#!/usr/bin/env python3 """ 资金流向数据每日采集脚本 功能：从5分钟K线数据自行计算资金流向，存入 stock_fund_flow_history 和 stock_fund_flow_today 表。 数据源：stock_kline_5min 表（自有数据，无需外部API） 算法： - 根据5分钟K线的 close vs open 判断买卖方向 - 根据成交额(amount)分类：超大单(≥100万), 大单(20~100万), 中单(4~20万), 小单(<4万) - 主力 = 超大单 + 大单 用法: # 计算今日资金流向 ./venv/bin/python sync_fund_flow.py # 补算历史（有5分钟K线但尚无资金流向的日期，最多30天） ./venv/bin/python sync_fund_flow.py --backfill 建议定时任务: 10 15 * * 1-5 /opt/stock-app/venv/bin/python /opt/stock-app/sync_fund_flow.py >> /opt/stock-app/sync_fund_flow.log 2>&1 30 15 * * 1-5 /opt/stock-app/venv/bin/python /opt/stock-app/sync_fund_flow.py --backfill >> /opt/stock-app/sync_fund_flow.log 2>&1 """ import sys import os import time import argparse import fcntl import atexit from datetime import datetime, date from collections import defaultdict sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) import psycopg2 from psycopg2.extras import execute_values from config import Config LOCK_FILE = '/tmp/sync_fund_flow.lock' _lock_fd = None def acquire_lock(): """获取进程锁，防止多实例同时运行""" global _lock_fd _lock_fd = open(LOCK_FILE, 'w') try: fcntl.flock(_lock_fd, fcntl.LOCK_EX | fcntl.LOCK_NB) _lock_fd.write(str(os.getpid())) _lock_fd.flush() atexit.register(release_lock) return True except IOError: try: with open(LOCK_FILE, 'r') as f: old_pid = f.read().strip() print(f"⚠️ 另一个实例正在运行 (PID: {old_pid})，退出", flush=True) except Exception: print(f"⚠️ 另一个实例正在运行，退出", flush=True) _lock_fd.close() _lock_fd = None return False def release_lock(): """释放进程锁""" global _lock_fd if _lock_fd: try: fcntl.flock(_lock_fd, fcntl.LOCK_UN) _lock_fd.close() except Exception: pass _lock_fd = None try: os.remove(LOCK_FILE) except Exception: pass def get_db_conn(): return psycopg2.connect( host=Config.DB_HOST, port=Config.DB_PORT, dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD, ) def calc_fund_flow_from_5min(conn, target_date): """ 从5分钟K线数据计算某日资金流向 算法: 1. 每根5分钟K线根据 close vs open 判断方向(买入/卖出) 2. 根据成交额(amount)分类: - 超大单: amount >= 100万 - 大单: 20万 <= amount < 100万 - 中单: 4万 <= amount < 20万 - 小单: amount < 4万 3. 主力 = 超大单 + 大单 """ cur = conn.cursor() cur.execute(""" SELECT code, open, close, volume, amount FROM stock_kline_5min WHERE dt::date = %s AND amount > 0 ORDER BY code, dt """, (target_date,)) rows = cur.fetchall() if not rows: return {} stock_flows = defaultdict(lambda: { 'super_buy': 0, 'super_sell': 0, 'big_buy': 0, 'big_sell': 0, 'mid_buy': 0, 'mid_sell': 0, 'small_buy': 0, 'small_sell': 0, 'total_amount': 0 }) for code, open_p, close_p, volume, amount in rows: if not amount or float(amount) <= 0: continue amt = float(amount) sf = stock_flows[code] sf['total_amount'] += amt is_buy = float(close_p) >= float(open_p) if close_p and open_p else True if amt >= 1000000: # 超大单 >= 100万 cat = 'super' elif amt >= 200000: # 大单 >= 20万 cat = 'big' elif amt >= 40000: # 中单 >= 4万 cat = 'mid' else: # 小单 cat = 'small' if is_buy: sf[f'{cat}_buy'] += amt else: sf[f'{cat}_sell'] += amt results = {} for code, sf in stock_flows.items(): total = sf['total_amount'] if total <= 0: continue super_net = sf['super_buy'] - sf['super_sell'] big_net = sf['big_buy'] - sf['big_sell'] mid_net = sf['mid_buy'] - sf['mid_sell'] small_net = sf['small_buy'] - sf['small_sell'] main_net = super_net + big_net results[code] = { 'main_net_inflow': round(main_net, 2), 'main_net_inflow_pct': round(main_net / total * 100, 4) if total > 0 else 0, 'super_net_inflow': round(super_net, 2), 'super_net_inflow_pct': round(super_net / total * 100, 4) if total > 0 else 0, 'big_net_inflow': round(big_net, 2), 'big_net_inflow_pct': round(big_net / total * 100, 4) if total > 0 else 0, 'mid_net_inflow': round(mid_net, 2), 'mid_net_inflow_pct': round(mid_net / total * 100, 4) if total > 0 else 0, 'small_net_inflow': round(small_net, 2), 'small_net_inflow_pct': round(small_net / total * 100, 4) if total > 0 else 0, } return results def update_today_flow(conn): """更新今日资金流向到 stock_fund_flow_today""" today = date.today() flows = calc_fund_flow_from_5min(conn, today) if not flows: print(f" 今日({today})无5分钟K线数据，跳过", flush=True) return 0 cur = conn.cursor() codes = list(flows.keys()) cur.execute(""" SELECT code, name, price, change_pct FROM stock_realtime_price WHERE code = ANY(%s) """, (codes,)) price_map = {r[0]: {'name': r[1], 'price': float(r[2] or 0), 'change_pct': float(r[3] or 0)} for r in cur.fetchall()} records = [] for code, f in flows.items(): info = price_map.get(code, {}) records.append(( code, info.get('name', ''), f['main_net_inflow'], f['main_net_inflow_pct'], f['super_net_inflow'], f['super_net_inflow_pct'], f['big_net_inflow'], f['big_net_inflow_pct'], f['mid_net_inflow'], f['mid_net_inflow_pct'], f['small_net_inflow'], f['small_net_inflow_pct'], info.get('price', 0), info.get('change_pct', 0), )) execute_values(cur, """ INSERT INTO stock_fund_flow_today (code, name, main_net_inflow, main_net_inflow_pct, super_net_inflow, super_net_inflow_pct, big_net_inflow, big_net_inflow_pct, mid_net_inflow, mid_net_inflow_pct, small_net_inflow, small_net_inflow_pct, price, change_pct, updated_at) VALUES %s ON CONFLICT (code) DO UPDATE SET name = EXCLUDED.name, main_net_inflow = EXCLUDED.main_net_inflow, main_net_inflow_pct = EXCLUDED.main_net_inflow_pct, super_net_inflow = EXCLUDED.super_net_inflow, super_net_inflow_pct = EXCLUDED.super_net_inflow_pct, big_net_inflow = EXCLUDED.big_net_inflow, big_net_inflow_pct = EXCLUDED.big_net_inflow_pct, mid_net_inflow = EXCLUDED.mid_net_inflow, mid_net_inflow_pct = EXCLUDED.mid_net_inflow_pct, small_net_inflow = EXCLUDED.small_net_inflow, small_net_inflow_pct = EXCLUDED.small_net_inflow_pct, price = EXCLUDED.price, change_pct = EXCLUDED.change_pct, updated_at = NOW() """, records, template="(%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW())") conn.commit() print(f" ✅ 今日资金流向: {len(records)} 只股票", flush=True) return len(records) def backfill_history(conn, max_days=30): """补算历史资金流向: 有5分钟K线但尚无 fund_flow_history 的日期""" cur = conn.cursor() cur.execute(""" SELECT DISTINCT dt::date as d FROM stock_kline_5min WHERE dt::date NOT IN ( SELECT DISTINCT trade_date FROM stock_fund_flow_history ) AND dt::date < CURRENT_DATE ORDER BY d DESC LIMIT %s """, (max_days,)) missing_dates = [row[0] for row in cur.fetchall()] if not missing_dates: print(" ✅ 历史资金流向已完整，无需补算", flush=True) return 0 print(f" 需补算 {len(missing_dates)} 天的历史资金流向", flush=True) total_records = 0 for d in missing_dates: flows = calc_fund_flow_from_5min(conn, d) if not flows: continue # 获取当天收盘价和涨跌幅（通过前一日收盘价计算） cur.execute(""" SELECT k.code, k.close, CASE WHEN prev.close > 0 THEN ROUND((k.close - prev.close) / prev.close * 100, 2) ELSE 0 END AS change_pct FROM stock_kline_daily k LEFT JOIN LATERAL ( SELECT close FROM stock_kline_daily WHERE code = k.code AND trade_date < k.trade_date ORDER BY trade_date DESC LIMIT 1 ) prev ON true WHERE k.trade_date = %s AND k.code = ANY(%s) """, (d, list(flows.keys()))) price_map = {r[0]: {'close': float(r[1] or 0), 'change_pct': float(r[2] or 0)} for r in cur.fetchall()} records = [] for code, f in flows.items(): info = price_map.get(code, {}) records.append(( code, d, info.get('close', 0), info.get('change_pct', 0), f['main_net_inflow'], f['main_net_inflow_pct'], f['super_net_inflow'], f['super_net_inflow_pct'], f['big_net_inflow'], f['big_net_inflow_pct'], f['mid_net_inflow'], f['mid_net_inflow_pct'], f['small_net_inflow'], f['small_net_inflow_pct'], )) if records: execute_values(cur, """ INSERT INTO stock_fund_flow_history (code, trade_date, close_price, change_pct, main_net_inflow, main_net_inflow_pct, super_net_inflow, super_net_inflow_pct, big_net_inflow, big_net_inflow_pct, mid_net_inflow, mid_net_inflow_pct, small_net_inflow, small_net_inflow_pct, updated_at) VALUES %s ON CONFLICT (code, trade_date) DO UPDATE SET close_price = EXCLUDED.close_price, change_pct = EXCLUDED.change_pct, main_net_inflow = EXCLUDED.main_net_inflow, main_net_inflow_pct = EXCLUDED.main_net_inflow_pct, super_net_inflow = EXCLUDED.super_net_inflow, super_net_inflow_pct = EXCLUDED.super_net_inflow_pct, big_net_inflow = EXCLUDED.big_net_inflow, big_net_inflow_pct = EXCLUDED.big_net_inflow_pct, mid_net_inflow = EXCLUDED.mid_net_inflow, mid_net_inflow_pct = EXCLUDED.mid_net_inflow_pct, small_net_inflow = EXCLUDED.small_net_inflow, small_net_inflow_pct = EXCLUDED.small_net_inflow_pct, updated_at = NOW() """, records, template="(%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW())") conn.commit() total_records += len(records) print(f" {d}: {len(records)} 只股票", flush=True) print(f" ✅ 历史补算完成: {total_records} 条记录, {len(missing_dates)} 天", flush=True) return total_records def main(): if not acquire_lock(): sys.exit(1) parser = argparse.ArgumentParser(description='资金流向计算（从5分钟K线数据）') parser.add_argument('--backfill', action='store_true', help='补算历史资金流向（有5分钟K线但尚无资金流向的日期）') parser.add_argument('--max-days', type=int, default=30, help='历史补算最大天数（默认30）') args = parser.parse_args() today = date.today() print(f"{'='*60}", flush=True) print(f"💰 资金流向计算（来源: 5分钟K线数据）", flush=True) print(f"📅 日期: {today}", flush=True) print(f"{'='*60}", flush=True) conn = get_db_conn() start_time = time.time() try: # 始终计算今日 print("\n📊 计算今日资金流向...", flush=True) today_count = update_today_flow(conn) # 如果指定了 --backfill，补算历史 if args.backfill: print(f"\n📜 补算历史资金流向(最多{args.max_days}天)...", flush=True) hist_count = backfill_history(conn, args.max_days) else: hist_count = 0 elapsed = time.time() - start_time # 显示数据库统计 cur = conn.cursor() cur.execute(""" SELECT count(*), count(DISTINCT code), min(trade_date), max(trade_date), count(DISTINCT trade_date) FROM stock_fund_flow_history """) cnt, codes, min_d, max_d, days = cur.fetchone() print(f"\n{'='*60}", flush=True) print(f"✅ 完成! 耗时: {elapsed:.1f}秒", flush=True) print(f" 今日: {today_count} 条 | 历史补算: {hist_count} 条", flush=True) print(f"\n💰 stock_fund_flow_history 统计:", flush=True) print(f" 总记录: {cnt:,} 条 | {codes:,} 只股票 | {days} 个交易日", flush=True) if min_d: print(f" 日期范围: {min_d} ~ {max_d}", flush=True) print(f"{'='*60}", flush=True) except Exception as e: print(f"❌ 错误: {e}", flush=True) import traceback traceback.print_exc() finally: conn.close() if __name__ == '__main__': main()