#!/usr/bin/env python3 # 期货分析系统演示脚本 import sys import json from datetime import datetime from qihuo_analyzer.data.data_fetcher import DataFetcher from qihuo_analyzer.data.data_storage import DataStorage from qihuo_analyzer.modules.trend_filter import TrendFilter from qihuo_analyzer.modules.risk_manager import RiskManager from qihuo_analyzer.modules.fund_flow_monitor import FundFlowMonitor from qihuo_analyzer.modules.support_resistance import SupportResistance from qihuo_analyzer.modules.rollover_detector import RolloverDetector from qihuo_analyzer.modules.deepseek_agent import DeepseekAgent from qihuo_analyzer.core.models import AnalysisResult def print_header(title): """打印标题""" print(f"\n{'='*60}") print(f"{title:^60}") print(f"{'='*60}") def print_section(title): """打印章节标题""" print(f"\n{'-'*40}") print(f"{title:^40}") print(f"{'-'*40}") def print_json(data, indent=2): """打印JSON格式数据""" print(json.dumps(data, ensure_ascii=False, indent=indent)) def main(): """主函数""" print_header("AI 期货分析系统演示") print(f"当前时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") # 初始化组件 print_section("初始化系统组件") data_fetcher = DataFetcher() data_storage = DataStorage() trend_filter = TrendFilter() risk_manager = RiskManager() fund_flow_monitor = FundFlowMonitor() support_resistance = SupportResistance() rollover_detector = RolloverDetector() deepseek_agent = DeepseekAgent() print("✅ 系统组件初始化完成") # 选择合约 symbol = "CU2309" # 铜期货合约 print_section(f"分析合约: {symbol}") # 获取K线数据 print("📊 获取K线数据...") kline_data = data_fetcher.get_kline_data(symbol, "1d", 200) if kline_data.empty: print("❌ 获取K线数据失败") return print(f"✅ 获取K线数据成功，共 {len(kline_data)} 条记录") print(f"最新价格: {kline_data['close'].iloc[-1]:.2f}") # 保存K线数据到数据库 data_storage.save_kline_data(symbol, "1d", kline_data) print("✅ K线数据已保存到数据库") # 1. 趋势分析 print_section("1. 趋势分析") trend_analysis = trend_filter.analyze_trend(kline_data) win_rate = trend_filter.calculate_win_rate(kline_data) cycle = trend_filter.judge_cycle(kline_data) print("📈 趋势分析结果:") print(f"ADX: {trend_analysis['adx']:.2f}") print(f"趋势强度: {trend_analysis['trend_strength']}") print(f"趋势方向: {trend_analysis['trend_direction']}") print(f"综合趋势: {trend_analysis['overall_trend']}") print(f"胜率: {win_rate:.2f}%") print(f"推荐周期: {cycle}") # 2. 资金流向分析 print_section("2. 资金流向分析") fund_flow_analysis = fund_flow_monitor.analyze_fund_flow(kline_data) print("💹 资金流向分析结果:") print(f"资金流向强度: {fund_flow_analysis['fund_flow_strength']:.2f}") print(f"持仓量趋势: {fund_flow_analysis['oi_trend']}") print(f"量价配合度: {fund_flow_analysis['volume_price_fit']:.2f}%") print(f"量价背离: {fund_flow_analysis['divergence']}") print(f"资金面信号: {fund_flow_analysis['fund_signal']}") # 3. 压力支撑分析 print_section("3. 压力支撑分析") sr_analysis = support_resistance.analyze_support_resistance(kline_data) print("🛡️ 压力支撑分析结果:") support_levels = sr_analysis['support_resistance_levels']['support_levels'] resistance_levels = sr_analysis['support_resistance_levels']['resistance_levels'] print(f"支撑位: {[f'{level:.2f}' for level in support_levels[:3]]}") print(f"阻力位: {[f'{level:.2f}' for level in resistance_levels[:3]]}") # 4. 风险分析 print_section("4. 风险分析") current_price = kline_data['close'].iloc[-1] atr = trend_analysis.get('atr', 20) # 计算止损位 stop_loss_long = risk_manager.calculate_stop_loss(kline_data, current_price, "long") stop_loss_short = risk_manager.calculate_stop_loss(kline_data, current_price, "short") # 计算仓位大小 account_balance = 1000000 # 100万账户 position_info = risk_manager.calculate_position_size(account_balance, kline_data, "long", current_price) print("⚡ 风险分析结果:") print(f"ATR: {atr:.2f}") print(f"做多止损: {stop_loss_long:.2f}") print(f"做空止损: {stop_loss_short:.2f}") print(f"建议仓位: {position_info['suggested_units']} 手") print(f"风险比例: {position_info['actual_risk_percent']*100:.2f}%") print(f"杠杆比例: {position_info['leverage']:.2f}") # 5. 换月分析 print_section("5. 换月分析") rollover_analysis = rollover_detector.analyze_rollover(symbol, kline_data) print("📅 换月分析结果:") print(f"交割日期: {rollover_analysis['expire_date']}") print(f"距离交割日: {rollover_analysis['days_to_delivery']} 天") print(f"预警级别: {rollover_analysis['warning_level']}") print(f"流动性风险: {rollover_analysis['liquidity_risk']}") print(f"换月建议: {rollover_analysis['rollover_warning']['warning_message']}") # 6. AI 智能研判 print_section("6. AI 智能研判") # 准备数据 market_data = { 'symbol': symbol, 'latest_price': current_price, 'volume': kline_data['volume'].iloc[-1], 'open_interest': kline_data['open_interest'].iloc[-1], 'timeframe': '1d' } technical_indicators = { 'macd': {'signal': '金叉'}, 'rsi': 55, 'bollinger': {'position': '中轨附近'}, 'kdj': {'signal': '金叉'}, 'atr': atr } trend_data = { 'adx': trend_analysis['adx'], 'trend_strength': trend_analysis['trend_strength'], 'trend_direction': trend_analysis['trend_direction'], 'ma_relationship': trend_analysis['ma_relationship'], 'multi_period_analysis': trend_analysis['multi_period_analysis'], 'overall_trend': trend_analysis['overall_trend'], 'win_rate': win_rate } risk_metrics = { 'stop_loss': stop_loss_long, 'target_price': resistance_levels[0] if resistance_levels else current_price * 1.05, 'profit_loss_ratio': 1.8, 'position_size': position_info['suggested_units'], 'risk_ratio': position_info['actual_risk_percent'] * 100 } # AI 分析 ai_analysis = deepseek_agent.analyze_market(market_data, technical_indicators, trend_data, risk_metrics) print("🤖 AI 分析结果:") print(f"趋势判断: {ai_analysis.get('trend_judgment', '未知')}") print(f"胜率评估: {ai_analysis.get('win_rate_assessment', '未知')}") print(f"风险预警: {ai_analysis.get('risk_warning', '未知')}") print(f"交易建议: {ai_analysis.get('trade_recommendation', '未知')}") print(f"分析逻辑: {ai_analysis.get('analysis_logic', '未知')}") # 7. 生成交易建议 print_section("7. 交易建议") recommendation = deepseek_agent.generate_trade_recommendation(ai_analysis) print("📋 交易建议详情:") print(f"交易方向: {recommendation.get('direction', '未知')}") print(f"入场价格: {recommendation.get('entry_price', '未知')}") print(f"止损价格: {recommendation.get('stop_loss', '未知')}") print(f"目标价格: {recommendation.get('target_price', '未知')}") print(f"建议仓位: {recommendation.get('position_size', '未知')} 手") print(f"执行计划: {recommendation.get('execution_plan', '未知')}") print(f"风险提示: {recommendation.get('risk_tips', '未知')}") # 8. 保存分析结果 print_section("8. 保存分析结果") # 创建分析结果对象 analysis_result = AnalysisResult(symbol) analysis_result.trend = trend_analysis['overall_trend'] analysis_result.probability = win_rate analysis_result.direction = recommendation.get('direction', 'wait') analysis_result.cycle = cycle analysis_result.atr = atr analysis_result.adx = trend_analysis['adx'] analysis_result.support = support_levels[0] if support_levels else None analysis_result.resistance = resistance_levels[0] if resistance_levels else None analysis_result.stop_loss = recommendation.get('stop_loss') analysis_result.target_price = recommendation.get('target_price') analysis_result.position_size = recommendation.get('position_size') analysis_result.risk_ratio = position_info['actual_risk_percent'] * 100 analysis_result.fund_flow = fund_flow_analysis analysis_result.signals = { 'trend': trend_analysis['overall_trend'], 'fund': fund_flow_analysis['fund_signal'], 'risk': rollover_analysis['liquidity_risk'], 'ai': recommendation.get('direction', 'wait') } # 保存到数据库 result_dict = analysis_result.to_dict() success = data_storage.save_analysis_result(result_dict) if success: print("✅ 分析结果已保存到数据库") else: print("❌ 保存分析结果失败") # 9. 生成综合报告 print_section("9. 综合分析报告") print_header("AI 期货分析系统 - 综合报告") print(f"合约: {symbol}") print(f"分析时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") print(f"最新价格: {current_price:.2f}") print(f"趋势判断: {trend_analysis['overall_trend']}") print(f"胜率评估: {win_rate:.2f}%") print(f"资金信号: {fund_flow_analysis['fund_signal']}") print(f"交易方向: {recommendation.get('direction', 'wait')}") print(f"建议仓位: {recommendation.get('position_size', '未知')} 手") print(f"止损价格: {recommendation.get('stop_loss', '未知')}") print(f"目标价格: {recommendation.get('target_price', '未知')}") print(f"风险等级: {rollover_analysis['liquidity_risk']}") print(f"换月预警: {rollover_analysis['rollover_warning']['overall_warning']}") print_header("演示完成") print("感谢使用 AI 期货分析系统！") print("系统已完成以下功能:") print("✅ 数据获取与存储") print("✅ 趋势分析与胜率计算") print("✅ 资金流向监控") print("✅ 压力支撑分析") print("✅ 风险控制与仓位管理") print("✅ 换月预警") print("✅ AI 智能研判") print("✅ 交易建议生成") if __name__ == "__main__": main()