Initial: MoFin 持仓分析与策略管理系统
核心模块： - 策略生命周期管理 (strategy_lifecycle.py) - 技术分析引擎 (technical_analysis.py) - 双维度策略评估 (strategy_evaluator.py) - 实时行情获取 (get_realtime_prices.py) - Web Dashboard (server.py, :8899) 提示词版本管理： - prompt_manager 模块 — 统一管理所有知微提示词 - 8个提示词共24个版本已录入 - 策略→提示词版本关联追踪 - Dashboard「提示词」Tab 数据源增强： - 服务端 POST /api/update/realtime 端点已就绪 - clients/tdx-relay/ — 小小莫在Windows上开发的通达信中继 - 解决港股15分钟延迟问题
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#!/usr/bin/env python3
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"""update_data.py — 解析cron输出，更新dashboard数据层"""
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import json
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import os
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import re
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from datetime import datetime
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from pathlib import Path
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DATA_DIR = Path(__file__).parent / "data"
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def _save(name, data):
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path = DATA_DIR / name
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os.makedirs(path.parent, exist_ok=True)
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with open(path, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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def parse_report(markdown_text, source_file=None):
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"""解析cron输出的markdown报告，提取结构化数据"""
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report = {
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"title": "",
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"type": "未知",
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"created_at": datetime.now().isoformat(),
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"summary": "",
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"content": markdown_text,
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"stocks_mentioned": [],
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"structured": None, # 结构化数据优先
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}
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lines = markdown_text.split("\n")
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# 提取标题
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for line in lines:
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m = re.match(r"^#\s+(.+)", line)
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if m:
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report["title"] = m.group(1).strip()
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break
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m = re.match(r"^📊\s+(.+)", line)
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if m:
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report["title"] = m.group(1).strip()
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break
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# 判断类型
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if "盘中" in report["title"]:
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report["type"] = "盘中"
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elif "盘后" in report["title"] or "复盘" in report["title"]:
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report["type"] = "盘后"
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elif "盯盘" in report["title"]:
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report["type"] = "盯盘"
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elif "扫描" in report["title"]:
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report["type"] = "盘前"
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# ★ 优先提取结构化JSON（如果知微输出了的话）
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struct_match = re.search(r'<structured_data>\s*(\{.*?\})\s*</structured_data>', markdown_text, re.DOTALL)
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if struct_match:
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try:
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parsed = json.loads(struct_match.group(1))
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report["structured"] = parsed
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# 从结构化数据中直接取stock codes
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codes = set()
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for h in parsed.get("holdings", []):
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c = h.get("code", "")
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if c:
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codes.add(c)
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report["stocks_mentioned"] = sorted(codes)
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except (json.JSONDecodeError, Exception) as e:
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pass # JSON解析失败→走NLP兜底
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# 摘要（前3非空行）
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body_lines = [l.strip() for l in lines if l.strip() and not l.strip().startswith("#") and not l.strip().startswith("##")]
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report["summary"] = "\n".join(body_lines[:5])[:200]
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# NLP兜底（仅当结构化数据没取到code时）
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if not report["stocks_mentioned"]:
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codes = set(re.findall(r'\b\d{6}\b', markdown_text))
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hk_codes = set(re.findall(r'\b\d{5}\b', markdown_text))
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report["stocks_mentioned"] = sorted(codes | hk_codes)
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return report
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def import_cron_outputs():
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"""从cron输出目录导入最新报告"""
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cron_dir = Path.home() / ".hermes" / "cron" / "output"
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reports_dir = DATA_DIR / "reports"
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os.makedirs(reports_dir, exist_ok=True)
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count = 0
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if not cron_dir.exists():
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return count
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for job_dir in sorted(cron_dir.iterdir()):
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if not job_dir.is_dir():
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continue
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for f in sorted(job_dir.iterdir(), reverse=True)[:5]: # 每个job最近5个
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if f.suffix != ".md":
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continue
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# Skip if already imported
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export_name = f"cron_{job_dir.name}_{f.stem}.json"
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if (reports_dir / export_name).exists():
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continue
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content = f.read_text(encoding="utf-8", errors="replace")
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report = parse_report(content, source_file=str(f))
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# Extract response section
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resp_match = re.search(r"## Response\n+(.*)", content, re.DOTALL)
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if resp_match:
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resp = resp_match.group(1).strip()
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if resp == "[SILENT]":
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continue # Skip SILENT reports
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report["_id"] = export_name.replace(".json", "")
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_save(f"reports/{export_name}", report)
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count += 1
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return count
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def extract_stock_mentions():
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"""从报告中提取个股操作建议"""
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reports_dir = DATA_DIR / "reports"
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stocks_dir = DATA_DIR / "stocks"
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os.makedirs(stocks_dir, exist_ok=True)
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stock_data = {}
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for f in sorted(reports_dir.iterdir()):
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if f.suffix != ".json":
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continue
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try:
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report = json.loads(f.read_text(encoding="utf-8"))
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except:
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continue
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content = report.get("content", "")
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codes = report.get("stocks_mentioned", [])
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for code in codes:
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if code not in stock_data:
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stock_data[code] = {"code": code, "history": []}
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# Try to extract recommendation from content
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# Look for patterns like "建议|止盈|止损|补仓|持有"
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pattern = re.compile(
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rf'.*?({code}).*?(建议|止盈|止损|补仓|持有|减仓|加仓|卖出|买入).*?(?:\n|$)',
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re.IGNORECASE,
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)
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for m in pattern.finditer(content):
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stock_data[code]["history"].append({
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"time": report.get("created_at", ""),
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"content": m.group(0).strip()[:100],
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"report_id": report.get("_id", ""),
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})
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for code, data in stock_data.items():
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_save(f"stocks/{code}.json", data)
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return len(stock_data)
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def sync_to_decisions():
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"""将个股建议同步到决策库（advice_timeline），自动去重"""
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decisions_path = DATA_DIR / "decisions.json"
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if not decisions_path.exists():
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return 0
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decisions = json.loads(decisions_path.read_text(encoding="utf-8"))
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stocks_dir = DATA_DIR / "stocks"
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synced = 0
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for f in sorted(stocks_dir.iterdir()):
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if f.suffix != ".json":
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continue
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try:
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stock = json.loads(f.read_text(encoding="utf-8"))
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except:
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continue
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code = stock.get("code", "")
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history = stock.get("history", [])
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if not code or not history:
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continue
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# 找决策库中是否有此股
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existing = None
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for d in decisions["decisions"]:
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if d["code"] == code:
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existing = d
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break
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if not existing:
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# 无决策记录→生成inactive记录
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existing = {
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"code": code,
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"name": stock.get("name", ""),
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"timestamp": datetime.now().isoformat(),
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"type": "历史建议汇总",
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"current": "自动从update_data同步",
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"status": "inactive",
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"updated_by": "system(update_data)",
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"advice_timeline": []
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}
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decisions["decisions"].append(existing)
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# 去重合并
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timeline = existing.setdefault("advice_timeline", [])
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existing_keys = {(e["date"], e["direction"], e["summary"]) for e in timeline
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if "date" in e and "direction" in e and "summary" in e}
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new_count = 0
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for entry in history:
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content = entry.get("content", "")
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# 判断方向
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direction = "其他"
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if any(w in content for w in ["买入", "加仓", "入场", "🟢", "可加", "可入"]):
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direction = "买入"
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elif any(w in content for w in ["卖出", "止盈", "减仓", "止损", "清仓", "🔴", "锁定利润"]):
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direction = "卖出"
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elif any(w in content for w in ["持有", "观望", "👀", "🤝", "暂持", "继续持有"]):
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direction = "持有"
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if direction == "其他":
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continue
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# 提取日期
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rid = entry.get("report_id", "")
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m = re.search(r'(\d{4}-\d{2}-\d{2})', rid)
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date = m.group(1) if m else "unknown"
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key = (date, direction, content.strip()[:80])
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if key not in existing_keys:
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existing_keys.add(key)
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timeline.append({
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"date": date,
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"direction": direction,
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"summary": content.strip()[:120],
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"report_id": rid
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})
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new_count += 1
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if new_count > 0:
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# 按日期排序
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timeline.sort(key=lambda e: e.get("date", ""))
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synced += new_count
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decisions_path.write_text(
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json.dumps(decisions, ensure_ascii=False, indent=2), encoding="utf-8"
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)
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return synced
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def build_portfolio_from_obsidian():
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"""读取Obsidian持仓数据，生成portfolio.json"""
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import subprocess
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# Attempt to read from Obsidian
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obsidian_path = Path.home() / "Obsidian" / "knowledge" / "finance"
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portfolio_file = obsidian_path / "dad-portfolio.md"
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holdings = []
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total_assets = 0
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stock_value = 0
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cash = 0
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if portfolio_file.exists():
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content = portfolio_file.read_text(encoding="utf-8", errors="replace")
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lines = content.split("\n")
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for line in lines:
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m = re.match(r'\|.*?\|.*?(\d+)@(\d+\.?\d*)@.*?\|(\d+\.?\d*)%?\|', line)
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if m:
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# Parse holding lines from markdown table
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parts = [p.strip() for p in line.split("|")]
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if len(parts) >= 8:
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name = parts[1] if len(parts) > 1 else ""
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code = parts[2] if len(parts) > 2 else ""
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if code:
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holdings.append({
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"code": code,
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"name": name,
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"position_pct": 0,
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"cost": 0,
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"shares": 0,
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"price": 0,
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"change_pct": 0,
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})
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return {
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"holdings": holdings,
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"total_assets": total_assets,
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"stock_value": stock_value,
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"cash": cash,
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"position_pct": 0,
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"total_pnl": 0,
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"updated_at": datetime.now().isoformat(),
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}
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if __name__ == "__main__":
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count = import_cron_outputs()
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if count > 0:
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print(f"📥 新增报告: {count}篇")
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stocks = extract_stock_mentions()
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if stocks > 0:
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print(f"📊 个股数据: {stocks}条")
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synced = sync_to_decisions()
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if synced > 0:
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print(f"📋 决策库: 新增{synced}条建议")
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# 有实质更新才发汇总，否则安静
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if count > 0 or stocks > 0 or synced > 0:
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print(f"✅ {datetime.now().strftime('%m/%d %H:%M')} 数据同步完成")
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# 什么新数据都没有→安静，不输出任何内容
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