feat: detect-batch adds --json output and --algo single-algo mode

ts_anomaly_td/cli.py

@@ -35,18 +35,49 @@ def cmd_detect_batch(args):
     """detect-batch 子命令：多算法 ANOMALY_WINDOW。"""
     logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
 
-    algos = args.algos.split(",") if args.algos else ALL_ALGOS
+    # 确定算法列表（--algo 优先于 --algos）
+    if args.algo:
+        algos = [args.algo]
+    elif args.algos:
+        algos = args.algos.split(",")
+    else:
+        algos = ALL_ALGOS
 
     conn = TDConnection(args.url)
     try:
         db = args.db or "ts_anomaly"
         conn.execute_no_result(f"USE {db}")
         results = detect_all_algos(conn, args.stable, algos=algos)
-        for algo, r in results.items():
-            if r["error"]:
-                print(f"  {algo}: ERROR - {r['error']}")
+
+        if getattr(args, 'json_output', False):
+            import json
+            if len(algos) == 1:
+                algo_name = algos[0]
+                r = results[algo_name]
+                output = {
+                    "algo": algo_name,
+                    "stable": args.stable,
+                    "windows": r["windows"],
+                    "window_count": len(r["windows"]),
+                    "error": r["error"],
+                }
             else:
-                print(f"  {algo}: {len(r['windows'])} windows")
+                output = []
+                for algo_name, r in results.items():
+                    output.append({
+                        "algo": algo_name,
+                        "stable": args.stable,
+                        "windows": r["windows"],
+                        "window_count": len(r["windows"]),
+                        "error": r["error"],
+                    })
+            print(json.dumps(output, ensure_ascii=False))
+        else:
+            for algo, r in results.items():
+                if r["error"]:
+                    print(f"  {algo}: ERROR - {r['error']}")
+                else:
+                    print(f"  {algo}: {len(r['windows'])} windows")
     finally:
         conn.close()
 
@@ -134,6 +165,7 @@ def build_parser() -> argparse.ArgumentParser:
     p_inj.add_argument("--csv", required=True, help="CSV 文件路径")
     p_inj.add_argument("--stable", required=True, help="supertable 名称")
     p_inj.add_argument("--db", default="ts_anomaly", help="数据库名 (default: ts_anomaly)")
+    p_inj.add_argument("--value-col", default="value", help="数值列名 (default: value)")
     p_inj.add_argument("--url", default="ws://root:taosdata@localhost:6041", help="TDengine WebSocket URL")
 
     # detect-batch
@@ -141,6 +173,8 @@ def build_parser() -> argparse.ArgumentParser:
     p_det.add_argument("--stable", required=True, help="supertable 名称")
     p_det.add_argument("--db", default="ts_anomaly", help="数据库名")
     p_det.add_argument("--algos", default=None, help="逗号分隔算法列表 (默认全 6 个)")
+    p_det.add_argument("--algo", default=None, help="单算法模式（优先于 --algos）")
+    p_det.add_argument("--json", action="store_true", dest="json_output", help="输出 JSON 到 stdout")
     p_det.add_argument("--url", default="ws://root:taosdata@localhost:6041", help="TDengine WebSocket URL")
 
     # forecast-anomaly