRetention struct from xml input
func ParseObjectRetention(reader io.Reader) (*ObjectRetention, error) {
	ret := ObjectRetention{}
	if err := xml.NewDecoder(io.LimitReader(reader, maxObjectRetentionSize)).Decode(&ret); err != nil {
		return nil, err
	}

  }

  /**
   * Constructs a {@code LinkedListMultimap} with the same mappings as the specified {@code
   * Multimap}. The new multimap has the same {@link Multimap#entries()} iteration order as the
   * input multimap.
   *
   * @param multimap the multimap whose contents are copied to this multimap
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>

   *
   * <p>Only one underlying stream will be open at a time. Closing the concatenated stream will
   * close the open underlying stream.
   *
   * <p>Note: The input {@code Iterator} will be copied to an {@code ImmutableList} when this method
   * is called. This will fail if the iterator is infinite and may cause problems if the iterator

		c2 := n - c1
		copy(p[c1:], r.buf[0:c2])
	}
	r.r = (r.r + n) % r.size

	r.isFull = false

	return n, r.readErr(true)
}

// ReadByte reads and returns the next byte from the input or ErrIsEmpty.
func (r *RingBuffer) ReadByte() (b byte, err error) {
	r.mu.Lock()
	defer r.mu.Unlock()
	if err = r.readErr(true); err != nil {
		return 0, err
	}
	for r.w == r.r && !r.isFull {

* The repository model where plugins can be stored and cataloged
* Bridging this into an OSGi system: if this could be done then we can basically take over p2

TODO

- dealing with processing of input and adapting GAVs before searching i.e. plugin groups in Maven and default searching
- how to deal with resolution from different places like local/remote/workspace
- how to incorporate the metadata processor to start with

performance (cerca de 100 nanosegundos), por favor observe que no **FastAPI** o efeito pode ser bem o oposto. Nesses casos, é melhor usar `async def` a menos que suas *funções de operação de rota* utilizem código que performem bloqueamento <abbr title="Input/Output: disco lendo ou escrevendo, comunicações de rede.">IO</abbr>.

Ainda, em ambas as situações, as chances são que o **FastAPI** será [ainda mais rápido](index.md#performance){.internal-link target=_blank} do que (ou ao menos comparável...