feat: 初始化PyFlowX轻量级DAG任务调度库

实现完整的DAG任务调度核心功能，包括：
1.  支持同步/异步/线程三种执行策略
2.  自动上下文注入，无需手动绑定任务依赖
3.  内置状态后端，支持断点续跑
4.  提供完整的测试用例与示例代码
5.  添加CI/CD配置与发布流程

examples/async_aggregation.py

@@ -0,0 +1,58 @@
+"""Example 3: async aggregation with static args and Context injection.
+
+Shows:
+  * async task functions executed with strategy="async".
+  * static positional args (TaskSpec.args) for parameterised tasks.
+  * Context annotation to receive the full upstream result mapping.
+  * on_event callback for real-time progress.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Any, Dict, List
+
+import pyflowx as px
+
+
+async def fetch_user(uid: int) -> dict:
+    await asyncio.sleep(0.2)
+    return {"id": uid, "name": f"User{uid}"}
+
+
+async def fetch_posts(uid: int) -> List[int]:
+    await asyncio.sleep(0.2)
+    return [uid, uid + 1]
+
+
+# Context annotation → receives the full mapping of upstream results.
+def aggregate(ctx: px.Context) -> Dict[str, Any]:
+    return dict(ctx)
+
+
+def main() -> None:
+    graph = px.Graph.from_specs(
+        [
+            # Static positional args parameterise the same function twice.
+            px.TaskSpec("fetch_user", fetch_user, args=(1,)),
+            px.TaskSpec("fetch_posts", fetch_posts, args=(1,)),
+            px.TaskSpec("aggregate", aggregate, ("fetch_user", "fetch_posts")),
+        ]
+    )
+
+    print("=== Dry run ===")
+    px.run(graph, strategy="async", dry_run=True)
+
+    events: List[px.TaskEvent] = []
+    print("\n=== Async execution ===")
+    report = px.run(graph, strategy="async", on_event=events.append)
+
+    for ev in events:
+        print(f"  event: {ev.task} -> {ev.status.value}")
+
+    print(f"\naggregate = {report['aggregate']}")
+    print(report.describe())
+
+
+if __name__ == "__main__":
+    main()