单任务受控执行(15 态状态机 + 审计轨迹)、DAG 管道、Controller 门面。
执行器三个:线程(默认,含 async def 任务)、内联(同步 / 测试)、进程
(spawn 子进程:硬性停止、绕开 GIL、崩溃隔离)。
调度:并发额度 + 每桶限流 + 具名资源信号量(按标签)+ 优先级排队。
持久层:TaskStore 契约 + 内存 / SQLite / Postgres 实现,契约测试随包发布。
跨进程与多节点:写穿 / 读穿、指令通道与租约、owned_buckets 划界、reconcile。
CLI、12 个可直接运行的示例、docs/ 下 5 份文档。
门禁:ruff / ruff format / mypy(strict) 干净;
pytest 563 passed(44 skipped 是需要真实 Postgres 的那批);
带一台可连的 Postgres 时 607 passed。
120 lines
4.1 KiB
Python
120 lines
4.1 KiB
Python
"""示例 8:``@task`` 装饰器与 ``TaskContext``。
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演示四件事:
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* ``@task`` 把元数据写在函数旁边,``register_module`` 一次登记整个模块;
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* ``ctx.progress(...)`` 上报进度——它会进快照、进存储,并出现在 ``ps`` 的 PROGRESS 列;
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* ``ctx.log(...)`` 走标准库 ``logging``,logger 名字是 ``chongming_task.task.<task_id>``;
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* ``ctx.input(节点id)`` 取上游节点的返回值——管道之间真正能传值。
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运行::
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uv run python examples/08_task_context.py
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"""
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from __future__ import annotations
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import logging
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import sys
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import time
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from typing import Any
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from chongming_task import Controller, Pipeline, RetryPolicy, render_table, task
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@task(tags={"io"}, retry=RetryPolicy(max_attempts=2))
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def extract(ctx: Any, day: str) -> list[str]:
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"""按天抽取分区列表。"""
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ctx.log(f"开始抽取 {day}")
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partitions = [f"{day}/part{i}" for i in range(6)]
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for index, part in enumerate(partitions, start=1):
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ctx.checkpoint()
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ctx.progress(index, total=len(partitions), unit="partitions", message=part)
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time.sleep(0.05)
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return partitions
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@task
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def transform(ctx: Any, day: str) -> int:
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"""把上游抽出的分区逐个转换,返回处理条数。"""
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partitions = ctx.input("extract", [])
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ctx.log(f"待转换分区:{len(partitions)} 个")
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rows = 0
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for index, part in enumerate(partitions, start=1):
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ctx.checkpoint()
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rows += 100
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ctx.progress(index, total=len(partitions), unit="partitions", message=part)
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time.sleep(0.05)
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return rows
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@task
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def load(ctx: Any, day: str) -> str:
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"""入库:条数来自上游的返回值,而不是自己再算一遍。"""
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rows = ctx.input("transform", 0)
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ctx.log(f"{day} 共 {rows} 行待入库")
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for index in range(1, 5):
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ctx.checkpoint()
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ctx.progress(index, total=4, unit="batch")
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time.sleep(0.04)
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return f"{day}: {rows} 行已入库"
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def main() -> None:
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logging.basicConfig(
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level=logging.INFO,
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format="%(levelname)-7s %(name)s %(message)s",
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stream=sys.stdout,
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)
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controller = Controller(max_parallel=2)
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# ---- 一次登记整个模块 ----
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registered = controller.register_module(sys.modules[__name__])
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print("从 @task 元数据登记的:")
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for item in registered:
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print(f" {item.name:<10} tags={sorted(item.tags) or '-'} {item.description}")
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# ---- 串成管道:数据沿依赖流动 ----
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pipeline = Pipeline("daily-etl")
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extract_node = pipeline.node("extract", "2026-10-02", node_id="extract")
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transform_node = pipeline.node(
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"transform", "2026-10-02", node_id="transform", depends_on=[extract_node]
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)
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pipeline.node("load", "2026-10-02", node_id="load", depends_on=[transform_node])
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run = controller.submit_pipeline(pipeline)
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print(f"\n已提交管道 {run.run_id}\n")
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# ---- 跑的过程中看进度 ----
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deadline = time.monotonic() + 30
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while time.monotonic() < deadline and not run.settled:
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snapshots = controller.list_tasks(pipeline_run_id=run.run_id)
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cells: list[str] = []
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for snapshot in snapshots:
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node = snapshot.name.split("/", 1)[-1]
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progress = "-"
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if snapshot.progress is not None:
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progress = f"{snapshot.progress.done}/{snapshot.progress.total}"
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cells.append(f"{node:<10} {snapshot.status.value:<10} {progress:<8}")
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sys.stdout.write("\r" + " | ".join(cells).ljust(120))
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sys.stdout.flush()
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time.sleep(0.1)
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outcome = run.wait(timeout=30)
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print("\n\n--- 结束 ---")
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print(render_table(controller.list_tasks(pipeline_run_id=run.run_id)))
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print(f"\n管道结论:{outcome.status.value}")
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final = controller.get(run.task_id_of("load"))
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print(f"load 的返回值:{final.outcome if final else None}") # type: ignore[union-attr]
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controller.close(timeout=10)
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print(
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"\n要点:ctx 是任务与运行时之间唯一的协作入口——停止、暂停、进度、日志、上游数据都在这里。"
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)
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if __name__ == "__main__":
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main()
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