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branch_scanner 彻底静默：自成长采集器不出操作信号

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branch_scanner 是自成长数据收集器，不输出也不推送。
操作信号由 stale_push_wlin / price_monitor / 开盘收盘简报 按cron-report-format规范输出。
scanner只做三件事：
1. 每15分钟扫价格+评估分支
2. trigger_count + 1（决策树数据）
3. 更新状态快照
This commit is contained in:
知微
2026-06-24 10:39:28 +08:00
parent 68e806cfa1
commit 80b854b945
4 changed files with 133 additions and 301 deletions
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branch_scanner.py
+27 -111
View File
@@ -1,28 +1,28 @@
#!/usr/bin/env python3
"""
branch_scanner.py — 盘中分支扫描器
branch_scanner.py — 分支自成长数据采集器（全静默）
每15分钟跑一轮：
1. 读取所有有 strategy_tree 的股票
2. 获取实时价格
3. 评估每个分支在当前情景下是否适用
4. 适用分支 → 记录 trigger_count + 推送信号
核心功能（三件事，全部后台静默执行）：
1. 每轮扫描42只股票，评估当前情景下各分支的适用性
2. 适用分支 → trigger_count + 1，记录 last_triggered
3. 保存当前状态到 scanner_state.json 供下次对比
自成长核心组件：让分支条件得到实际验证。
无输出 → 静默运行。触发数据积累在 decisions.json。
操作信号由 stale_push_wlin / price_monitor / 开盘收盘简报 另路输出。
数据流向（自成长）：每15分钟branch_scanner积累trigger_count →
每日prune_branches评估低效分支 → decisions.json修剪 → 分支越来越有效
"""
import json, sys, os, re
from datetime import datetime, date
import json, sys, re
from datetime import datetime
from urllib.request import Request, urlopen
DECISIONS_PATH = "/home/hmo/web-dashboard/data/decisions.json"
WATCHLIST_PATH = "/home/hmo/web-dashboard/data/watchlist.json"
MACRO_PATH = "/home/hmo/web-dashboard/data/macro_context.json"
EVENTS_PATH = "/home/hmo/web-dashboard/data/price_events.json"
SCANNER_STATE = "/home/hmo/web-dashboard/data/scanner_state.json"
def get_price(code):
"""腾讯API实时价格"""
mkt = "sh" if code.startswith("6") or code.startswith("5") else "sz"
url = f"http://qt.gtimg.cn/q={mkt}{code}"
req = Request(url, headers={"User-Agent": "Mozilla/5.0"})
@@ -32,12 +32,10 @@ def get_price(code):
if len(parts) > 3:
return float(parts[3])
except Exception:
pass
return None
def get_scenario():
"""读当前情景"""
try:
sys.path.insert(0, "/home/hmo/MoFin")
from strategy_tree import detect_scenario
@@ -46,26 +44,11 @@ def get_scenario():
return {"id": "unknown", "label": "未知", "confidence": 0}
def load_decisions():
try:
with open(DECISIONS_PATH) as f:
return json.load(f)
except Exception:
return {"decisions": []}
def save_decisions(data):
with open(DECISIONS_PATH, "w") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def check_condition(branch, scenario_id, price):
"""检查分支条件是否满足 — 同步 strategy_tree._check_branch_condition 逻辑"""
cond = branch.get("condition", {})
required_scenario = cond.get("scenario", "")
if required_scenario and required_scenario != scenario_id:
return False
price_cond = cond.get("price", "")
if price_cond and price:
ops = re.findall(r"([<>=!]+)\s*([\d.]+)", price_cond)
@@ -75,8 +58,6 @@ def check_condition(branch, scenario_id, price):
if op == ">" and not (price > val): return False
if op == "<=" and not (price <= val): return False
if op == ">=" and not (price >= val): return False
# 买入区下界（price_lower）检查 — 之前遗漏
price_lower = cond.get("price_lower", "")
if price_lower and price:
ops = re.findall(r"([<>=!]+)\s*([\d.]+)", price_lower)
@@ -86,119 +67,54 @@ def check_condition(branch, scenario_id, price):
if op == ">" and not (price > val): return False
if op == "<=" and not (price <= val): return False
if op == ">=" and not (price >= val): return False
return True
def main():
now = datetime.now()
today = now.strftime("%Y-%m-%d")
hour = now.hour
# 盘后才扫无意义
if hour < 9 or hour > 16:
if now.hour < 9 or now.hour > 16:
return 0
scenario = get_scenario()
sid = scenario.get("id", "unknown")
slabel = scenario.get("label", "未知")
data = load_decisions()
with open(DECISIONS_PATH) as f:
data = json.load(f)
decisions = data.get("decisions", [])
# 读上次扫描的状态（记录情景+各股最优分支）
state_path = "/home/hmo/web-dashboard/data/scanner_state.json"
last_state = {"scenario": "", "branches": {}}
try:
with open(state_path) as f:
last_state = json.load(f)
except Exception:
pass
triggered = []
alerts = []
for entry in decisions:
code = entry.get("code", "")
tree = entry.get("strategy_tree", {})
branches = tree.get("branches", [])
if not branches:
continue
price = get_price(code)
if not price:
continue
# 找出最优适用分支
best = None
for br in sorted(branches, key=lambda b: b.get("priority", 999)):
if check_condition(br, sid, price):
best = br
br["trigger_count"] = br.get("trigger_count", 0) + 1
br["last_triggered"] = now.strftime("%Y-%m-%d")
break
if best:
best["trigger_count"] = best.get("trigger_count", 0) + 1
best["last_triggered"] = today
triggered.append(code)
with open(DECISIONS_PATH, "w") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
# 状态变化检测：上次不是这个分支→推送
action_type = best.get("action", {}).get("type", "hold")
br_id = best.get("id", "")
last_br = last_state.get("branches", {}).get(code, "")
last_action = last_state.get("branches", {}).get(f"{code}_action", "")
changed = (br_id != last_br)
# 推送条件：分支变化（情景变化已隐含）或止损首次触发
priority = best.get("priority", 99)
should_alert = False
if priority == 0: # 止损
# 只有止损新出现才推（上次不是止损 or 上次扫描不存在）
should_alert = (changed or not last_state.get("branches"))
elif sid != last_state.get("scenario"):
should_alert = True
elif changed:
should_alert = True
if should_alert:
rationale = best.get("rationale", "")
count = best.get("trigger_count", 1)
alerts.append(f" {code} {entry.get('name','')}: {action_type}（{rationale}）")
if triggered:
save_decisions(data)
# 保存当前状态供下次对比
new_state = {
"scenario": sid,
"scenario_label": slabel,
"branches": {},
"updated_at": now.isoformat(),
}
# 更新状态快照
state = {"scenario": sid, "updated_at": now.isoformat(), "branches": {}}
for e in decisions:
code = e.get("code", "")
tree = e.get("strategy_tree", {})
branches = tree.get("branches", [])
best = None
for br in sorted(branches, key=lambda b: b.get("priority", 999)):
for br in sorted(tree.get("branches", []), key=lambda b: b.get("priority", 999)):
if check_condition(br, sid, get_price(code)):
best = br
state["branches"][code] = br.get("id", "")
break
if best:
new_state["branches"][code] = best.get("id", "")
new_state["branches"][f"{code}_action"] = best.get("action", {}).get("type", "")
try:
with open(state_path, "w") as f:
json.dump(new_state, f, indent=2)
with open(SCANNER_STATE, "w") as f:
json.dump(state, f, indent=2)
except Exception:
pass
# 输出：变化才出声，平常静默
if alerts:
scenario_shift = f"【情景切换】{last_state.get('scenario','')}→{sid}" if sid != last_state.get("scenario") else ""
header = f"【分支扫描】{now.strftime('%H:%M')}" + (f" | {scenario_shift}" if scenario_shift else "")
msg = header + "\n" + "\n".join(alerts)
print(msg)
return 0
# 无变化→静默
return 0
data/decisions.json
+26 -26
View File
@@ -147,7 +147,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -226,7 +226,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -411,7 +411,7 @@
},
"priority": 0,
"rationale": "止损保护本金",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -705,7 +705,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -852,7 +852,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 6,
"trigger_count": 7,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -4831,7 +4831,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5035,7 +5035,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 6,
"trigger_count": 7,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5197,7 +5197,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5401,7 +5401,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5642,7 +5642,7 @@
},
"priority": 4,
"rationale": "达到目标价，减半仓锁定利润",
"trigger_count": 5,
"trigger_count": 6,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5802,7 +5802,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -5978,7 +5978,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -6253,7 +6253,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -6351,7 +6351,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 10,
"trigger_count": 11,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -6606,7 +6606,7 @@
},
"priority": 4,
"rationale": "达到目标价，减半仓锁定利润",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -6823,7 +6823,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 6,
"trigger_count": 7,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -6913,7 +6913,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 6,
"trigger_count": 7,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -7117,7 +7117,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -7358,7 +7358,7 @@
},
"priority": 4,
"rationale": "达到目标价，减半仓锁定利润",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -7505,7 +7505,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -7716,7 +7716,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -7920,7 +7920,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 3,
"trigger_count": 4,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -8060,7 +8060,7 @@
},
"priority": 1,
"rationale": "价格回调到支撑区，弱势市场低吸",
"trigger_count": 6,
"trigger_count": 7,
"success_rate": null,
"last_triggered": "2026-06-24"
},
@@ -8328,7 +8328,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -8518,7 +8518,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
@@ -8653,7 +8653,7 @@
},
"priority": 99,
"rationale": "没有分支匹配时的默认动作",
"trigger_count": 7,
"trigger_count": 8,
"success_rate": null,
"last_triggered": "2026-06-24"
}
data/portfolio.json
+35 -35
View File
@@ -55,8 +55,8 @@
"action_note": "⚠️盈亏比偏低(1:1.3)，不建议加仓",
"timing_signal": "大盘中性，行业中性，高估值，蓝筹，持有"
},
"price": 83.95,
"change_pct": 7.84
"price": 83.65,
"change_pct": 7.45
},
{
"code": "01088",
@@ -85,7 +85,7 @@
"timing_signal": "大盘中性，行业中性，蓝筹，持有"
},
"price": 41.52,
"change_pct": -1.09
"change_pct": -1.28
},
{
"code": "01211",
@@ -113,8 +113,8 @@
"action_note": "深套持有",
"timing_signal": "大盘中性，行业偏弱，蓝筹，持有"
},
"price": 75.0,
"change_pct": -1.12
"price": 74.95,
"change_pct": -1.19
},
{
"code": "01478",
@@ -142,8 +142,8 @@
"action_note": "深套持有",
"timing_signal": "大盘中性，行业中性，低估值，持有"
},
"price": 7.68,
"change_pct": -2.79
"price": 7.67,
"change_pct": -2.66
},
{
"code": "01888",
@@ -171,8 +171,8 @@
"action_note": "短炒强趋势持",
"timing_signal": "大盘中性，行业偏弱，高估值，强趋势持"
},
"price": 96.75,
"change_pct": 10.89
"price": 96.15,
"change_pct": 10.2
},
{
"code": "02202",
@@ -201,7 +201,7 @@
"timing_signal": "大盘中性，行业中性，高估值，持有"
},
"price": 2.34,
"change_pct": -2.5
"change_pct": -2.92
},
{
"code": "02388",
@@ -229,8 +229,8 @@
"action_note": "",
"timing_signal": "大盘中性，行业偏强，低估值，蓝筹，持有"
},
"price": 46.4,
"change_pct": -1.02
"price": 46.32,
"change_pct": -1.45
},
{
"code": "09988",
@@ -258,8 +258,8 @@
"action_note": "深套持有",
"timing_signal": "大盘中性，行业偏弱，蓝筹，持有"
},
"price": 98.25,
"change_pct": -0.66
"price": 98.45,
"change_pct": -0.51
},
{
"code": "300035",
@@ -287,8 +287,8 @@
"action_note": "深套持有",
"timing_signal": "大盘中性，行业偏弱，持有"
},
"price": 16.21,
"change_pct": -0.92
"price": 16.17,
"change_pct": -0.98
},
{
"code": "300548",
@@ -316,8 +316,8 @@
"action_note": "短炒强趋势持",
"timing_signal": "大盘中性，行业中性，高估值，强趋势持"
},
"price": 282.89,
"change_pct": -1.09
"price": 282.02,
"change_pct": -1.4
},
{
"code": "300690",
@@ -345,8 +345,8 @@
"action_note": "⚠️盈亏比偏低(1:1.5)，不建议加仓",
"timing_signal": "大盘中性，行业偏弱，持有"
},
"price": 22.82,
"change_pct": -3.47
"price": 22.83,
"change_pct": -3.39
},
{
"code": "300750",
@@ -374,8 +374,8 @@
"action_note": "",
"timing_signal": "大盘中性，行业偏弱，蓝筹，持有"
},
"price": 393.04,
"change_pct": 0.14
"price": 392.25,
"change_pct": -0.07
},
{
"code": "518880",
@@ -404,7 +404,7 @@
"timing_signal": "大盘中性，行业偏弱，持有"
},
"price": 8.45,
"change_pct": -0.97
"change_pct": -1.07
},
{
"code": "600036",
@@ -432,8 +432,8 @@
"action_note": "⚠️盈亏比偏低(1:1.2)，不建议加仓",
"timing_signal": "大盘中性，行业偏强，低估值，蓝筹，弱势持有"
},
"price": 37.04,
"change_pct": -0.94
"price": 37.07,
"change_pct": -0.88
},
{
"code": "600563",
@@ -490,8 +490,8 @@
"action_note": "⚠️盈亏比偏低(1:1.2)，不建议加仓",
"timing_signal": "大盘中性，行业偏强，持有"
},
"price": 10.49,
"change_pct": -1.5
"price": 10.47,
"change_pct": -1.69
},
{
"code": "601899",
@@ -519,8 +519,8 @@
"action_note": "深套持有",
"timing_signal": "大盘中性，行业偏弱，低估值，蓝筹，持有"
},
"price": 27.58,
"change_pct": -0.61
"price": 27.56,
"change_pct": -0.68
},
{
"code": "603259",
@@ -548,8 +548,8 @@
"action_note": "",
"timing_signal": "大盘中性，行业偏强，低估值，持有"
},
"price": 116.26,
"change_pct": 9.36
"price": 116.18,
"change_pct": 9.28
},
{
"code": "688411",
@@ -577,8 +577,8 @@
"action_note": "",
"timing_signal": "持有"
},
"price": 267.1,
"change_pct": -2.11
"price": 267.18,
"change_pct": -1.86
},
{
"code": "688981",
@@ -606,8 +606,8 @@
"action_note": "",
"timing_signal": "大盘中性，行业中性，高估值，蓝筹，持有"
},
"price": 150.91,
"change_pct": 6.5
"price": 151.24,
"change_pct": 6.73
}
]
}
scripts/branch_scanner.py
+27 -111
View File
@@ -1,28 +1,28 @@
#!/usr/bin/env python3
"""
branch_scanner.py — 盘中分支扫描器
branch_scanner.py — 分支自成长数据采集器（全静默）
每15分钟跑一轮：
1. 读取所有有 strategy_tree 的股票
2. 获取实时价格
3. 评估每个分支在当前情景下是否适用
4. 适用分支 → 记录 trigger_count + 推送信号
核心功能（三件事，全部后台静默执行）：
1. 每轮扫描42只股票，评估当前情景下各分支的适用性
2. 适用分支 → trigger_count + 1，记录 last_triggered
3. 保存当前状态到 scanner_state.json 供下次对比
自成长核心组件：让分支条件得到实际验证。
无输出 → 静默运行。触发数据积累在 decisions.json。
操作信号由 stale_push_wlin / price_monitor / 开盘收盘简报 另路输出。
数据流向（自成长）：每15分钟branch_scanner积累trigger_count →
每日prune_branches评估低效分支 → decisions.json修剪 → 分支越来越有效
"""
import json, sys, os, re
from datetime import datetime, date
import json, sys, re
from datetime import datetime
from urllib.request import Request, urlopen
DECISIONS_PATH = "/home/hmo/web-dashboard/data/decisions.json"
WATCHLIST_PATH = "/home/hmo/web-dashboard/data/watchlist.json"
MACRO_PATH = "/home/hmo/web-dashboard/data/macro_context.json"
EVENTS_PATH = "/home/hmo/web-dashboard/data/price_events.json"
SCANNER_STATE = "/home/hmo/web-dashboard/data/scanner_state.json"
def get_price(code):
"""腾讯API实时价格"""
mkt = "sh" if code.startswith("6") or code.startswith("5") else "sz"
url = f"http://qt.gtimg.cn/q={mkt}{code}"
req = Request(url, headers={"User-Agent": "Mozilla/5.0"})
@@ -32,12 +32,10 @@ def get_price(code):
if len(parts) > 3:
return float(parts[3])
except Exception:
pass
return None
def get_scenario():
"""读当前情景"""
try:
sys.path.insert(0, "/home/hmo/MoFin")
from strategy_tree import detect_scenario
@@ -46,26 +44,11 @@ def get_scenario():
return {"id": "unknown", "label": "未知", "confidence": 0}
def load_decisions():
try:
with open(DECISIONS_PATH) as f:
return json.load(f)
except Exception:
return {"decisions": []}
def save_decisions(data):
with open(DECISIONS_PATH, "w") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def check_condition(branch, scenario_id, price):
"""检查分支条件是否满足 — 同步 strategy_tree._check_branch_condition 逻辑"""
cond = branch.get("condition", {})
required_scenario = cond.get("scenario", "")
if required_scenario and required_scenario != scenario_id:
return False
price_cond = cond.get("price", "")
if price_cond and price:
ops = re.findall(r"([<>=!]+)\s*([\d.]+)", price_cond)
@@ -75,8 +58,6 @@ def check_condition(branch, scenario_id, price):
if op == ">" and not (price > val): return False
if op == "<=" and not (price <= val): return False
if op == ">=" and not (price >= val): return False
# 买入区下界（price_lower）检查 — 之前遗漏
price_lower = cond.get("price_lower", "")
if price_lower and price:
ops = re.findall(r"([<>=!]+)\s*([\d.]+)", price_lower)
@@ -86,119 +67,54 @@ def check_condition(branch, scenario_id, price):
if op == ">" and not (price > val): return False
if op == "<=" and not (price <= val): return False
if op == ">=" and not (price >= val): return False
return True
def main():
now = datetime.now()
today = now.strftime("%Y-%m-%d")
hour = now.hour
# 盘后才扫无意义
if hour < 9 or hour > 16:
if now.hour < 9 or now.hour > 16:
return 0
scenario = get_scenario()
sid = scenario.get("id", "unknown")
slabel = scenario.get("label", "未知")
data = load_decisions()
with open(DECISIONS_PATH) as f:
data = json.load(f)
decisions = data.get("decisions", [])
# 读上次扫描的状态（记录情景+各股最优分支）
state_path = "/home/hmo/web-dashboard/data/scanner_state.json"
last_state = {"scenario": "", "branches": {}}
try:
with open(state_path) as f:
last_state = json.load(f)
except Exception:
pass
triggered = []
alerts = []
for entry in decisions:
code = entry.get("code", "")
tree = entry.get("strategy_tree", {})
branches = tree.get("branches", [])
if not branches:
continue
price = get_price(code)
if not price:
continue
# 找出最优适用分支
best = None
for br in sorted(branches, key=lambda b: b.get("priority", 999)):
if check_condition(br, sid, price):
best = br
br["trigger_count"] = br.get("trigger_count", 0) + 1
br["last_triggered"] = now.strftime("%Y-%m-%d")
break
if best:
best["trigger_count"] = best.get("trigger_count", 0) + 1
best["last_triggered"] = today
triggered.append(code)
with open(DECISIONS_PATH, "w") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
# 状态变化检测：上次不是这个分支→推送
action_type = best.get("action", {}).get("type", "hold")
br_id = best.get("id", "")
last_br = last_state.get("branches", {}).get(code, "")
last_action = last_state.get("branches", {}).get(f"{code}_action", "")
changed = (br_id != last_br)
# 推送条件：分支变化（情景变化已隐含）或止损首次触发
priority = best.get("priority", 99)
should_alert = False
if priority == 0: # 止损
# 只有止损新出现才推（上次不是止损 or 上次扫描不存在）
should_alert = (changed or not last_state.get("branches"))
elif sid != last_state.get("scenario"):
should_alert = True
elif changed:
should_alert = True
if should_alert:
rationale = best.get("rationale", "")
count = best.get("trigger_count", 1)
alerts.append(f" {code} {entry.get('name','')}: {action_type}（{rationale}）")
if triggered:
save_decisions(data)
# 保存当前状态供下次对比
new_state = {
"scenario": sid,
"scenario_label": slabel,
"branches": {},
"updated_at": now.isoformat(),
}
# 更新状态快照
state = {"scenario": sid, "updated_at": now.isoformat(), "branches": {}}
for e in decisions:
code = e.get("code", "")
tree = e.get("strategy_tree", {})
branches = tree.get("branches", [])
best = None
for br in sorted(branches, key=lambda b: b.get("priority", 999)):
for br in sorted(tree.get("branches", []), key=lambda b: b.get("priority", 999)):
if check_condition(br, sid, get_price(code)):
best = br
state["branches"][code] = br.get("id", "")
break
if best:
new_state["branches"][code] = best.get("id", "")
new_state["branches"][f"{code}_action"] = best.get("action", {}).get("type", "")
try:
with open(state_path, "w") as f:
json.dump(new_state, f, indent=2)
with open(SCANNER_STATE, "w") as f:
json.dump(state, f, indent=2)
except Exception:
pass
# 输出：变化才出声，平常静默
if alerts:
scenario_shift = f"【情景切换】{last_state.get('scenario','')}→{sid}" if sid != last_state.get("scenario") else ""
header = f"【分支扫描】{now.strftime('%H:%M')}" + (f" | {scenario_shift}" if scenario_shift else "")
msg = header + "\n" + "\n".join(alerts)
print(msg)
return 0
# 无变化→静默
return 0