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/etl_pipeline.py

@@ -0,0 +1,81 @@
+"""Example 1: ETL pipeline (sequential strategy).
+
+Demonstrates the core PyFlowX workflow:
+  * Define tasks as plain functions.
+  * Declare the DAG with a list of TaskSpec.
+  * Parameter names == dependency names → automatic context injection,
+    no wrappers needed (contrast with flowweaver's get_task_result boilerplate).
+  * dry_run to preview, then execute and read typed results from RunReport.
+"""
+
+from __future__ import annotations
+
+from typing import List
+
+import pyflowx as px
+
+# --- task functions: pure, testable, no framework coupling ------------- #
+
+
+def extract_customers() -> List[dict]:
+    return [
+        {"id": "C001", "name": "Alice"},
+        {"id": "C002", "name": "Bob"},
+    ]
+
+
+def extract_orders() -> List[dict]:
+    return [
+        {"id": "O001", "customer_id": "C001", "amount": 150.0},
+        {"id": "O002", "customer_id": "C002", "amount": 200.5},
+    ]
+
+
+# Parameter names match dependency names → automatic injection.
+def transform(
+    extract_customers: List[dict],
+    extract_orders: List[dict],
+) -> List[dict]:
+    cmap = {c["id"]: c for c in extract_customers}
+    return [
+        {**o, "customer_name": cmap[o["customer_id"]]["name"]}
+        for o in extract_orders
+        if o["customer_id"] in cmap
+    ]
+
+
+def load(transform: List[dict]) -> int:
+    print(f"  loaded {len(transform)} records")
+    return len(transform)
+
+
+def main() -> None:
+    graph = px.Graph.from_specs(
+        [
+            px.TaskSpec("extract_customers", extract_customers, tags=("extract",)),
+            px.TaskSpec("extract_orders", extract_orders, tags=("extract",)),
+            px.TaskSpec(
+                "transform",
+                transform,
+                ("extract_customers", "extract_orders"),
+                tags=("transform",),
+            ),
+            px.TaskSpec("load", load, ("transform",), retries=1, tags=("load",)),
+        ]
+    )
+
+    print("=== Execution plan ===")
+    print(graph.describe())
+
+    print("\n=== Dry run (no execution) ===")
+    px.run(graph, strategy="sequential", dry_run=True)
+
+    print("\n=== Sequential execution ===")
+    report = px.run(graph, strategy="sequential")
+    print(report.describe())
+    print(f"\nload result = {report['load']}")
+    print(f"summary = {report.summary()}")
+
+
+if __name__ == "__main__":
+    main()