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hello-datap-component-base

数据处理平台组件 SDK:统一入参/出参、Ray 分布式日志、数据跟踪(track)、结果投递(OSS + MNS)。

当前版本:0.5.7

安装

pip install hello-datap-component-base

Ray 集群由平台或作业入口初始化,组件代码内无需 ray.init()。

集成方式(推荐:提示词)

不要从零对照 API 手写骨架。 将下方提示词交给 Cursor / Copilot 等 AI,附上你的业务描述,即可生成符合平台规范的完整组件代码。

场景 提示词文件 SDK 要求
普通流水线节点(自行 ray.get 批量聚合) prompts/普通组件集成提示词.md ≥ 0.4.10
流水线已开启 「DAG 流式执行 / DAG 漏斗视角」 prompts/DAG流式组件集成提示词.md ≥ 0.5.0

如何选型

流水线「高级」里是否勾选「启用 DAG 流式执行」?
├── 否 → 用「普通组件」提示词,继承 BaseService
└── 是 → 用「DAG 流式」提示词,继承 DagStreamingService(自动 dagStream 计数 + 并发/超时)

提示词内已包含:Ray runtime_env 透传、logger / track 用法、失败隔离、代码骨架。以提示词为准,本文不再重复展开。

参考示例

提交远程 Ray 集群前,可先对照仓库内完整 Demo:

目录 类型 说明
examples/batch_compute/ 普通组件 加减乘除批量计算,BaseService + ray.get
examples/dag_streaming/ DAG 流式 同上业务,含 outputResult.dagStream

各子目录含 service.py + config.json,运行方式见对应 README.md。

运行组件

component_manager start <config.json> --class-name <YourServiceClass>

等价:python -m hello_datap_component_base.cli start ...

常用子命令:list · validate · test

配置要点

config.json 中 params 会作为 process(data) / extract_items(params) 的入参;平台注入的跟踪、MNS、OSS 等变量写在 runtime_env.env_vars 或由平台下发(提示词中说明如何传给 Ray worker)。

最小字段:name(必需)、version、work_flow_id、work_flow_instance_id、task_id、runtime_env、params。

返回格式

框架将业务 process 返回值包在 data.out_put 中;整体结构:

{
  "code": 0,
  "message": "success",
  "processing_time": 0.12,
  "data": {
    "work_flow_id": 123,
    "work_flow_instance_id": 456,
    "task_id": "task-001",
    "out_put": { }
  }
}

失败时 code = -1,out_put 为 null。DAG 流式组件的业务结果与 dagStream 字段同在 out_put 内(详见 DAG 提示词)。

SDK 能力一览

模块 用途
BaseService 普通组件基类
DagStreamingService DAG 流式组件(v0.5.0+)
logger Header / 按数据 key 分文件的 Ray 业务日志,可上传 OSS
track 数据跟踪,两段式上报 MNS
tools extract_specific_env_vars()、bag 路径解析等

项目结构

hello_datap_component_base/   # SDK 源码
prompts/                      # 集成提示词(推荐入口)
examples/                     # 可运行的参考 Demo
tests/

许可证

MIT License

Metadata

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