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
	}

   * {@code '-'} (<code>'&#92;u002D'</code>) is recognized as the minus sign.
   *
   * <p>Unlike {@link Float#parseFloat(String)}, this method returns {@code null} instead of
   * throwing an exception if parsing fails. Valid inputs are exactly those accepted by {@link
   * Float#valueOf(String)}, except that leading and trailing whitespace is not permitted.
   *
   * <p>This implementation is likely to be faster than {@code Float.parseFloat} if many failures

   * {@code '-'} (<code>'&#92;u002D'</code>) is recognized as the minus sign.
   *
   * <p>Unlike {@link Float#parseFloat(String)}, this method returns {@code null} instead of
   * throwing an exception if parsing fails. Valid inputs are exactly those accepted by {@link
   * Float#valueOf(String)}, except that leading and trailing whitespace is not permitted.
   *
   * <p>This implementation is likely to be faster than {@code Float.parseFloat} if many failures

labels.webApiJson=JSON-Antwort
labels.webConfigName=Web-Konfigurationsname
labels.allLanguages=Alle Sprachen
labels.dictId=Wörterbuch-ID
labels.docId=Dokument-ID
labels.endTime=Endzeitpunkt
labels.hq=hq
labels.inputs=Quelle
labels.jobLogging=Protokollierung
labels.jobName=Name
labels.jobStatus=Status
labels.labelTypeIds=Label
labels.lang=Sprache
labels.outputs=Ziel
labels.pos=POS

		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 {

        },
        "enable": true,
        "hide": true,
        "iconColor": "rgba(0, 211, 255, 1)",
        "name": "Annotations & Alerts",
        "type": "dashboard"
      }
    ]
  },
 "__inputs": [
    { 
      "name": "DS_PROMETHEUS",
      "label": "Prometheus",
      "description": "",
      "type": "datasource",
      "pluginId": "prometheus",
      "pluginName": "Prometheus"
    } 
  ],    

* 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

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

    * Errores automáticos y claros cuándo los datos son inválidos.
    * Validación, incluso para objetos JSON profundamente anidados.
* <abbr title="en inglés: serialization, parsing, marshalling">Conversión</abbr> de datos de input: viniendo de la red a datos y tipos de Python. Leyendo desde:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Formularios.
    * Archivos.