184 lines
8.5 KiB
Python
184 lines
8.5 KiB
Python
import json
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from fam_edge.oracle_db import OracleDB
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def _db(tmp_path):
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return OracleDB(str(tmp_path / "oracle.db"))
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def _set_heartbeat_age(db, age_sec):
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"""把心跳时间戳直接改写成"距现在 age_sec 秒前"，用于测试新鲜度阈值边界。"""
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from datetime import datetime, timedelta, timezone
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ts = (datetime.now(timezone(timedelta(hours=8))) - timedelta(seconds=age_sec))
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db.set_cursor('motion_heartbeat_at', ts.strftime('%Y-%m-%d %H:%M:%S'))
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def test_upsert_person_same_gender_merges_into_one_row(tmp_path):
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db = _db(tmp_path)
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db.upsert_person("人物A", features={"gender": "男", "hair": "短发黑色"})
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db.upsert_person("人物A", features={"gender": "男", "clothing": "蓝色T恤"})
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rows = db._conn.execute("SELECT * FROM people").fetchall()
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assert len(rows) == 1
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assert rows[0]["appearances"] == 2
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feats = json.loads(rows[0]["features_json"])
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assert feats["hair"] == "短发黑色"
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assert feats["clothing"] == "蓝色T恤"
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def test_upsert_person_gender_conflict_splits_into_new_label(tmp_path):
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"""核心诉求: 大模型给的 人物A/B/C 这类 uid 只在单次视频分析内稳定，不同视频
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独立编号，同一字符串完全可能撞到不同真人（实测 "人物A" 混了男女两个人）。
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性别冲突时不能直接合并覆盖，要拆成新 label，避免两个人的特征越merge越乱。"""
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db = _db(tmp_path)
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db.upsert_person("人物A", features={"gender": "男", "clothing": "蓝色Polo衫"})
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db.upsert_person("人物A", features={"gender": "女", "clothing": "白色上衣"})
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rows = {r["label"]: r for r in db._conn.execute("SELECT * FROM people").fetchall()}
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assert set(rows.keys()) == {"人物A", "人物A#2"}
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assert rows["人物A"]["appearances"] == 1
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assert json.loads(rows["人物A"]["features_json"])["gender"] == "男"
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assert rows["人物A#2"]["appearances"] == 1
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assert json.loads(rows["人物A#2"]["features_json"])["gender"] == "女"
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# 派生行的 display_uid 仍然记录原始大模型 uid，方便追溯来源
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assert rows["人物A#2"]["display_uid"] == "人物A"
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def test_upsert_person_gender_conflict_allocates_next_free_suffix(tmp_path):
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db = _db(tmp_path)
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db.upsert_person("人物A", features={"gender": "男"})
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db.upsert_person("人物A", features={"gender": "女"}) # -> 人物A#2
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db.upsert_person("人物A", features={"gender": "unknown"}) # unknown 不冲突，合并回 人物A
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db.upsert_person("人物A", features={"gender": "男", "hair": "光头"}) # 冲突，人物A 有 gender 男了不冲突；应仍合并
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labels = {r["label"] for r in db._conn.execute("SELECT label FROM people").fetchall()}
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assert labels == {"人物A", "人物A#2"}
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# 再来一次性别冲突（对着 人物A#2，性别女）应该分配 人物A#3，而不是复用 人物A#2
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db.upsert_person("人物A", features={"gender": "男"})
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db.upsert_person("人物A", features={"gender": "女"})
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# 这次新的女性冲突会先撞到 人物A（此时是男），分裂出下一个空闲后缀
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labels = {r["label"] for r in db._conn.execute("SELECT label FROM people").fetchall()}
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assert "人物A" in labels
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assert len(labels) >= 2
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def test_upsert_person_unknown_gender_never_triggers_split(tmp_path):
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db = _db(tmp_path)
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db.upsert_person("人物A", features={"gender": "男"})
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db.upsert_person("人物A", features={"gender": "unknown"})
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db.upsert_person("人物A", features={"gender": "未知"})
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rows = db._conn.execute("SELECT * FROM people").fetchall()
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assert len(rows) == 1
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assert rows[0]["appearances"] == 3
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def test_upsert_person_no_features_never_triggers_split(tmp_path):
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db = _db(tmp_path)
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db.upsert_person("人物A", features={"gender": "男"})
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db.upsert_person("人物A") # 无 features（source 更新等场景）
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rows = db._conn.execute("SELECT * FROM people").fetchall()
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assert len(rows) == 1
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assert rows[0]["appearances"] == 2
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# ----------------------------------------------------------------------
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# 运动侦测事件（NAS 推送）
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# ----------------------------------------------------------------------
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def test_record_motion_events_upserts_by_event_id(tmp_path):
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db = _db(tmp_path)
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n = db.record_motion_events([
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{"event_id": 1, "camera_id": 2, "event_type": 10, "start_time": 1000, "duration": 5},
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{"event_id": 2, "camera_id": 2, "event_type": 10, "start_time": 2000, "duration": 3},
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])
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assert n == 2
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rows = db._conn.execute("SELECT * FROM ss_motion_events ORDER BY event_id").fetchall()
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assert len(rows) == 2
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# 重复推送同一个 event_id（幂等）应该更新而不是新增一行
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 2, "event_type": 10, "start_time": 1000, "duration": 99}])
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rows = db._conn.execute("SELECT * FROM ss_motion_events").fetchall()
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assert len(rows) == 2
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updated = db._conn.execute(
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"SELECT duration FROM ss_motion_events WHERE event_id=1").fetchone()
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assert updated['duration'] == 99
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def test_record_motion_events_skips_missing_event_id(tmp_path):
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db = _db(tmp_path)
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n = db.record_motion_events([{"camera_id": 2, "start_time": 1000}])
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assert n == 0
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def test_heartbeat_age_none_when_never_recorded(tmp_path):
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db = _db(tmp_path)
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assert db.get_motion_heartbeat_age_sec() is None
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def test_heartbeat_age_near_zero_right_after_recording(tmp_path):
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db = _db(tmp_path)
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db.record_motion_heartbeat()
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age = db.get_motion_heartbeat_age_sec()
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assert age is not None and age < 5
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def test_has_motion_in_range_local_fails_open_without_heartbeat(tmp_path):
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"""核心诉求: 从未收到过心跳（冷启动，NAS 推送链路还没接上）必须 fail-open，
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不能因为本地表是空的就悄悄跳过分析。"""
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db = _db(tmp_path)
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assert db.has_motion_in_range_local(1000, 2000) is None
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def test_has_motion_in_range_local_fails_open_when_heartbeat_stale(tmp_path):
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"""核心诉求: 表里有大量历史运动事件（曾经推送链路是健康的），但心跳已经
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过期太久（NAS 服务挂了/网络断了/DSM Webhook 规则被误关）——这时候不能信任
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"查询结果是 0 条 = 确认无运动"，必须当作链路已死，fail-open。"""
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db = _db(tmp_path)
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 2, "event_type": 10, "start_time": 500, "duration": 10}])
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_set_heartbeat_age(db, 1000) # 超过默认阈值 900s
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assert db.has_motion_in_range_local(2000, 3000, max_heartbeat_age_sec=900) is None
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def test_has_motion_in_range_local_trusts_result_when_heartbeat_fresh(tmp_path):
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db = _db(tmp_path)
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db.record_motion_heartbeat()
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assert db.has_motion_in_range_local(2000, 3000, max_heartbeat_age_sec=900) is False
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 2, "event_type": 10, "start_time": 2500, "duration": 5}])
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assert db.has_motion_in_range_local(2000, 3000, max_heartbeat_age_sec=900) is True
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def test_has_motion_in_range_local_respects_heartbeat_boundary(tmp_path):
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db = _db(tmp_path)
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_set_heartbeat_age(db, 899)
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assert db.has_motion_in_range_local(2000, 3000, max_heartbeat_age_sec=900) is not None
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_set_heartbeat_age(db, 901)
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assert db.has_motion_in_range_local(2000, 3000, max_heartbeat_age_sec=900) is None
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def test_has_motion_in_range_local_overlap_semantics(tmp_path):
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"""事件区间 [start_time, start_time+duration] 只要和查询窗口有重叠就算命中，
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不要求事件完全落在窗口内部（也不要求窗口完全覆盖事件）。"""
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db = _db(tmp_path)
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db.record_motion_heartbeat()
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# 事件在窗口开始之前就开始，但持续到窗口内 -> 应该命中
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 2, "event_type": 10, "start_time": 1990, "duration": 20}])
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assert db.has_motion_in_range_local(2000, 3000) is True
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def test_has_motion_in_range_local_ignores_non_motion_event_type(tmp_path):
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db = _db(tmp_path)
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db.record_motion_heartbeat()
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 2, "event_type": 99, "start_time": 2500, "duration": 5}])
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assert db.has_motion_in_range_local(2000, 3000) is False
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def test_has_motion_in_range_local_filters_by_camera_id(tmp_path):
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db = _db(tmp_path)
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db.record_motion_heartbeat()
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db.record_motion_events(
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[{"event_id": 1, "camera_id": 99, "event_type": 10, "start_time": 2500, "duration": 5}])
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assert db.has_motion_in_range_local(2000, 3000, camera_id=2) is False
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assert db.has_motion_in_range_local(2000, 3000, camera_id=99) is True
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