3209 lines
131 KiB
Python
3209 lines
131 KiB
Python
# -*- coding: utf-8 -*-
|
||
import sys
|
||
import os
|
||
from datetime import datetime, timedelta
|
||
import pandas as pd
|
||
import uuid
|
||
import json
|
||
from threading import Thread
|
||
from sqlalchemy import text
|
||
from src.fundamentals_llm.fundamental_analysis_database import get_db
|
||
|
||
# 添加项目根目录到 Python 路径
|
||
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||
|
||
from flask import Flask, jsonify, request, send_from_directory, render_template
|
||
from flask_cors import CORS
|
||
import logging
|
||
|
||
# 导入企业筛选器
|
||
from src.fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
|
||
# 导入股票回测器
|
||
from src.stock_analysis_v2 import run_backtest
|
||
|
||
# 导入PE/PB估值分析器
|
||
from src.valuation_analysis.pe_pb_analysis import ValuationAnalyzer
|
||
|
||
# 导入行业估值分析器
|
||
from src.valuation_analysis.industry_analysis import IndustryAnalyzer
|
||
|
||
# 导入沪深港通监控器
|
||
from src.valuation_analysis.hsgt_monitor import HSGTMonitor
|
||
|
||
# 导入融资融券数据采集器
|
||
from src.valuation_analysis.eastmoney_rzrq_collector import EastmoneyRzrqCollector
|
||
|
||
# 导入恐贪指数管理器
|
||
from src.valuation_analysis.fear_greed_index import FearGreedIndexManager
|
||
|
||
# 导入指数分析器
|
||
from src.valuation_analysis.index_analyzer import IndexAnalyzer
|
||
|
||
# 导入股票日线数据采集器
|
||
from src.scripts.stock_daily_data_collector import collect_stock_daily_data, collect_stock_daily_data_optimized
|
||
from src.scripts.stock_daily_data_collector_v2 import collect_stock_daily_data_v2
|
||
|
||
from valuation_analysis.financial_analysis import FinancialAnalyzer
|
||
from src.valuation_analysis.stock_price_collector import StockPriceCollector
|
||
from src.quantitative_analysis.batch_stock_price_collector import fetch_and_store_stock_data
|
||
from src.quantitative_analysis.hk_stock_price_collector import fetch_and_store_hk_stock_data
|
||
from src.quantitative_analysis.momentum_analysis import MomentumAnalyzer
|
||
|
||
# 设置日志
|
||
logging.basicConfig(
|
||
level=logging.INFO,
|
||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
|
||
handlers=[
|
||
logging.StreamHandler(), # 输出到控制台
|
||
logging.FileHandler(f'logs/app_{datetime.now().strftime("%Y%m%d")}.log', encoding='utf-8') # 输出到文件
|
||
]
|
||
)
|
||
|
||
# 确保logs和results目录存在
|
||
os.makedirs('logs', exist_ok=True)
|
||
os.makedirs('results', exist_ok=True)
|
||
os.makedirs('results/tasks', exist_ok=True)
|
||
os.makedirs('static/results', exist_ok=True)
|
||
|
||
logger = logging.getLogger(__name__)
|
||
logger.info("Flask应用启动")
|
||
|
||
# 创建 Flask 应用
|
||
app = Flask(__name__, static_folder='static')
|
||
CORS(app) # 启用跨域请求支持
|
||
|
||
# 创建企业筛选器实例
|
||
screener = EnterpriseScreener()
|
||
|
||
# 创建估值分析器实例
|
||
valuation_analyzer = ValuationAnalyzer()
|
||
|
||
# 创建行业分析器实例
|
||
industry_analyzer = IndustryAnalyzer()
|
||
|
||
# 创建监控器实例
|
||
hsgt_monitor = HSGTMonitor()
|
||
|
||
# 创建融资融券数据采集器实例
|
||
em_rzrq_collector = EastmoneyRzrqCollector()
|
||
|
||
# 创建恐贪指数管理器实例
|
||
fear_greed_manager = FearGreedIndexManager()
|
||
|
||
# 创建指数分析器实例
|
||
index_analyzer = IndexAnalyzer()
|
||
|
||
# 获取项目根目录
|
||
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||
REPORTS_DIR = os.path.join(ROOT_DIR, 'src', 'reports')
|
||
|
||
# 确保reports目录存在
|
||
os.makedirs(REPORTS_DIR, exist_ok=True)
|
||
logger.info(f"报告目录路径: {REPORTS_DIR}")
|
||
|
||
# 存储回测任务状态的字典
|
||
backtest_tasks = {}
|
||
|
||
# 融资融券数据采集任务列表
|
||
rzrq_tasks = {}
|
||
|
||
def run_backtest_task(task_id, stocks_buy_dates, end_date):
|
||
"""
|
||
在后台运行回测任务
|
||
"""
|
||
try:
|
||
logger.info(f"开始执行回测任务 {task_id}")
|
||
# 更新任务状态为进行中
|
||
backtest_tasks[task_id]['status'] = 'running'
|
||
|
||
# 运行回测
|
||
results, stats_list = run_backtest(stocks_buy_dates, end_date)
|
||
|
||
# 如果回测成功
|
||
if results and stats_list:
|
||
# 计算总体统计
|
||
stats_df = pd.DataFrame(stats_list)
|
||
total_profit = stats_df['final_profit'].sum()
|
||
avg_win_rate = stats_df['win_rate'].mean()
|
||
avg_holding_days = stats_df['avg_holding_days'].mean()
|
||
|
||
# 找出最佳止盈比例(假设为0.15，实际应从回测结果中分析得出)
|
||
best_take_profit_pct = 0.15
|
||
|
||
# 获取图表URL
|
||
chart_urls = {
|
||
"all_stocks": f"/static/results/{task_id}/all_stocks_analysis.png",
|
||
"profit_matrix": f"/static/results/{task_id}/profit_matrix_analysis.png"
|
||
}
|
||
|
||
# 保存股票详细统计
|
||
stock_stats = []
|
||
for stat in stats_list:
|
||
stock_stats.append({
|
||
"symbol": stat['symbol'],
|
||
"total_trades": int(stat['total_trades']),
|
||
"profitable_trades": int(stat['profitable_trades']),
|
||
"loss_trades": int(stat['loss_trades']),
|
||
"win_rate": float(stat['win_rate']),
|
||
"avg_holding_days": float(stat['avg_holding_days']),
|
||
"final_profit": float(stat['final_profit']),
|
||
"entry_count": int(stat['entry_count'])
|
||
})
|
||
|
||
# 构建结果数据
|
||
result_data = {
|
||
"task_id": task_id,
|
||
"status": "completed",
|
||
"results": {
|
||
"total_profit": float(total_profit),
|
||
"win_rate": float(avg_win_rate),
|
||
"avg_holding_days": float(avg_holding_days),
|
||
"best_take_profit_pct": best_take_profit_pct,
|
||
"stock_stats": stock_stats,
|
||
"chart_urls": chart_urls
|
||
}
|
||
}
|
||
|
||
# 保存结果到文件
|
||
task_result_path = os.path.join('results', 'tasks', f"{task_id}.json")
|
||
with open(task_result_path, 'w', encoding='utf-8') as f:
|
||
json.dump(result_data, f, ensure_ascii=False, indent=2)
|
||
|
||
# 更新任务状态为已完成
|
||
backtest_tasks[task_id].update({
|
||
'status': 'completed',
|
||
'results': result_data['results']
|
||
})
|
||
|
||
logger.info(f"回测任务 {task_id} 已完成")
|
||
else:
|
||
# 更新任务状态为失败
|
||
backtest_tasks[task_id]['status'] = 'failed'
|
||
backtest_tasks[task_id]['error'] = "回测未产生有效结果"
|
||
logger.error(f"回测任务 {task_id} 失败：回测未产生有效结果")
|
||
except Exception as e:
|
||
# 更新任务状态为失败
|
||
backtest_tasks[task_id]['status'] = 'failed'
|
||
backtest_tasks[task_id]['error'] = str(e)
|
||
logger.error(f"回测任务 {task_id} 失败：{str(e)}")
|
||
|
||
@app.route('/scheduler/stockRealtimePrice/collection', methods=['GET'])
|
||
def update_stock_realtime_price():
|
||
"""更新实时股价数据 周内的9点半、10点半、11点半、2点、3点各更新一次"""
|
||
try:
|
||
collector = StockPriceCollector()
|
||
collector.update_latest_data()
|
||
except Exception as e:
|
||
logger.error(f"更新实时股价数据失败: {e}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
|
||
@app.route('/scheduler/stockDaily/collection', methods=['GET'])
|
||
def run_stock_daily_collection1():
|
||
"""执行股票日线数据采集任务 下午3点四十开始"""
|
||
try:
|
||
logger.info("开始执行股票日线数据采集")
|
||
# 获取当天日期
|
||
today = datetime.now().strftime('%Y-%m-%d')
|
||
|
||
# 定义数据库连接地址
|
||
db_url = 'mysql+pymysql://root:Chlry#$.8@192.168.18.199:3306/db_gp_cj'
|
||
# collect_stock_daily_data(db_url, today)
|
||
collect_stock_daily_data_v2(db_url)
|
||
except Exception as e:
|
||
logger.error(f"启动股票日线数据采集任务失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
@app.route('/scheduler/stockDailyHK/collection', methods=['GET'])
|
||
def run_stock_daily_collection2():
|
||
"""执行股票日线数据采集任务 下午4点开始"""
|
||
try:
|
||
logger.info("开始执行股票日线数据采集")
|
||
# 获取当天日期
|
||
today = datetime.now().strftime('%Y-%m-%d')
|
||
|
||
# 定义数据库连接地址
|
||
db_url = 'mysql+pymysql://root:Chlry#$.8@192.168.18.199:3306/db_gp_cj'
|
||
collect_stock_daily_data_optimized(db_url, today)
|
||
except Exception as e:
|
||
logger.error(f"启动股票日线数据采集任务失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
|
||
@app.route('/scheduler/rzrq/collection', methods=['GET'])
|
||
def run_rzrq_initial_collection1():
|
||
"""执行融资融券数据更新采集 下午7点开始"""
|
||
try:
|
||
# 执行采集
|
||
em_rzrq_collector.initial_data_collection()
|
||
except Exception as e:
|
||
logger.error(f"启动融资融券数据更新任务失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
@app.route('/scheduler/financial/analysis', methods=['GET'])
|
||
def scheduler_financial_analysis():
|
||
"""预计算所有股票的财务分析数据 早晚各一次"""
|
||
try:
|
||
from src.valuation_analysis.financial_analysis import FinancialAnalyzer
|
||
|
||
analyzer = FinancialAnalyzer()
|
||
analyzer.analyze_financial_data('600584.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('600584.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('600584.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('601138.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('601138.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('601138.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('601698.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('601698.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('601698.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('603055.SZ', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603055.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603055.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('603658.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603658.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603658.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('603659.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603659.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603659.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('603986.SZ', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603986.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('603986.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('688008.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688008.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688008.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('688012.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688012.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688012.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('688072.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688072.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688072.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('688596.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688596.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('688596.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('000733.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('000733.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('000733.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('002409.SZ', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('002409.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('002409.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('002747.SZ', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('002747.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('002747.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('300603.SH', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('300603.SH', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('300603.SH', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
analyzer.analyze_financial_data('300661.SZ', current_year = '2024-12-31', previous_year = '2023-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('300661.SZ', current_year = '2023-12-31', previous_year = '2022-12-31', force_update=True)
|
||
analyzer.analyze_financial_data('300661.SZ', current_year = '2022-12-31', previous_year = '2021-12-31', force_update=True)
|
||
|
||
except Exception as e:
|
||
logger.error(f"预计算所有股票的财务分析数据失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
@app.route('/scheduler/industry/crowding', methods=['GET'])
|
||
def precalculate_industry_crowding_batch():
|
||
"""批量预计算行业和概念板块的拥挤度指标"""
|
||
try:
|
||
from src.valuation_analysis.industry_analysis import IndustryAnalyzer
|
||
|
||
analyzer = IndustryAnalyzer()
|
||
# 固定行业和概念板块
|
||
industries = ["煤炭开采", "焦炭加工", "油气开采", "石油化工", "油服工程", "日用化工", "化纤", "化学原料", "化学制品", "塑料", "橡胶", "农用化工", "非金属材料", "冶钢原料", "普钢", "特钢", "工业金属", "贵金属", "能源金属", "稀有金属", "金属新材料", "水泥", "玻璃玻纤", "装饰建材", "种植业", "养殖业", "林业", "渔业", "饲料", "农产品加工", "动物保健", "酿酒", "饮料乳品", "调味品", "休闲食品", "食品加工", "纺织制造", "服装家纺", "饰品", "造纸", "包装印刷", "家居用品", "文娱用品", "白色家电", "黑色家电", "小家电", "厨卫电器", "家电零部件", "一般零售", "商业物业经营", "专业连锁", "贸易", "电子商务", "乘用车", "商用车", "汽车零部件", "汽车服务", "摩托车及其他", "化学制药", "生物制品", "中药", "医药商业", "医疗器械", "医疗服务", "医疗美容", "电机制造", "电池", "电网设备", "光伏设备", "风电设备", "其他发电设备", "地面兵装", "航空装备", "航天装备", "航海装备", "军工电子", "轨交设备", "通用设备", "专用设备", "工程机械", "自动化设备", "半导体", "消费电子", "光学光电", "元器件", "其他电子", "通信设备", "通信工程", "电信服务", "IT设备", "软件服务", "云服务", "产业互联网", "游戏", "广告营销", "影视院线", "数字媒体", "出版业", "广播电视", "全国性银行", "地方性银行", "证券", "保险", "多元金融", "房屋建设", "基础建设", "专业工程", "工程咨询服务", "装修装饰", "房地产开发", "房产服务", "体育", "教育培训", "酒店餐饮", "旅游", "专业服务", "公路铁路", "航空机场", "航运港口", "物流", "电力", "燃气", "水务", "环保设备", "环境治理", "环境监测", "综合类"]
|
||
concepts = ["通达信88", "海峡西岸", "海南自贸", "一带一路", "上海自贸", "雄安新区", "粤港澳", "ST板块", "次新股", "含H股", "含B股", "含GDR", "含可转债", "国防军工", "军民融合", "大飞机", "稀缺资源", "5G概念", "碳中和", "黄金概念", "物联网", "创投概念", "航运概念", "铁路基建", "高端装备", "核电核能", "光伏", "风电", "锂电池概念", "燃料电池", "HJT电池", "固态电池", "钠电池", "钒电池", "TOPCon电池", "钙钛矿电池", "BC电池", "氢能源", "稀土永磁", "盐湖提锂", "锂矿", "水利建设", "卫星导航", "可燃冰", "页岩气", "生物疫苗", "基因概念", "维生素", "仿制药", "创新药", "免疫治疗", "CXO概念", "节能环保", "食品安全", "白酒概念", "代糖概念", "猪肉", "鸡肉", "水产品", "碳纤维", "石墨烯", "3D打印", "苹果概念", "阿里概念", "腾讯概念", "小米概念", "百度概念", "华为鸿蒙", "华为海思", "华为汽车", "华为算力", "特斯拉概念", "消费电子概念", "汽车电子", "无线耳机", "生物质能", "地热能", "充电桩", "新能源车", "换电概念", "高压快充", "草甘膦", "安防服务", "垃圾分类", "核污染防治", "风沙治理", "乡村振兴", "土地流转", "体育概念", "博彩概念", "赛马概念", "分散染料", "聚氨酯", "云计算", "边缘计算", "网络游戏", "信息安全", "国产软件", "大数据", "数据中心", "芯片", "MCU芯片", "汽车芯片", "存储芯片", "互联金融", "婴童概念", "养老概念", "网红经济", "民营医院", "特高压", "智能电网", "智能穿戴", "智能交通", "智能家居", "智能医疗", "智慧城市", "智慧政务", "机器人概念", "机器视觉", "超导概念", "职业教育", "物业管理概念", "虚拟现实", "数字孪生", "钛金属", "钴金属", "镍金属", "氟概念", "磷概念", "无人机", "PPP概念", "新零售", "跨境电商", "量子科技", "无人驾驶", "ETC概念", "胎压监测", "OLED概念", "MiniLED", "MicroLED", "超清视频", "区块链", "数字货币", "人工智能", "租购同权", "工业互联", "知识产权", "工业大麻", "工业气体", "人造肉", "预制菜", "种业", "化肥概念", "操作系统", "光刻机", "第三代半导体", "远程办公", "口罩防护", "医废处理", "虫害防治", "超级电容", "C2M概念", "地摊经济", "冷链物流", "抖音概念", "降解塑料", "医美概念", "人脑工程", "烟草概念", "新型烟草", "有机硅概念", "新冠检测", "BIPV概念", "地下管网", "储能", "新材料", "工业母机", "一体压铸", "汽车热管理", "汽车拆解", "NMN概念", "国资云", "元宇宙概念", "NFT概念", "云游戏", "天然气", "绿色电力", "培育钻石", "信创", "幽门螺杆菌", "电子纸", "新冠药概念", "免税概念", "PVDF概念", "装配式建筑", "绿色建筑", "东数西算", "跨境支付CIPS", "中俄贸易", "电子身份证", "家庭医生", "辅助生殖", "肝炎概念", "新型城镇", "粮食概念", "超临界发电", "虚拟电厂", "动力电池回收", "PCB概念", "先进封装", "热泵概念", "EDA概念", "光热发电", "供销社", "Web3概念", "DRG-DIP", "AIGC概念", "复合铜箔", "数据确权", "数据要素", "POE胶膜", "血氧仪", "旅游概念", "中特估", "ChatGPT概念", "CPO概念", "数字水印", "毫米波雷达", "工业软件", "6G概念", "时空大数据", "可控核聚变", "知识付费", "算力租赁", "光通信", "混合现实", "英伟达概念", "减速器", "减肥药", "合成生物", "星闪概念", "液冷服务器", "新型工业化", "短剧游戏", "多模态AI", "PEEK材料", "小米汽车概念", "飞行汽车", "Sora概念", "人形机器人", "AI手机PC", "低空经济", "铜缆高速连接", "军工信息化", "玻璃基板", "商业航天", "车联网", "财税数字化", "折叠屏", "AI眼镜", "智谱AI", "IP经济", "宠物经济", "小红书概念", "AI智能体", "DeepSeek概念", "AI医疗概念", "海洋经济", "外骨骼机器人", "军贸概念"]
|
||
|
||
# 批量计算行业和概念板块拥挤度
|
||
analyzer.batch_calculate_industry_crowding(industries, concepts)
|
||
|
||
logger.info("批量计算行业和概念板块的拥挤度指标完成")
|
||
except Exception as e:
|
||
logger.error(f"批量计算行业拥挤度指标失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "success"
|
||
}), 200
|
||
|
||
@app.route('/')
|
||
def index():
|
||
"""渲染主页"""
|
||
return render_template('index.html')
|
||
|
||
@app.route('/api/backtest/run', methods=['POST'])
|
||
def start_backtest():
|
||
"""启动回测任务
|
||
|
||
请求体格式:
|
||
{
|
||
"stocks_buy_dates": {
|
||
"SH600522": ["2022-05-10", "2022-06-10"], // 股票代码: [买入日期列表]
|
||
"SZ002340": ["2022-06-15"],
|
||
"SH601615": ["2022-07-20", "2022-08-01"]
|
||
},
|
||
"end_date": "2022-10-20" // 所有股票共同的结束日期
|
||
}
|
||
|
||
返回内容:
|
||
{
|
||
"task_id": "backtask-khkerhy4u237y489237489truiy8432"
|
||
}
|
||
"""
|
||
try:
|
||
# 从请求体获取参数
|
||
data = request.get_json()
|
||
|
||
if not data:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供JSON数据"
|
||
}), 400
|
||
|
||
stocks_buy_dates = data.get('stocks_buy_dates')
|
||
end_date = data.get('end_date')
|
||
|
||
if not stocks_buy_dates or not isinstance(stocks_buy_dates, dict):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供stocks_buy_dates字典"
|
||
}), 400
|
||
|
||
if not end_date or not isinstance(end_date, str):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供有效的end_date"
|
||
}), 400
|
||
|
||
# 验证日期格式
|
||
try:
|
||
datetime.strptime(end_date, '%Y-%m-%d')
|
||
for stock_code, buy_dates in stocks_buy_dates.items():
|
||
if not isinstance(buy_dates, list):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"请求格式错误: 股票 {stock_code} 的买入日期必须是列表"
|
||
}), 400
|
||
for buy_date in buy_dates:
|
||
datetime.strptime(buy_date, '%Y-%m-%d')
|
||
except ValueError as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"日期格式错误: {str(e)}"
|
||
}), 400
|
||
|
||
# 生成任务ID
|
||
task_id = f"backtask-{uuid.uuid4().hex[:16]}"
|
||
|
||
# 创建任务目录
|
||
task_dir = os.path.join('static', 'results', task_id)
|
||
os.makedirs(task_dir, exist_ok=True)
|
||
|
||
# 记录任务信息
|
||
backtest_tasks[task_id] = {
|
||
'status': 'pending',
|
||
'created_at': datetime.now().isoformat(),
|
||
'stocks_buy_dates': stocks_buy_dates,
|
||
'end_date': end_date
|
||
}
|
||
|
||
# 创建线程运行回测
|
||
thread = Thread(target=run_backtest_task, args=(task_id, stocks_buy_dates, end_date))
|
||
thread.daemon = True
|
||
thread.start()
|
||
|
||
logger.info(f"已创建回测任务: {task_id}")
|
||
|
||
return jsonify({
|
||
"task_id": task_id
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"创建回测任务失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"创建回测任务失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/backtest/status', methods=['GET'])
|
||
def check_backtest_status():
|
||
"""查询回测任务状态
|
||
|
||
参数:
|
||
- task_id: 回测任务ID
|
||
|
||
返回内容:
|
||
{
|
||
"task_id": "backtask-khkerhy4u237y489237489truiy8432",
|
||
"status": "running" | "completed" | "failed",
|
||
"created_at": "2023-12-01T10:30:45",
|
||
"error": "错误信息（如有）"
|
||
}
|
||
"""
|
||
try:
|
||
task_id = request.args.get('task_id')
|
||
|
||
if not task_id:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供task_id参数"
|
||
}), 400
|
||
|
||
# 检查任务是否存在
|
||
if task_id not in backtest_tasks:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"任务不存在: {task_id}"
|
||
}), 404
|
||
|
||
# 获取任务信息
|
||
task_info = backtest_tasks[task_id]
|
||
|
||
# 构建响应
|
||
response = {
|
||
"task_id": task_id,
|
||
"status": task_info['status'],
|
||
"created_at": task_info['created_at']
|
||
}
|
||
|
||
# 如果任务失败，添加错误信息
|
||
if task_info['status'] == 'failed' and 'error' in task_info:
|
||
response['error'] = task_info['error']
|
||
|
||
return jsonify(response)
|
||
|
||
except Exception as e:
|
||
logger.error(f"查询任务状态失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"查询任务状态失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/backtest/result', methods=['GET'])
|
||
def get_backtest_result():
|
||
"""获取回测任务结果
|
||
|
||
参数:
|
||
- task_id: 回测任务ID
|
||
|
||
返回内容:
|
||
{
|
||
"task_id": "backtask-2023121-001",
|
||
"status": "completed",
|
||
"results": {
|
||
"total_profit": 123456.78,
|
||
"win_rate": 75.5,
|
||
"avg_holding_days": 12.3,
|
||
"best_take_profit_pct": 0.15,
|
||
"stock_stats": [...],
|
||
"chart_urls": {
|
||
"all_stocks": "/static/results/backtask-2023121-001/all_stocks_analysis.png",
|
||
"profit_matrix": "/static/results/backtask-2023121-001/profit_matrix_analysis.png"
|
||
}
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
task_id = request.args.get('task_id')
|
||
|
||
if not task_id:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供task_id参数"
|
||
}), 400
|
||
|
||
# 检查任务是否存在
|
||
if task_id not in backtest_tasks:
|
||
# 尝试从文件加载
|
||
task_result_path = os.path.join('results', 'tasks', f"{task_id}.json")
|
||
if os.path.exists(task_result_path):
|
||
with open(task_result_path, 'r', encoding='utf-8') as f:
|
||
result_data = json.load(f)
|
||
return jsonify(result_data)
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"任务不存在: {task_id}"
|
||
}), 404
|
||
|
||
# 获取任务信息
|
||
task_info = backtest_tasks[task_id]
|
||
|
||
# 检查任务是否完成
|
||
if task_info['status'] != 'completed':
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"任务尚未完成或已失败: {task_info['status']}"
|
||
}), 400
|
||
|
||
# 构建响应
|
||
response = {
|
||
"task_id": task_id,
|
||
"status": "completed",
|
||
"results": task_info['results']
|
||
}
|
||
|
||
return jsonify(response)
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取任务结果失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"获取任务结果失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/reports/<path:filename>')
|
||
def serve_report(filename):
|
||
"""提供PDF报告的访问"""
|
||
try:
|
||
logger.info(f"请求文件: {filename}")
|
||
logger.info(f"从目录: {REPORTS_DIR} 提供文件")
|
||
return send_from_directory(REPORTS_DIR, filename, as_attachment=True)
|
||
except Exception as e:
|
||
logger.error(f"提供报告文件失败: {str(e)}")
|
||
return jsonify({"error": "文件不存在"}), 404
|
||
|
||
@app.route('/api/health', methods=['GET'])
|
||
def health_check():
|
||
"""健康检查接口"""
|
||
return jsonify({"status": "ok", "message": "Service is running"})
|
||
|
||
@app.route('/api/stock_profiles', methods=['GET'])
|
||
def get_stock_profiles():
|
||
"""获取企业画像筛选结果列表"""
|
||
return jsonify({
|
||
"profiles": [
|
||
{"id": 1, "name": "高成长潜力企业", "method": "high_growth"},
|
||
{"id": 2, "name": "稳定型龙头企业", "method": "stable_leaders"},
|
||
{"id": 3, "name": "短期投资机会", "method": "short_term"},
|
||
{"id": 4, "name": "价值型投资标的", "method": "value_investment"},
|
||
{"id": 5, "name": "困境反转机会", "method": "turnaround"},
|
||
{"id": 6, "name": "风险规避标的", "method": "risk_averse"},
|
||
{"id": 7, "name": "创新驱动型企业", "method": "innovation_driven"},
|
||
{"id": 8, "name": "行业整合机会", "method": "industry_integration"},
|
||
{"id": 9, "name": "推荐投资企业", "method": "recommended"}
|
||
]
|
||
})
|
||
|
||
@app.route('/api/screen/<profile_type>', methods=['GET'])
|
||
def screen_stocks(profile_type):
|
||
"""根据企业画像类型筛选股票
|
||
|
||
Args:
|
||
profile_type: 企业画像类型 (method 字段值)
|
||
"""
|
||
try:
|
||
# 解析limit参数
|
||
limit = request.args.get('limit', None, type=int)
|
||
|
||
# 处理别名
|
||
if profile_type == 'innovation_driven':
|
||
profile_type = 'innovation'
|
||
elif profile_type == 'industry_integration':
|
||
profile_type = 'integration'
|
||
|
||
# 映射画像类型到筛选方法
|
||
method_map = {
|
||
'high_growth': screener.screen_high_growth_stocks,
|
||
'stable_leaders': screener.screen_stable_leaders,
|
||
'short_term': screener.screen_short_term_opportunities,
|
||
'value_investment': screener.screen_value_investment_stocks,
|
||
'turnaround': screener.screen_turnaround_opportunities,
|
||
'risk_averse': screener.screen_risk_averse_stocks,
|
||
'innovation': screener.screen_innovation_driven_stocks,
|
||
'integration': screener.screen_industry_integration_stocks,
|
||
'recommended': screener.screen_multi_term_investment_stocks
|
||
}
|
||
|
||
# 检查请求的画像类型是否有效
|
||
if profile_type not in method_map:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"Invalid profile type: {profile_type}"
|
||
}), 400
|
||
|
||
# 调用相应的筛选方法
|
||
stocks = method_map[profile_type](limit=limit)
|
||
|
||
# 转换结果格式
|
||
result = []
|
||
for code, name in stocks:
|
||
result.append({
|
||
"code": code,
|
||
"name": name
|
||
})
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"profile_type": profile_type,
|
||
"count": len(result),
|
||
"stocks": result
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"筛选股票失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"Failed to screen stocks: {str(e)}"
|
||
}), 500
|
||
|
||
# 条件筛选接口，接受自定义的筛选条件
|
||
@app.route('/api/screen/custom', methods=['POST'])
|
||
def screen_custom():
|
||
"""使用自定义条件筛选股票"""
|
||
try:
|
||
# 从请求体获取筛选条件
|
||
data = request.get_json()
|
||
|
||
if not data or 'conditions' not in data:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "Missing conditions in request body"
|
||
}), 400
|
||
|
||
# 调用通用筛选方法
|
||
stocks = screener._screen_stocks_by_conditions(data['conditions'])
|
||
|
||
# 转换结果格式
|
||
result = []
|
||
for code, name in stocks:
|
||
result.append({
|
||
"code": code,
|
||
"name": name
|
||
})
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"count": len(result),
|
||
"stocks": result
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"自定义筛选股票失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"Failed to screen stocks with custom conditions: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/generate_reports', methods=['POST'])
|
||
def generate_reports():
|
||
"""为指定的股票列表生成PDF投资报告
|
||
|
||
请求体格式:
|
||
{
|
||
"stocks": [
|
||
["603690", "至纯科技"],
|
||
["688053", "思科瑞"],
|
||
["300750", "宁德时代"]
|
||
]
|
||
}
|
||
"""
|
||
try:
|
||
# 从请求体获取股票列表
|
||
data = request.get_json()
|
||
|
||
if not data or 'stocks' not in data or not isinstance(data['stocks'], list):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供股票列表"
|
||
}), 400
|
||
|
||
# 检查股票列表格式
|
||
stocks = data['stocks']
|
||
if not all(isinstance(item, list) and len(item) == 2 for item in stocks):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "股票列表格式错误: 每个股票应该是 [代码, 名称] 格式"
|
||
}), 400
|
||
|
||
# 导入 PDF 生成器模块
|
||
try:
|
||
from src.fundamentals_llm.pdf_generator import PDFGenerator
|
||
except ImportError:
|
||
try:
|
||
from fundamentals_llm.pdf_generator import PDFGenerator
|
||
except ImportError as e:
|
||
logger.error(f"无法导入 PDF 生成器模块: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: PDF 生成器模块不可用, 错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 生成报告
|
||
generated_reports = []
|
||
for stock_code, stock_name in stocks:
|
||
try:
|
||
# 创建 PDF 生成器实例
|
||
generator = PDFGenerator()
|
||
# 调用 PDF 生成器
|
||
report_path = generator.generate_pdf(
|
||
title=f"{stock_name}({stock_code}) 基本面分析报告",
|
||
content_dict={}, # 这里需要传入实际的内容字典
|
||
filename=f"{stock_name}_{stock_code}_analysis.pdf"
|
||
)
|
||
generated_reports.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"report_path": report_path,
|
||
"status": "success"
|
||
})
|
||
logger.info(f"成功生成 {stock_name}({stock_code}) 的投资报告: {report_path}")
|
||
except Exception as e:
|
||
logger.error(f"生成 {stock_name}({stock_code}) 的投资报告失败: {str(e)}")
|
||
generated_reports.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": str(e)
|
||
})
|
||
|
||
# 返回结果
|
||
return jsonify({
|
||
"status": "success",
|
||
"message": f"处理了 {len(stocks)} 个股票的报告生成请求",
|
||
"reports": generated_reports
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"处理报告生成请求失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"Failed to process report generation request: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/recommended_stocks', methods=['GET'])
|
||
def recommended_stocks():
|
||
"""获取系统推荐的投资股票
|
||
|
||
该接口会返回系统基于基本面分析推荐的股票列表，具有较高投资价值
|
||
|
||
可以通过以下参数进行过滤:
|
||
- profile_type: 企业画像类型，例如 'high_growth', 'stable_leaders' 等
|
||
- limit: 限制返回的股票数量
|
||
"""
|
||
try:
|
||
# 解析请求参数
|
||
profile_type = request.args.get('profile_type', 'high_growth')
|
||
limit = request.args.get('limit', 10, type=int)
|
||
|
||
# 导入筛选器模块
|
||
try:
|
||
from src.fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError:
|
||
try:
|
||
from fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError as e:
|
||
logger.error(f"无法导入企业筛选器模块: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 企业筛选器模块不可用, 错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建筛选器实例
|
||
screener = EnterpriseScreener()
|
||
|
||
# 根据类型获取推荐股票
|
||
try:
|
||
if profile_type == 'recommended':
|
||
stocks = screener.screen_multi_term_investment_stocks(limit=limit)
|
||
elif profile_type == 'high_growth':
|
||
stocks = screener.screen_high_growth_stocks(limit=limit)
|
||
elif profile_type == 'stable_leaders':
|
||
stocks = screener.screen_stable_leaders(limit=limit)
|
||
elif profile_type == 'short_term':
|
||
stocks = screener.screen_short_term_opportunities(limit=limit)
|
||
elif profile_type == 'value_investment':
|
||
stocks = screener.screen_value_investment_stocks(limit=limit)
|
||
elif profile_type == 'turnaround':
|
||
stocks = screener.screen_turnaround_opportunities(limit=limit)
|
||
elif profile_type == 'risk_averse':
|
||
stocks = screener.screen_risk_averse_stocks(limit=limit)
|
||
elif profile_type == 'innovation' or profile_type == 'innovation_driven':
|
||
stocks = screener.screen_innovation_driven_stocks(limit=limit)
|
||
elif profile_type == 'integration' or profile_type == 'industry_integration':
|
||
stocks = screener.screen_industry_integration_stocks(limit=limit)
|
||
elif profile_type == 'custom' and 'conditions' in request.args:
|
||
# 解析自定义条件
|
||
try:
|
||
import json
|
||
conditions = json.loads(request.args.get('conditions'))
|
||
stocks = screener.screen_by_custom_conditions(conditions, limit=limit)
|
||
except Exception as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"解析自定义条件失败: {str(e)}"
|
||
}), 400
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"不支持的企业画像类型: {profile_type}"
|
||
}), 400
|
||
except Exception as e:
|
||
logger.error(f"筛选股票时出错: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"筛选股票时出错: {str(e)}"
|
||
}), 500
|
||
|
||
# 格式化返回结果
|
||
formatted_stocks = []
|
||
for stock_code, stock_name in stocks:
|
||
formatted_stocks.append({
|
||
"code": stock_code,
|
||
"name": stock_name
|
||
})
|
||
|
||
# 返回结果
|
||
return jsonify({
|
||
"status": "success",
|
||
"profile_type": profile_type,
|
||
"count": len(formatted_stocks),
|
||
"stocks": formatted_stocks
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取推荐股票失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"获取推荐股票失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/analyze_and_recommend', methods=['POST'])
|
||
def analyze_and_recommend():
|
||
"""分析指定企业列表，生成投资建议，并筛选推荐投资的企业
|
||
|
||
请求体格式:
|
||
{
|
||
"stocks": [
|
||
["603690", "至纯科技"],
|
||
["688053", "思科瑞"],
|
||
["300750", "宁德时代"]
|
||
],
|
||
"limit": 10 // 可选，限制返回推荐股票的数量
|
||
}
|
||
"""
|
||
try:
|
||
# 从请求体获取股票列表
|
||
data = request.get_json()
|
||
|
||
if not data or 'stocks' not in data or not isinstance(data['stocks'], list):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供股票列表"
|
||
}), 400
|
||
|
||
# 检查股票列表格式
|
||
stocks = data['stocks']
|
||
if not all(isinstance(item, list) and len(item) == 2 for item in stocks):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "股票列表格式错误: 每个股票应该是 [代码, 名称] 格式"
|
||
}), 400
|
||
|
||
# 解析limit参数
|
||
limit = data.get('limit', 10)
|
||
if not isinstance(limit, int) or limit <= 0:
|
||
limit = 10
|
||
|
||
# 导入必要的聊天机器人模块
|
||
try:
|
||
# 首先尝试导入聊天机器人模块
|
||
try:
|
||
from src.fundamentals_llm.chat_bot import ChatBot as OnlineChatBot
|
||
logger.info("成功从 src.fundamentals_llm.chat_bot 导入 ChatBot")
|
||
except ImportError as e1:
|
||
try:
|
||
from fundamentals_llm.chat_bot import ChatBot as OnlineChatBot
|
||
logger.info("成功从 fundamentals_llm.chat_bot 导入 ChatBot")
|
||
except ImportError as e2:
|
||
logger.error(f"无法导入在线聊天机器人模块: {str(e1)}, {str(e2)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 聊天机器人模块不可用，错误详情: {str(e2)}"
|
||
}), 500
|
||
|
||
# 然后尝试导入离线聊天机器人模块
|
||
try:
|
||
from src.fundamentals_llm.chat_bot_with_offline import ChatBot as OfflineChatBot
|
||
logger.info("成功从 src.fundamentals_llm.chat_bot_with_offline 导入 ChatBot")
|
||
except ImportError as e1:
|
||
try:
|
||
from fundamentals_llm.chat_bot_with_offline import ChatBot as OfflineChatBot
|
||
logger.info("成功从 fundamentals_llm.chat_bot_with_offline 导入 ChatBot")
|
||
except ImportError as e2:
|
||
logger.warning(f"无法导入离线聊天机器人模块: {str(e1)}, {str(e2)}")
|
||
# 这里可以继续执行，因为某些功能可能不需要离线模型
|
||
|
||
# 最后导入基本面分析器
|
||
try:
|
||
from src.fundamentals_llm.fundamental_analysis import FundamentalAnalyzer
|
||
logger.info("成功从 src.fundamentals_llm.fundamental_analysis 导入 FundamentalAnalyzer")
|
||
except ImportError as e1:
|
||
try:
|
||
from fundamentals_llm.fundamental_analysis import FundamentalAnalyzer
|
||
logger.info("成功从 fundamentals_llm.fundamental_analysis 导入 FundamentalAnalyzer")
|
||
except ImportError as e2:
|
||
logger.error(f"无法导入基本面分析模块: {str(e1)}, {str(e2)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 基本面分析模块不可用，错误详情: {str(e2)}"
|
||
}), 500
|
||
except Exception as e:
|
||
logger.error(f"导入必要模块时出错: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 导入必要模块时出错，错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建基本面分析器实例
|
||
analyzer = FundamentalAnalyzer()
|
||
|
||
# 为每个股票生成投资建议
|
||
investment_advices = []
|
||
for stock_code, stock_name in stocks:
|
||
try:
|
||
# 生成投资建议
|
||
success, advice, reasoning, references = analyzer.query_analysis(
|
||
stock_code, stock_name, "investment_advice"
|
||
)
|
||
|
||
if success:
|
||
investment_advices.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"advice": advice,
|
||
"reasoning": reasoning,
|
||
"references": references,
|
||
"status": "success"
|
||
})
|
||
logger.info(f"成功生成 {stock_name}({stock_code}) 的投资建议")
|
||
else:
|
||
investment_advices.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": advice
|
||
})
|
||
logger.error(f"生成 {stock_name}({stock_code}) 的投资建议失败: {advice}")
|
||
except Exception as e:
|
||
logger.error(f"处理 {stock_name}({stock_code}) 时出错: {str(e)}")
|
||
investment_advices.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": str(e)
|
||
})
|
||
|
||
# 导入企业筛选器
|
||
try:
|
||
from src.fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError:
|
||
try:
|
||
from fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError as e:
|
||
logger.error(f"无法导入企业筛选器模块: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 企业筛选器模块不可用，错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建筛选器实例
|
||
screener = EnterpriseScreener()
|
||
|
||
# 筛选符合推荐投资条件的股票
|
||
# 获取传入的所有股票代码
|
||
input_stock_codes = set(code for code, _ in stocks)
|
||
|
||
# 获取所有符合推荐投资条件的股票
|
||
recommended_stocks = screener.screen_multi_term_investment_stocks(limit=limit)
|
||
|
||
# 筛选出传入列表中符合推荐投资条件的股票
|
||
recommended_input_stocks = []
|
||
for code, name in recommended_stocks:
|
||
if code in input_stock_codes:
|
||
recommended_input_stocks.append({
|
||
"code": code,
|
||
"name": name
|
||
})
|
||
|
||
# 返回结果
|
||
return jsonify({
|
||
"status": "success",
|
||
"total_input_stocks": len(stocks),
|
||
"investment_advices": investment_advices,
|
||
"recommended_stocks": {
|
||
"count": len(recommended_input_stocks),
|
||
"stocks": recommended_input_stocks
|
||
}
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"分析和推荐股票失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"分析和推荐股票失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/comprehensive_analysis', methods=['POST'])
|
||
def comprehensive_analysis():
|
||
"""综合分析接口 - 使用队列方式处理被锁定的股票
|
||
|
||
请求体格式:
|
||
{
|
||
"stocks": [
|
||
["603690", "至纯科技"],
|
||
["688053", "思科瑞"],
|
||
["300750", "宁德时代"]
|
||
],
|
||
"generate_pdf": true,
|
||
"limit": 10, // 可选，限制返回推荐股票的数量
|
||
"profile_filter": {
|
||
"type": "custom", // 可选值: 预定义的画像类型或 "custom"
|
||
"profile_name": "high_growth", // 当 type = 预定义画像类型时使用
|
||
"conditions": [ // 当 type = "custom" 时使用
|
||
{
|
||
"dimension": "financial_report",
|
||
"field": "financial_report_level",
|
||
"operator": ">=",
|
||
"value": 1
|
||
},
|
||
// 其他条件...
|
||
]
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 从请求体获取参数
|
||
data = request.get_json()
|
||
|
||
if not data or 'stocks' not in data or not isinstance(data['stocks'], list):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供股票列表"
|
||
}), 400
|
||
|
||
# 检查股票列表格式
|
||
stocks = data['stocks']
|
||
if not all(isinstance(item, list) and len(item) == 2 for item in stocks):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "股票列表格式错误: 每个股票应该是 [代码, 名称] 格式"
|
||
}), 400
|
||
|
||
# 解析其他参数
|
||
generate_pdf = data.get('generate_pdf', False)
|
||
profile_filter = data.get('profile_filter', None)
|
||
limit = data.get('limit', 10)
|
||
if not isinstance(limit, int) or limit <= 0:
|
||
limit = 10
|
||
|
||
# 导入必要的模块
|
||
try:
|
||
# 先导入基本面分析器
|
||
try:
|
||
from src.fundamentals_llm.fundamental_analysis import FundamentalAnalyzer
|
||
logger.info("成功从 src.fundamentals_llm.fundamental_analysis 导入 FundamentalAnalyzer")
|
||
except ImportError as e1:
|
||
try:
|
||
from fundamentals_llm.fundamental_analysis import FundamentalAnalyzer
|
||
logger.info("成功从 fundamentals_llm.fundamental_analysis 导入 FundamentalAnalyzer")
|
||
except ImportError as e2:
|
||
logger.error(f"无法导入基本面分析模块: {str(e1)}, {str(e2)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 基本面分析模块不可用，错误详情: {str(e2)}"
|
||
}), 500
|
||
|
||
# 再导入其他可能需要的模块
|
||
try:
|
||
from src.fundamentals_llm.chat_bot import ChatBot as OnlineChatBot
|
||
from src.fundamentals_llm.chat_bot_with_offline import ChatBot as OfflineChatBot
|
||
except ImportError:
|
||
try:
|
||
from fundamentals_llm.chat_bot import ChatBot as OnlineChatBot
|
||
from fundamentals_llm.chat_bot_with_offline import ChatBot as OfflineChatBot
|
||
except ImportError:
|
||
# 这些模块不是必须的，所以继续执行
|
||
logger.warning("无法导入聊天机器人模块，但这不会影响基本功能")
|
||
|
||
except Exception as e:
|
||
logger.error(f"导入必要模块时出错: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 导入必要模块时出错，错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建基本面分析器实例
|
||
analyzer = FundamentalAnalyzer()
|
||
|
||
# 准备结果容器
|
||
investment_advices = {} # 使用字典，股票代码作为键
|
||
processing_queue = list(stocks) # 初始处理队列
|
||
max_attempts = 5 # 最大重试次数
|
||
total_attempts = 0
|
||
|
||
# 导入数据库模块
|
||
from src.fundamentals_llm.fundamental_analysis_database import get_analysis_result, get_db
|
||
|
||
# 开始处理队列
|
||
while processing_queue and total_attempts < max_attempts:
|
||
total_attempts += 1
|
||
logger.info(f"开始第 {total_attempts} 轮处理，队列中有 {len(processing_queue)} 只股票")
|
||
|
||
# 暂存下一轮需要处理的股票
|
||
next_round_queue = []
|
||
|
||
# 处理当前队列中的所有股票
|
||
for stock_code, stock_name in processing_queue:
|
||
try:
|
||
# 检查是否被锁定
|
||
if analyzer.is_stock_locked(stock_code, "investment_advice"):
|
||
# 已被锁定，放到下一轮队列
|
||
next_round_queue.append([stock_code, stock_name])
|
||
# 记录状态
|
||
if stock_code not in investment_advices:
|
||
investment_advices[stock_code] = {
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "pending",
|
||
"message": f"股票 {stock_code} 正在被其他请求分析中，已加入等待队列"
|
||
}
|
||
logger.info(f"股票 {stock_name}({stock_code}) 已被锁定，放入下一轮队列")
|
||
continue
|
||
|
||
# 尝试锁定并分析
|
||
analyzer.lock_stock(stock_code, "investment_advice")
|
||
try:
|
||
# 执行分析
|
||
success, advice, reasoning, references = analyzer.query_analysis(
|
||
stock_code, stock_name, "investment_advice"
|
||
)
|
||
|
||
# 记录结果
|
||
if success:
|
||
investment_advices[stock_code] = {
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"advice": advice,
|
||
"reasoning": reasoning,
|
||
"references": references,
|
||
"status": "success"
|
||
}
|
||
logger.info(f"成功分析 {stock_name}({stock_code})")
|
||
else:
|
||
investment_advices[stock_code] = {
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": advice or "分析失败，无详细信息"
|
||
}
|
||
logger.error(f"分析 {stock_name}({stock_code}) 失败: {advice}")
|
||
finally:
|
||
# 确保释放锁
|
||
analyzer.unlock_stock(stock_code, "investment_advice")
|
||
|
||
except Exception as e:
|
||
# 处理异常
|
||
investment_advices[stock_code] = {
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": str(e)
|
||
}
|
||
logger.error(f"处理 {stock_name}({stock_code}) 时出错: {str(e)}")
|
||
# 确保释放锁
|
||
try:
|
||
analyzer.unlock_stock(stock_code, "investment_advice")
|
||
except:
|
||
pass
|
||
|
||
# 如果还有下一轮要处理的股票，等待一段时间后继续
|
||
if next_round_queue:
|
||
logger.info(f"本轮结束，还有 {len(next_round_queue)} 只股票等待下一轮处理")
|
||
# 等待30秒再处理下一轮
|
||
import time
|
||
time.sleep(30)
|
||
processing_queue = next_round_queue
|
||
else:
|
||
# 所有股票都已处理完，退出循环
|
||
logger.info("所有股票处理完毕")
|
||
processing_queue = []
|
||
|
||
# 处理仍在队列中的股票（达到最大重试次数但仍未处理的）
|
||
for stock_code, stock_name in processing_queue:
|
||
if stock_code in investment_advices and investment_advices[stock_code]["status"] == "pending":
|
||
investment_advices[stock_code].update({
|
||
"status": "timeout",
|
||
"message": f"等待超时，股票 {stock_code} 可能正在被长时间分析"
|
||
})
|
||
logger.warning(f"股票 {stock_name}({stock_code}) 分析超时")
|
||
|
||
# 将字典转换为列表
|
||
investment_advice_list = list(investment_advices.values())
|
||
|
||
# 生成PDF报告（如果需要）
|
||
pdf_results = []
|
||
if generate_pdf:
|
||
try:
|
||
# 针对已成功分析的股票生成PDF
|
||
for stock_info in investment_advice_list:
|
||
if stock_info["status"] == "success":
|
||
stock_code = stock_info["code"]
|
||
stock_name = stock_info["name"]
|
||
try:
|
||
report_path = analyzer.generate_pdf_report(stock_code, stock_name)
|
||
if report_path:
|
||
pdf_results.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"report_path": report_path,
|
||
"status": "success"
|
||
})
|
||
logger.info(f"成功生成 {stock_name}({stock_code}) 的投资报告: {report_path}")
|
||
else:
|
||
pdf_results.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": "生成报告失败"
|
||
})
|
||
logger.error(f"生成 {stock_name}({stock_code}) 的投资报告失败")
|
||
except Exception as e:
|
||
logger.error(f"生成 {stock_name}({stock_code}) 的投资报告失败: {str(e)}")
|
||
pdf_results.append({
|
||
"code": stock_code,
|
||
"name": stock_name,
|
||
"status": "error",
|
||
"error": str(e)
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"处理PDF生成请求失败: {str(e)}")
|
||
pdf_results = []
|
||
|
||
# 应用企业画像筛选
|
||
filtered_stocks = []
|
||
if profile_filter:
|
||
try:
|
||
# 导入企业筛选器
|
||
try:
|
||
from src.fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError:
|
||
try:
|
||
from fundamentals_llm.enterprise_screener import EnterpriseScreener
|
||
except ImportError as e:
|
||
logger.error(f"无法导入企业筛选器模块: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 企业筛选器模块不可用，错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建筛选器实例
|
||
screener = EnterpriseScreener()
|
||
|
||
# 根据筛选类型获取推荐股票
|
||
filter_type = profile_filter.get('type', 'custom')
|
||
|
||
# 如果是自定义条件筛选
|
||
if filter_type == 'custom':
|
||
conditions = profile_filter.get('conditions', [])
|
||
if conditions:
|
||
print(f"使用自定义条件筛选: {len(conditions)} 个条件")
|
||
all_stocks = screener.screen_by_custom_conditions(conditions, limit=limit)
|
||
else:
|
||
# 如果没有提供条件，使用默认的high_growth类型
|
||
print("未提供自定义条件，使用默认的high_growth类型")
|
||
all_stocks = screener.screen_high_growth_stocks(limit=limit)
|
||
# 如果是预定义类型
|
||
else:
|
||
# 直接使用type作为画像类型，如果用户同时提供了profile_name也兼容处理
|
||
profile_name = profile_filter.get('profile_name', filter_type)
|
||
|
||
print(f"使用预定义画像类型: {profile_name}")
|
||
|
||
if profile_name == 'high_growth':
|
||
all_stocks = screener.screen_high_growth_stocks(limit=limit)
|
||
elif profile_name == 'stable_leaders':
|
||
all_stocks = screener.screen_stable_leaders(limit=limit)
|
||
elif profile_name == 'short_term':
|
||
all_stocks = screener.screen_short_term_opportunities(limit=limit)
|
||
elif profile_name == 'value_investment':
|
||
all_stocks = screener.screen_value_investment_stocks(limit=limit)
|
||
elif profile_name == 'turnaround':
|
||
all_stocks = screener.screen_turnaround_opportunities(limit=limit)
|
||
elif profile_name == 'risk_averse':
|
||
all_stocks = screener.screen_risk_averse_stocks(limit=limit)
|
||
elif profile_name == 'innovation' or profile_name == 'innovation_driven':
|
||
all_stocks = screener.screen_innovation_driven_stocks(limit=limit)
|
||
elif profile_name == 'integration' or profile_name == 'industry_integration':
|
||
all_stocks = screener.screen_industry_integration_stocks(limit=limit)
|
||
elif profile_name == 'recommended':
|
||
all_stocks = screener.screen_multi_term_investment_stocks(limit=limit)
|
||
else:
|
||
# 如果类型无效，使用默认的high_growth类型
|
||
logger.warning(f"无效的画像类型: {profile_name}，使用默认的high_growth类型")
|
||
all_stocks = screener.screen_high_growth_stocks(limit=limit)
|
||
|
||
# 获取传入的所有股票代码
|
||
input_stock_codes = set(code for code, _ in stocks)
|
||
|
||
# 查询赛道关联信息
|
||
track_query = text("""
|
||
SELECT DISTINCT pc.stock_code, ci.belong_industry
|
||
FROM gp_product_category pc
|
||
JOIN gp_category_industry ci ON pc.category_name = ci.category_name
|
||
WHERE pc.stock_code IN :stock_codes
|
||
""")
|
||
|
||
# 获取赛道信息
|
||
track_results = {}
|
||
try:
|
||
# 获取数据库连接
|
||
db_session2 = next(get_db())
|
||
# 使用 Session 的 execute 方法执行查询
|
||
result = db_session2.execute(track_query, {"stock_codes": tuple(input_stock_codes)})
|
||
for row in result:
|
||
if row.stock_code not in track_results:
|
||
track_results[row.stock_code] = []
|
||
if row.belong_industry: # 确保 belong_industry 不为空
|
||
track_results[row.stock_code].append(row.belong_industry)
|
||
except Exception as e:
|
||
logger.error(f"查询赛道信息失败: {str(e)}")
|
||
track_results = {}
|
||
finally:
|
||
if 'db_session2' in locals() and db_session2 is not None: # 确保 db_session 已定义
|
||
db_session2.close() # <--- 关闭会话
|
||
|
||
# 获取企业市值信息
|
||
market_value_results = {}
|
||
try:
|
||
from src.valuation_analysis.stock_price_collector import StockPriceCollector
|
||
price_collector = StockPriceCollector()
|
||
|
||
for stock_code in input_stock_codes:
|
||
price_data = price_collector.get_stock_price_data(stock_code)
|
||
if price_data and 'total_market_value' in price_data:
|
||
market_value_results[stock_code] = price_data['total_market_value']
|
||
else:
|
||
market_value_results[stock_code] = None
|
||
except Exception as e:
|
||
logger.error(f"获取企业市值信息失败: {str(e)}")
|
||
market_value_results = {}
|
||
|
||
db_session = next(get_db())
|
||
# 筛选出传入列表中符合条件的股票
|
||
for code, name in all_stocks:
|
||
if code in input_stock_codes:
|
||
# 获取各个维度的分析结果
|
||
investment_advice_result = get_analysis_result(db_session, code, "investment_advice")
|
||
industry_competition_result = get_analysis_result(db_session, code, "industry_competition")
|
||
financial_report_result = get_analysis_result(db_session, code, "financial_report")
|
||
valuation_level_result = get_analysis_result(db_session, code, "valuation_level")
|
||
|
||
# 从ai_response和extra_info中提取所需的值
|
||
investment_advice = investment_advice_result.ai_response if investment_advice_result else None
|
||
industry_space = industry_competition_result.extra_info.get("industry_space") if industry_competition_result else 0
|
||
financial_report_level = financial_report_result.extra_info.get("financial_report_level") if financial_report_result else 0
|
||
pe_industry = valuation_level_result.extra_info.get("pe_industry") if valuation_level_result else 0
|
||
|
||
filtered_stocks.append({
|
||
"code": code,
|
||
"name": name,
|
||
"investment_advice": investment_advice, # 投资建议（从ai_response获取）
|
||
"industry_space": industry_space, # 行业发展空间（2:高速增长, 1:稳定经营, 0:不确定性大, -1:不利经营）
|
||
"financial_report_level": financial_report_level, # 经营质量（2:优秀, 1:较好, 0:一般, -1:存在隐患，-2：较大隐患）
|
||
"pe_industry": pe_industry, # 个股在行业的PE水平（-1:高于行业, 0:接近行业, 1:低于行业）
|
||
"tracks": track_results.get(code, []), # 添加赛道信息
|
||
"market_value": market_value_results.get(code) # 添加企业市值信息
|
||
})
|
||
|
||
logger.info(f"筛选出 {len(filtered_stocks)} 个符合条件的股票")
|
||
|
||
except Exception as e:
|
||
logger.error(f"应用企业画像筛选失败: {str(e)}")
|
||
filtered_stocks = []
|
||
finally:
|
||
if 'db_session' in locals() and db_session is not None: # 确保 db_session 已定义
|
||
db_session.close() # <--- 关闭会话
|
||
|
||
# 统计各种状态的股票数量
|
||
success_count = sum(1 for item in investment_advice_list if item["status"] == "success")
|
||
pending_count = sum(1 for item in investment_advice_list if item["status"] == "pending")
|
||
timeout_count = sum(1 for item in investment_advice_list if item["status"] == "timeout")
|
||
error_count = sum(1 for item in investment_advice_list if item["status"] == "error")
|
||
|
||
# 返回结果
|
||
response = {
|
||
"status": "success" if success_count > 0 else "partial_success" if success_count + pending_count > 0 else "failed",
|
||
"total_input_stocks": len(stocks),
|
||
"stats": {
|
||
"success": success_count,
|
||
"pending": pending_count,
|
||
"timeout": timeout_count,
|
||
"error": error_count
|
||
},
|
||
"rounds_attempted": total_attempts,
|
||
"investment_advices": investment_advice_list
|
||
}
|
||
|
||
if profile_filter:
|
||
response["filtered_stocks"] = {
|
||
"count": len(filtered_stocks),
|
||
"stocks": filtered_stocks
|
||
}
|
||
|
||
if generate_pdf:
|
||
response["pdf_results"] = {
|
||
"count": len(pdf_results),
|
||
"reports": pdf_results
|
||
}
|
||
|
||
return jsonify(response)
|
||
|
||
except Exception as e:
|
||
logger.error(f"综合分析失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"综合分析失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/valuation_analysis', methods=['GET'])
|
||
def valuation_analysis():
|
||
"""
|
||
估值分析接口 - 获取股票的PE/PB估值分析数据
|
||
|
||
参数:
|
||
- stock_code: 股票代码（支持两种格式：SH601021或601021.SH）
|
||
- stock_name: 股票名称（和stock_code二选一）
|
||
- start_date: 开始日期（可选，默认为2018-01-01）
|
||
- industry_name: 行业名称（可选）
|
||
- concept_name: 概念板块名称（可选）
|
||
- metric: 估值指标，可选值为'pe'或'pb'，默认为'pe'
|
||
|
||
返回:
|
||
用于构建ECharts图表的数据对象
|
||
"""
|
||
try:
|
||
# 解析参数
|
||
stock_code = request.args.get('stock_code')
|
||
stock_name = request.args.get('stock_name')
|
||
start_date = request.args.get('start_date', '2018-01-01')
|
||
industry_name = request.args.get('industry_name')
|
||
concept_name = request.args.get('concept_name')
|
||
metric = request.args.get('metric', 'pe')
|
||
|
||
# 检查参数
|
||
if not stock_code and not stock_name:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供stock_code或stock_name参数"
|
||
}), 400
|
||
|
||
if metric not in ['pe', 'pb']:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: metric参数必须为'pe'或'pb'"
|
||
}), 400
|
||
|
||
# 处理股票代码格式
|
||
if stock_code:
|
||
if '.' in stock_code: # 处理601021.SH格式
|
||
code_parts = stock_code.split('.')
|
||
if len(code_parts) == 2:
|
||
stock_code = f"{code_parts[1]}{code_parts[0]}"
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "股票代码格式错误: 应为601021.SH格式"
|
||
}), 400
|
||
|
||
# 验证日期格式
|
||
try:
|
||
datetime.strptime(start_date, '%Y-%m-%d')
|
||
except ValueError:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"日期格式错误: {start_date}，应为YYYY-MM-DD格式"
|
||
}), 400
|
||
|
||
# 获取股票历史数据
|
||
stock_data = valuation_analyzer.get_historical_data(stock_code, start_date)
|
||
if stock_data.empty:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"未找到股票 {stock_code} 的历史数据"
|
||
}), 404
|
||
|
||
# 使用过滤后的数据
|
||
metric_filtered = f'{metric}_filtered' if f'{metric}_filtered' in stock_data.columns else metric
|
||
|
||
# 计算分位数
|
||
percentiles = valuation_analyzer.calculate_percentiles(stock_data, metric)
|
||
if not percentiles:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"无法计算股票 {stock_code} 的 {metric} 分位数"
|
||
}), 500
|
||
|
||
# 获取行业平均数据
|
||
industry_data = None
|
||
if industry_name:
|
||
industry_data = valuation_analyzer.get_industry_avg_data(industry_name, start_date, metric)
|
||
|
||
# 获取概念板块平均数据
|
||
concept_data = None
|
||
if concept_name:
|
||
concept_data = valuation_analyzer.get_concept_avg_data(concept_name, start_date, metric)
|
||
|
||
# 获取股票名称
|
||
stock_name = valuation_analyzer.get_stock_name(stock_code) if not stock_name else stock_name
|
||
|
||
# 构建ECharts数据结构
|
||
dates = stock_data['timestamp'].dt.strftime('%Y-%m-%d').tolist()
|
||
|
||
# 准备行业和概念数据，使其与股票数据的日期对齐
|
||
aligned_industry_data = []
|
||
aligned_concept_data = []
|
||
|
||
# 日期映射，用于快速查找
|
||
if industry_data is not None and not industry_data.empty:
|
||
industry_date_map = dict(zip(industry_data['timestamp'].dt.strftime('%Y-%m-%d').tolist(),
|
||
industry_data[f'avg_{metric}'].tolist()))
|
||
|
||
# 根据股票日期创建对齐的行业数据
|
||
for date in dates:
|
||
aligned_industry_data.append(industry_date_map.get(date, None))
|
||
|
||
if concept_data is not None and not concept_data.empty:
|
||
concept_date_map = dict(zip(concept_data['timestamp'].dt.strftime('%Y-%m-%d').tolist(),
|
||
concept_data[f'avg_{metric}'].tolist()))
|
||
|
||
# 根据股票日期创建对齐的概念数据
|
||
for date in dates:
|
||
aligned_concept_data.append(concept_date_map.get(date, None))
|
||
|
||
# 构建结果
|
||
result = {
|
||
"status": "success",
|
||
"data": {
|
||
"title": {
|
||
"text": f"{stock_code} {stock_name} 历史{metric.upper()}分位数分析",
|
||
"subtext": f"当前{metric.upper()}百分位: {percentiles['percentile']:.2f}%"
|
||
},
|
||
"tooltip": {
|
||
"trigger": "axis",
|
||
"axisPointer": {
|
||
"type": "cross"
|
||
}
|
||
},
|
||
"legend": {
|
||
"data": [f"{stock_name} {metric.upper()}"]
|
||
},
|
||
"grid": {
|
||
"left": "3%",
|
||
"right": "4%",
|
||
"bottom": "3%",
|
||
"containLabel": True
|
||
},
|
||
"xAxis": {
|
||
"type": "category",
|
||
"boundaryGap": False,
|
||
"data": dates
|
||
},
|
||
"yAxis": {
|
||
"type": "value",
|
||
"name": f"{metric.upper()}值"
|
||
},
|
||
"series": [
|
||
{
|
||
"name": f"{stock_name} {metric.upper()}",
|
||
"type": "line",
|
||
"data": stock_data[metric_filtered].tolist(),
|
||
"markLine": {
|
||
"data": [
|
||
{"name": "最小值", "yAxis": percentiles['min']},
|
||
{"name": "最大值", "yAxis": percentiles['max']},
|
||
{"name": "均值", "yAxis": percentiles['mean']},
|
||
{"name": "第一四分位数", "yAxis": percentiles['q1']},
|
||
{"name": "第三四分位数", "yAxis": percentiles['q3']},
|
||
{"name": "当前值", "yAxis": percentiles['current']}
|
||
]
|
||
}
|
||
}
|
||
],
|
||
"percentiles": {
|
||
"min": percentiles['min'],
|
||
"max": percentiles['max'],
|
||
"current": percentiles['current'],
|
||
"mean": percentiles['mean'],
|
||
"median": percentiles['median'],
|
||
"q1": percentiles['q1'],
|
||
"q3": percentiles['q3'],
|
||
"percentile": percentiles['percentile']
|
||
}
|
||
}
|
||
}
|
||
|
||
# 添加行业平均数据
|
||
if industry_data is not None and not industry_data.empty:
|
||
# 添加到legend
|
||
result["data"]["legend"]["data"].append(f"{industry_name}行业平均{metric.upper()}")
|
||
|
||
# 添加到series
|
||
result["data"]["series"].append({
|
||
"name": f"{industry_name}行业平均{metric.upper()}",
|
||
"type": "line",
|
||
"data": aligned_industry_data,
|
||
"lineStyle": {
|
||
"color": "#1e90ff", # 深蓝色
|
||
"width": 2
|
||
},
|
||
"itemStyle": {
|
||
"color": "#1e90ff",
|
||
"opacity": 0.9
|
||
},
|
||
"connectNulls": True # 连接空值点
|
||
})
|
||
|
||
# 添加行业统计信息
|
||
result["data"]["industry_stats"] = {
|
||
"name": industry_name,
|
||
"min_count": int(industry_data['stock_count'].min()),
|
||
"max_count": int(industry_data['stock_count'].max()),
|
||
"avg_count": float(industry_data['stock_count'].mean()),
|
||
"avg_value": float(industry_data[f'avg_{metric}'].mean())
|
||
}
|
||
|
||
# 添加概念板块平均数据
|
||
if concept_data is not None and not concept_data.empty:
|
||
# 添加到legend
|
||
result["data"]["legend"]["data"].append(f"{concept_name}概念平均{metric.upper()}")
|
||
|
||
# 添加到series
|
||
result["data"]["series"].append({
|
||
"name": f"{concept_name}概念平均{metric.upper()}",
|
||
"type": "line",
|
||
"data": aligned_concept_data,
|
||
"lineStyle": {
|
||
"color": "#ff7f50", # 珊瑚色
|
||
"width": 2
|
||
},
|
||
"itemStyle": {
|
||
"color": "#ff7f50",
|
||
"opacity": 0.9
|
||
},
|
||
"connectNulls": True # 连接空值点
|
||
})
|
||
|
||
# 添加概念统计信息
|
||
result["data"]["concept_stats"] = {
|
||
"name": concept_name,
|
||
"min_count": int(concept_data['stock_count'].min()),
|
||
"max_count": int(concept_data['stock_count'].max()),
|
||
"avg_count": float(concept_data['stock_count'].mean()),
|
||
"avg_value": float(concept_data[f'avg_{metric}'].mean())
|
||
}
|
||
|
||
return jsonify(result)
|
||
|
||
except Exception as e:
|
||
logger.error(f"估值分析失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"估值分析失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/industry/list', methods=['GET'])
|
||
def get_industry_list():
|
||
"""
|
||
获取行业列表
|
||
|
||
返回:
|
||
{
|
||
"status": "success",
|
||
"data": [
|
||
{"code": "100001", "name": "银行"},
|
||
{"code": "100002", "name": "保险"},
|
||
...
|
||
]
|
||
}
|
||
"""
|
||
try:
|
||
industries = industry_analyzer.get_industry_list()
|
||
|
||
if not industries:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "未找到行业数据"
|
||
}), 404
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"count": len(industries),
|
||
"data": industries
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取行业列表失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"获取行业列表失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/concept/list', methods=['GET'])
|
||
def get_concept_list():
|
||
"""
|
||
获取概念板块列表
|
||
|
||
返回:
|
||
{
|
||
"status": "success",
|
||
"data": [
|
||
{"code": "200001", "name": "人工智能"},
|
||
{"code": "200002", "name": "大数据"},
|
||
...
|
||
]
|
||
}
|
||
"""
|
||
try:
|
||
# 使用IndustryAnalyzer获取概念板块列表
|
||
concepts = industry_analyzer.get_concept_list()
|
||
|
||
if not concepts:
|
||
logger.warning("未找到概念板块数据")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "未找到概念板块数据"
|
||
}), 404
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"count": len(concepts),
|
||
"data": concepts
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取概念板块列表失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"获取概念板块列表失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/industry/analysis', methods=['GET'])
|
||
def industry_analysis():
|
||
"""
|
||
行业/概念板块分析接口 - 获取行业或概念板块的PE/PB/PS估值分析数据和拥挤度指标
|
||
|
||
参数:
|
||
- industry_name: 行业名称（与concept_name二选一）
|
||
- concept_name: 概念板块名称（与industry_name二选一）
|
||
- metric: 估值指标，可选值为'pe'、'pb'或'ps'，默认为'pe'
|
||
- start_date: 开始日期（可选，默认为3年前）
|
||
|
||
返回:
|
||
用于构建ECharts图表的行业/概念板块估值数据对象，包含估值指标和拥挤度
|
||
|
||
注意：
|
||
- 行业/概念板块PE/PB/PS计算中已剔除负值和极端值(如PE>1000)
|
||
- 所有百分位数据都是基于行业/概念板块平均值计算的
|
||
- 拥挤度数据固定使用最近3年的数据，不受start_date参数影响
|
||
"""
|
||
try:
|
||
# 解析参数
|
||
industry_name = request.args.get('industry_name')
|
||
concept_name = request.args.get('concept_name')
|
||
metric = request.args.get('metric', 'pe')
|
||
start_date = request.args.get('start_date')
|
||
|
||
# 检查参数
|
||
if not industry_name and not concept_name:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: 需要提供industry_name或concept_name参数"
|
||
}), 400
|
||
|
||
if industry_name and concept_name:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: industry_name和concept_name不能同时提供"
|
||
}), 400
|
||
|
||
if metric not in ['pe', 'pb', 'ps']:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求格式错误: metric参数必须为'pe'、'pb'或'ps'"
|
||
}), 400
|
||
|
||
# 获取分析数据
|
||
if industry_name:
|
||
result = industry_analyzer.get_industry_analysis(industry_name, metric, start_date)
|
||
title_name = industry_name
|
||
else:
|
||
result = industry_analyzer.get_concept_analysis(concept_name, metric, start_date)
|
||
title_name = concept_name
|
||
|
||
if not result.get('success', False):
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get('message', '未知错误')
|
||
}), 404
|
||
|
||
# 构建ECharts数据结构
|
||
metric_name = metric.upper()
|
||
|
||
# 估值指标数据
|
||
valuation_data = result['valuation']
|
||
percentiles = valuation_data['percentiles']
|
||
|
||
# 准备图例数据
|
||
legend_data = [
|
||
f"{title_name}平均{metric_name}",
|
||
f"平均{metric_name}历史最小值",
|
||
f"平均{metric_name}历史最大值",
|
||
f"平均{metric_name}历史Q1",
|
||
f"平均{metric_name}历史Q3"
|
||
]
|
||
|
||
# 构建结果
|
||
response = {
|
||
"status": "success",
|
||
"data": {
|
||
"title": {
|
||
"text": f"{title_name}历史{metric_name}分析",
|
||
"subtext": f"当前{metric_name}百分位: {percentiles['percentile']:.2f}%（剔除负值及极端值）"
|
||
},
|
||
"tooltip": {
|
||
"trigger": "axis",
|
||
"axisPointer": {
|
||
"type": "cross"
|
||
}
|
||
},
|
||
"legend": {
|
||
"data": legend_data
|
||
},
|
||
"grid": [
|
||
{
|
||
"left": "3%",
|
||
"right": "4%",
|
||
"top": "15%",
|
||
"height": "50%",
|
||
"containLabel": True
|
||
}
|
||
],
|
||
"xAxis": [
|
||
{
|
||
"type": "category",
|
||
"boundaryGap": False,
|
||
"data": valuation_data['dates'],
|
||
"axisLabel": {
|
||
"rotate": 45
|
||
},
|
||
"gridIndex": 0
|
||
}
|
||
],
|
||
"yAxis": [
|
||
{
|
||
"type": "value",
|
||
"name": f"{metric_name}值",
|
||
"gridIndex": 0
|
||
}
|
||
],
|
||
"dataZoom": [
|
||
{
|
||
"type": "inside",
|
||
"start": 0,
|
||
"end": 100,
|
||
"xAxisIndex": [0]
|
||
},
|
||
{
|
||
"start": 0,
|
||
"end": 100,
|
||
"xAxisIndex": [0]
|
||
}
|
||
],
|
||
"series": [
|
||
{
|
||
"name": f"{title_name}平均{metric_name}",
|
||
"type": "line",
|
||
"data": valuation_data['avg_values'],
|
||
"markLine": {
|
||
"symbol": "none",
|
||
"data": [
|
||
{"name": "历史最小值", "yAxis": percentiles['min'], "lineStyle": {"color": "#28a745", "type": "dashed"}},
|
||
{"name": "历史最大值", "yAxis": percentiles['max'], "lineStyle": {"color": "#dc3545", "type": "dashed"}},
|
||
{"name": "历史均值", "yAxis": percentiles['mean'], "lineStyle": {"color": "#9400d3", "type": "dashed"}},
|
||
{"name": "历史Q1", "yAxis": percentiles['q1'], "lineStyle": {"color": "#28a745", "type": "dashed"}},
|
||
{"name": "历史Q3", "yAxis": percentiles['q3'], "lineStyle": {"color": "#dc3545", "type": "dashed"}}
|
||
]
|
||
}
|
||
},
|
||
{
|
||
"name": f"平均{metric_name}历史最小值",
|
||
"type": "line",
|
||
"data": valuation_data['min_values'],
|
||
"lineStyle": {"width": 1, "opacity": 0.4, "color": "#28a745"},
|
||
"areaStyle": {"opacity": 0.1, "color": "#28a745"}
|
||
},
|
||
{
|
||
"name": f"平均{metric_name}历史最大值",
|
||
"type": "line",
|
||
"data": valuation_data['max_values'],
|
||
"lineStyle": {"width": 1, "opacity": 0.4, "color": "#dc3545"},
|
||
"areaStyle": {"opacity": 0.1, "color": "#dc3545"}
|
||
},
|
||
{
|
||
"name": f"平均{metric_name}历史Q1",
|
||
"type": "line",
|
||
"data": valuation_data['q1_values'],
|
||
"lineStyle": {"width": 1, "opacity": 0.6, "color": "#28a745"}
|
||
},
|
||
{
|
||
"name": f"平均{metric_name}历史Q3",
|
||
"type": "line",
|
||
"data": valuation_data['q3_values'],
|
||
"lineStyle": {"width": 1, "opacity": 0.6, "color": "#dc3545"}
|
||
}
|
||
],
|
||
"percentiles": {
|
||
"min": percentiles['min'],
|
||
"max": percentiles['max'],
|
||
"current": percentiles['current'],
|
||
"mean": percentiles['mean'],
|
||
"median": percentiles['median'],
|
||
"q1": percentiles['q1'],
|
||
"q3": percentiles['q3'],
|
||
"percentile": percentiles['percentile'],
|
||
"stock_count": percentiles['stock_count'],
|
||
"date": percentiles.get('date', valuation_data['dates'][-1])
|
||
},
|
||
"toolbox": {
|
||
"feature": {
|
||
"saveAsImage": {}
|
||
}
|
||
},
|
||
"valuation": {
|
||
"dates": valuation_data['dates'],
|
||
"avg_values": valuation_data['avg_values']
|
||
}
|
||
}
|
||
}
|
||
|
||
# 添加拥挤度指标（如果有）
|
||
if "crowding" in result:
|
||
crowding_data = result["crowding"]
|
||
current_crowding = crowding_data["current"]
|
||
|
||
# 添加拥挤度数据作为单独部分
|
||
response["data"]["crowding"] = {
|
||
"current_ratio": current_crowding["ratio"],
|
||
"current_percentile": current_crowding["percentile"],
|
||
"level": current_crowding["level"],
|
||
"dates": crowding_data["dates"],
|
||
"percentiles": crowding_data["percentiles"],
|
||
"ratios": crowding_data["ratios"]
|
||
}
|
||
|
||
# 如果有行业成交比例的历史统计数据，也添加到响应中
|
||
if "ratio_stats" in current_crowding:
|
||
response["data"]["crowding"]["ratio_stats"] = current_crowding["ratio_stats"]
|
||
|
||
return jsonify(response)
|
||
|
||
except Exception as e:
|
||
logger.error(f"行业/概念板块分析请求失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"分析失败: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/industry')
|
||
def industry_page():
|
||
"""渲染行业分析页面"""
|
||
return render_template('industry.html')
|
||
|
||
@app.route('/hsgt')
|
||
def hsgt_page():
|
||
"""渲染沪深港通监控页面"""
|
||
return render_template('hsgt_monitor.html')
|
||
|
||
@app.route('/api/hsgt/northbound', methods=['GET'])
|
||
def get_northbound_data():
|
||
"""获取北向资金流向数据接口
|
||
|
||
参数:
|
||
- start_time: 可选 ，开始时间戳（秒）
|
||
- end_time: 可选，结束时间戳（秒）
|
||
|
||
返回北向资金流向数据
|
||
"""
|
||
try:
|
||
# 获取请求参数
|
||
start_time = request.args.get('start_time')
|
||
end_time = request.args.get('end_time')
|
||
|
||
# 转换为整数
|
||
if start_time:
|
||
start_time = int(start_time)
|
||
if end_time:
|
||
end_time = int(end_time)
|
||
|
||
# 调用数据获取方法
|
||
result = hsgt_monitor.fetch_northbound_data(start_time, end_time)
|
||
|
||
if result.get('success'):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get('message', '获取北向资金数据失败')
|
||
}), 500
|
||
|
||
except ValueError as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"参数格式错误: {str(e)}"
|
||
}), 400
|
||
except Exception as e:
|
||
logger.error(f"获取北向资金数据异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/hsgt/southbound', methods=['GET'])
|
||
def get_southbound_data():
|
||
"""获取南向资金流向数据接口
|
||
|
||
参数:
|
||
- start_time: 可选，开始时间戳（秒）
|
||
- end_time: 可选，结束时间戳（秒）
|
||
|
||
返回南向资金流向数据
|
||
"""
|
||
try:
|
||
# 获取请求参数
|
||
start_time = request.args.get('start_time')
|
||
end_time = request.args.get('end_time')
|
||
|
||
# 转换为整数
|
||
if start_time:
|
||
start_time = int(start_time)
|
||
if end_time:
|
||
end_time = int(end_time)
|
||
|
||
# 调用数据获取方法
|
||
result = hsgt_monitor.fetch_southbound_data(start_time, end_time)
|
||
|
||
if result.get('success'):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get('message', '获取南向资金数据失败')
|
||
}), 500
|
||
|
||
except ValueError as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"参数格式错误: {str(e)}"
|
||
}), 400
|
||
except Exception as e:
|
||
logger.error(f"获取南向资金数据异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/rzrq/chart_data', methods=['GET'])
|
||
def get_rzrq_chart_data():
|
||
"""获取融资融券数据用于图表展示
|
||
|
||
参数:
|
||
- days: 可选，获取最近多少天的数据（默认30天）
|
||
|
||
返回内容：
|
||
{
|
||
"status": "success",
|
||
"data": {
|
||
"success": true,
|
||
"dates": ["2023-01-01", "2023-01-02", ...],
|
||
"series": [
|
||
{
|
||
"name": "融资融券余额合计",
|
||
"data": [1234.56, 1235.67, ...],
|
||
"unit": "亿元"
|
||
},
|
||
// 其他系列数据...
|
||
],
|
||
"last_update": "2023-01-15 12:34:56"
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 获取天数参数
|
||
days = request.args.get('days', type=int, default=30)
|
||
|
||
# 限制天数范围
|
||
if days <= 0:
|
||
days = 30
|
||
elif days > 365:
|
||
days = 365
|
||
|
||
# 调用数据获取方法
|
||
result = em_rzrq_collector.get_chart_data(limit_days=days)
|
||
|
||
if result.get('success'):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get('message', '获取融资融券数据失败')
|
||
}), 500
|
||
|
||
except ValueError as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"参数格式错误: {str(e)}"
|
||
}), 400
|
||
except Exception as e:
|
||
logger.error(f"获取融资融券图表数据异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/stock/tracks', methods=['GET'])
|
||
def get_stock_tracks():
|
||
"""根据股票代码获取相关赛道信息
|
||
|
||
参数:
|
||
- stock_code: 必须，股票代码
|
||
|
||
返回赛道列表
|
||
"""
|
||
try:
|
||
# 获取股票代码参数
|
||
stock_code = request.args.get('stock_code')
|
||
|
||
# 验证参数
|
||
if not stock_code:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: stock_code"
|
||
}), 400
|
||
|
||
# 查询赛道关联信息
|
||
track_query = text("""
|
||
SELECT DISTINCT pc.stock_code, ci.belong_industry
|
||
FROM gp_product_category pc
|
||
JOIN gp_category_industry ci ON pc.category_name = ci.category_name
|
||
WHERE pc.stock_code = :stock_code
|
||
""")
|
||
|
||
# 获取赛道信息
|
||
tracks = []
|
||
try:
|
||
# 获取数据库连接
|
||
db_session = next(get_db())
|
||
# 执行查询
|
||
result = db_session.execute(track_query, {"stock_code": stock_code})
|
||
for row in result:
|
||
if row.belong_industry: # 确保不为空
|
||
tracks.append(row.belong_industry)
|
||
except Exception as e:
|
||
logger.error(f"查询赛道信息失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"查询赛道信息失败: {str(e)}"
|
||
}), 500
|
||
finally:
|
||
if 'db_session' in locals() and db_session is not None:
|
||
db_session.close() # 关闭会话
|
||
|
||
# 返回结果
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": {
|
||
"stock_code": stock_code,
|
||
"tracks": tracks
|
||
}
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取股票赛道信息异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/stock/price_range', methods=['GET'])
|
||
def get_stock_price_range():
|
||
"""根据股票估值分位计算理论价格区间
|
||
|
||
根据当前PE和PB的四分位数据，反向计算出对应的理论股价区间
|
||
|
||
参数:
|
||
- stock_code: 必须，股票代码
|
||
- start_date: 可选，开始日期，默认为一年前
|
||
|
||
返回内容:
|
||
{
|
||
"status": "success",
|
||
"data": {
|
||
"stock_code": "600000",
|
||
"stock_name": "浦发银行",
|
||
"current_price": 10.5,
|
||
"current_date": "2023-12-01",
|
||
"pe": {
|
||
"current": 5.2,
|
||
"q1": 4.8,
|
||
"q3": 6.5,
|
||
"q1_price": 9.7, // 对应PE为Q1时的理论股价
|
||
"q3_price": 13.1 // 对应PE为Q3时的理论股价
|
||
},
|
||
"pb": {
|
||
"current": 0.65,
|
||
"q1": 0.6,
|
||
"q3": 0.8,
|
||
"q1_price": 9.7, // 对应PB为Q1时的理论股价
|
||
"q3_price": 12.9 // 对应PB为Q3时的理论股价
|
||
}
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 获取股票代码参数
|
||
stock_code = request.args.get('stock_code')
|
||
|
||
# 验证参数
|
||
if not stock_code:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: stock_code"
|
||
}), 400
|
||
|
||
# 兼容处理股票代码 (SZ002009, 002009.SZ, 002009)
|
||
stock_code = stock_code.strip().upper()
|
||
if '.' in stock_code: # 处理 002009.SZ 格式
|
||
parts = stock_code.split('.')
|
||
if len(parts) == 2:
|
||
stock_code = f"{parts[1]}{parts[0]}"
|
||
elif len(stock_code) == 5:
|
||
# 港股的情况
|
||
stock_code = stock_code
|
||
elif stock_code.isdigit(): # 处理 002009 格式
|
||
if stock_code.startswith(('60', '68')):
|
||
stock_code = f"SH{stock_code}"
|
||
elif stock_code.startswith(('00', '30', '20')):
|
||
stock_code = f"SZ{stock_code}"
|
||
elif stock_code.startswith(('8', '43', '87')):
|
||
stock_code = f"BJ{stock_code}"
|
||
|
||
# 计算一年前的日期作为默认起始日期
|
||
default_start_date = (datetime.now() - timedelta(days=365)).strftime('%Y-%m-%d')
|
||
start_date = request.args.get('start_date', default_start_date)
|
||
|
||
# 通过复用现有API的逻辑获取PE和PB数据
|
||
# 首先获取PE数据
|
||
pe_data = valuation_analyzer.get_historical_data(stock_code, start_date)
|
||
if pe_data.empty:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"未找到股票 {stock_code} 的历史数据"
|
||
}), 404
|
||
|
||
# 计算PE分位数
|
||
pe_percentiles = valuation_analyzer.calculate_percentiles(pe_data, 'pe')
|
||
if not pe_percentiles:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"无法计算股票 {stock_code} 的PE分位数"
|
||
}), 500
|
||
|
||
# 计算PB分位数
|
||
pb_percentiles = valuation_analyzer.calculate_percentiles(pe_data, 'pb')
|
||
if not pb_percentiles:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"无法计算股票 {stock_code} 的PB分位数"
|
||
}), 500
|
||
|
||
# 获取当前股价
|
||
current_price = None
|
||
current_date = None
|
||
if not pe_data.empty:
|
||
current_price = pe_data.iloc[-1].get('close')
|
||
current_date = pe_data.iloc[-1].get('timestamp').strftime('%Y-%m-%d') if 'timestamp' in pe_data.columns else None
|
||
|
||
if current_price is None:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"无法获取股票 {stock_code} 的当前股价"
|
||
}), 500
|
||
|
||
# 获取当前PE和PB
|
||
current_pe = pe_percentiles.get('current')
|
||
current_pb = pb_percentiles.get('current')
|
||
|
||
# 获取PE的Q1和Q3
|
||
pe_q1 = pe_percentiles.get('q1')
|
||
pe_q3 = pe_percentiles.get('q3')
|
||
|
||
# 获取PB的Q1和Q3
|
||
pb_q1 = pb_percentiles.get('q1')
|
||
pb_q3 = pb_percentiles.get('q3')
|
||
|
||
# 反向计算估值分位对应的股价
|
||
# 如果当前PE为X，股价为Y，则PE为Z时的理论股价 = Y * (X / Z)
|
||
|
||
# 计算PE对应的理论股价
|
||
pe_q1_price = None
|
||
pe_q3_price = None
|
||
if current_pe and current_pe > 0 and pe_q1 and pe_q3:
|
||
pe_q1_price = current_price * (pe_q1 / current_pe)
|
||
pe_q3_price = current_price * (pe_q3 / current_pe)
|
||
|
||
# 计算PB对应的理论股价
|
||
pb_q1_price = None
|
||
pb_q3_price = None
|
||
if current_pb and current_pb > 0 and pb_q1 and pb_q3:
|
||
pb_q1_price = current_price * (pb_q1 / current_pb)
|
||
pb_q3_price = current_price * (pb_q3 / current_pb)
|
||
|
||
# 获取股票名称
|
||
stock_name = valuation_analyzer.get_stock_name(stock_code)
|
||
|
||
# 构建响应
|
||
response = {
|
||
"status": "success",
|
||
"data": {
|
||
"stock_code": stock_code,
|
||
"stock_name": stock_name,
|
||
"current_price": current_price,
|
||
"current_date": current_date,
|
||
"pe": {
|
||
"current": current_pe,
|
||
"q1": pe_q1,
|
||
"q3": pe_q3,
|
||
"q1_price": round(pe_q1_price, 2) if pe_q1_price is not None else None,
|
||
"q3_price": round(pe_q3_price, 2) if pe_q3_price is not None else None
|
||
},
|
||
"pb": {
|
||
"current": current_pb,
|
||
"q1": pb_q1,
|
||
"q3": pb_q3,
|
||
"q1_price": round(pb_q1_price, 2) if pb_q1_price is not None else None,
|
||
"q3_price": round(pb_q3_price, 2) if pb_q3_price is not None else None
|
||
}
|
||
}
|
||
}
|
||
|
||
return jsonify(response)
|
||
|
||
except Exception as e:
|
||
logger.error(f"计算股票价格区间异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/fear_greed/data', methods=['GET'])
|
||
def get_fear_greed_data():
|
||
"""获取恐贪指数数据
|
||
|
||
参数:
|
||
- start_date: 可选，开始日期（YYYY-MM-DD格式）
|
||
- end_date: 可选，结束日期（YYYY-MM-DD格式）
|
||
- limit: 可选，限制返回的记录数量，默认为730（约两年的交易日数量）
|
||
|
||
返回内容：
|
||
{
|
||
"status": "success",
|
||
"data": {
|
||
"dates": ["2023-01-01", "2023-01-02", ...],
|
||
"values": [45.67, 50.12, ...],
|
||
"latest": {
|
||
"id": 123,
|
||
"index_value": 50.12,
|
||
"trading_date": "2023-01-02",
|
||
"update_time": "2023-01-02 15:30:00"
|
||
},
|
||
"latest_status": "中性",
|
||
"update_time": "2023-01-02 16:00:00"
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 获取参数
|
||
start_date = request.args.get('start_date')
|
||
end_date = request.args.get('end_date')
|
||
limit = request.args.get('limit', type=int, default=730)
|
||
|
||
# 调用数据获取方法
|
||
result = fear_greed_manager.get_index_data(start_date, end_date, limit)
|
||
|
||
if result.get('success'):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get('message', '获取恐贪指数数据失败')
|
||
}), 500
|
||
|
||
except ValueError as e:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"参数格式错误: {str(e)}"
|
||
}), 400
|
||
except Exception as e:
|
||
logger.error(f"获取恐贪指数数据异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/api/fear_greed/add', methods=['POST'])
|
||
def add_fear_greed_data():
|
||
"""添加恐贪指数数据
|
||
|
||
请求体格式:
|
||
{
|
||
"index_value": 45.67, // 恐贪指数值，0-100之间的数值
|
||
"trading_date": "2023-01-01" // 交易日期，YYYY-MM-DD格式
|
||
}
|
||
|
||
返回内容:
|
||
{
|
||
"status": "success",
|
||
"message": "数据添加成功"
|
||
}
|
||
"""
|
||
try:
|
||
# 从请求体获取参数
|
||
data = request.get_json()
|
||
|
||
if not data:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "请求体为空"
|
||
}), 400
|
||
|
||
index_value = data.get('index_value')
|
||
trading_date = data.get('trading_date')
|
||
|
||
# 验证参数
|
||
if index_value is None:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: index_value"
|
||
}), 400
|
||
|
||
if trading_date is None:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: trading_date"
|
||
}), 400
|
||
|
||
# 尝试转换为浮点数
|
||
try:
|
||
index_value = float(index_value)
|
||
except ValueError:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "index_value必须是数值"
|
||
}), 400
|
||
|
||
# 调用添加方法
|
||
result = fear_greed_manager.add_index_data(index_value, trading_date)
|
||
|
||
if result:
|
||
return jsonify({
|
||
"status": "success",
|
||
"message": "恐贪指数数据添加成功"
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "恐贪指数数据添加失败"
|
||
}), 500
|
||
|
||
except Exception as e:
|
||
logger.error(f"添加恐贪指数数据异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
# 获取可用指数列表
|
||
@app.route('/api/indices/list', methods=['GET'])
|
||
def get_indices_list():
|
||
"""
|
||
获取可用指数列表
|
||
|
||
返回所有可用于叠加显示的指数列表
|
||
"""
|
||
try:
|
||
indices = index_analyzer.get_indices_list()
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": indices
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"获取指数列表失败: {str(e)}")
|
||
return jsonify({"status": "error", "message": str(e)})
|
||
|
||
# 获取指数历史数据
|
||
@app.route('/api/indices/data', methods=['GET'])
|
||
def get_index_data():
|
||
"""
|
||
获取指数历史数据
|
||
|
||
参数:
|
||
- code: 指数代码
|
||
- start_date: 开始日期 (可选，默认为1年前)
|
||
- end_date: 结束日期 (可选，默认为今天)
|
||
|
||
返回指数历史收盘价数据
|
||
"""
|
||
try:
|
||
index_code = request.args.get('code')
|
||
start_date = request.args.get('start_date')
|
||
end_date = request.args.get('end_date')
|
||
|
||
if not index_code:
|
||
return jsonify({"status": "error", "message": "缺少指数代码参数"})
|
||
|
||
index_data = index_analyzer.get_index_data(index_code, start_date, end_date)
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": index_data
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"获取指数数据失败: {str(e)}")
|
||
return jsonify({"status": "error", "message": str(e)})
|
||
|
||
@app.route('/api/financial/analysis', methods=['GET'])
|
||
def financial_analysis():
|
||
"""
|
||
财务分析接口
|
||
|
||
请求参数:
|
||
stock_code: 股票代码
|
||
force_update: 是否强制更新缓存（可选，默认为false）
|
||
current_year: 当前年份，格式为'YYYY-12-31'（可选，默认为'2024-12-31'）
|
||
previous_year: 上一年份，格式为'YYYY-12-31'（可选，默认为'2023-12-31'）
|
||
|
||
返回:
|
||
分析结果JSON
|
||
"""
|
||
try:
|
||
stock_code = request.args.get('stock_code')
|
||
if not stock_code:
|
||
return jsonify({
|
||
'success': False,
|
||
'message': '缺少必要参数：stock_code'
|
||
}), 400
|
||
|
||
analyzer = FinancialAnalyzer()
|
||
result2024 = analyzer.analyze_financial_data(stock_code, current_year = '2024-12-31', previous_year = '2023-12-31')
|
||
result2023 = analyzer.analyze_financial_data(stock_code, current_year = '2023-12-31', previous_year = '2022-12-31')
|
||
result2022 = analyzer.analyze_financial_data(stock_code, current_year = '2022-12-31', previous_year = '2021-12-31')
|
||
|
||
# 合并2023和2022的is_better、change_rate、change和avg_score到2024的result
|
||
def merge_year_data(target, source, year):
|
||
for block in ["financial_strength", "profitability", "growth", "value_rating", "liquidity"]:
|
||
if block in target and block in source:
|
||
# avg_score
|
||
target[block][f"avg_score_{year}"] = source[block].get("avg_score")
|
||
# indicators
|
||
if "indicators" in target[block] and "indicators" in source[block]:
|
||
for t_item, s_item in zip(target[block]["indicators"], source[block]["indicators"]):
|
||
for k in ["is_better", "change_rate", "change"]:
|
||
if k in s_item:
|
||
t_item[f"{k}_{year}"] = s_item.get(k)
|
||
merge_year_data(result2024, result2023, "2023")
|
||
merge_year_data(result2024, result2022, "2022")
|
||
|
||
return jsonify(result2024)
|
||
|
||
except Exception as e:
|
||
logger.error(f"财务分析失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'财务分析失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/api/financial/indicators', methods=['GET'])
|
||
def get_financial_indicators():
|
||
"""
|
||
获取财务指标接口
|
||
|
||
请求参数:
|
||
stock_code: 股票代码
|
||
|
||
返回:
|
||
JSON格式的财务指标数据
|
||
"""
|
||
try:
|
||
# 获取股票代码
|
||
stock_code = request.args.get('stock_code')
|
||
if not stock_code:
|
||
return jsonify({
|
||
'success': False,
|
||
'message': '缺少必要参数: stock_code'
|
||
}), 400
|
||
|
||
# 创建分析器实例
|
||
analyzer = FinancialAnalyzer()
|
||
|
||
# 获取财务指标
|
||
result = analyzer.extract_financial_indicators(stock_code)
|
||
|
||
return jsonify(result)
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取财务指标失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'获取财务指标失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/api/financial/test_structure', methods=['GET'])
|
||
def test_mongo_structure():
|
||
"""
|
||
测试MongoDB集合结构接口
|
||
|
||
请求参数:
|
||
stock_code: 股票代码（可选）
|
||
|
||
返回:
|
||
JSON格式的集合结构信息
|
||
"""
|
||
try:
|
||
# 获取股票代码（可选）
|
||
stock_code = request.args.get('stock_code')
|
||
|
||
# 创建分析器实例
|
||
analyzer = FinancialAnalyzer()
|
||
|
||
# 获取集合结构
|
||
result = analyzer.test_mongo_structure(stock_code)
|
||
|
||
return jsonify(result)
|
||
|
||
except Exception as e:
|
||
logger.error(f"测试MongoDB结构失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'测试MongoDB结构失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/api/stock/real_time_price', methods=['GET'])
|
||
def get_real_time_price():
|
||
"""获取股票实时价格接口
|
||
|
||
参数:
|
||
- stock_code: 股票代码（必填）
|
||
|
||
返回:
|
||
{
|
||
"status": "success",
|
||
"data": {
|
||
"stock_code": "600000",
|
||
"stock_name": "浦发银行",
|
||
"current_price": 10.5,
|
||
"change_percent": 2.5,
|
||
"change_amount": 0.25,
|
||
"volume": 1234567,
|
||
"amount": 12345678.9,
|
||
"high": 10.8,
|
||
"low": 10.2,
|
||
"open": 10.3,
|
||
"pre_close": 10.25,
|
||
"update_time": "2024-01-20 14:30:00"
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 获取股票代码参数
|
||
stock_code = request.args.get('stock_code')
|
||
|
||
# 验证参数
|
||
if not stock_code:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: stock_code"
|
||
}), 400
|
||
|
||
# 导入股票价格采集器
|
||
from src.valuation_analysis.stock_price_collector import StockPriceCollector
|
||
|
||
# 创建采集器实例
|
||
collector = StockPriceCollector()
|
||
|
||
# 获取实时价格数据
|
||
price_data = collector.get_stock_price_data(stock_code)
|
||
|
||
if not price_data:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"获取股票 {stock_code} 的实时价格失败"
|
||
}), 404
|
||
|
||
# 构建响应数据
|
||
response_data = {
|
||
"stock_code": stock_code,
|
||
"stock_name": price_data.get('stock_name'),
|
||
"current_price": price_data.get('current_price'),
|
||
"change_percent": price_data.get('change_percent'),
|
||
"change_amount": price_data.get('change_amount'),
|
||
"volume": price_data.get('volume'),
|
||
"amount": price_data.get('amount'),
|
||
"high": price_data.get('high'),
|
||
"low": price_data.get('low'),
|
||
"open": price_data.get('open'),
|
||
"pre_close": price_data.get('pre_close'),
|
||
"update_time": price_data.get('update_time')
|
||
}
|
||
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": response_data
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取股票实时价格异常: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器错误: {str(e)}"
|
||
}), 500
|
||
|
||
@app.route('/bigscreen')
|
||
def bigscreen_page():
|
||
"""渲染大屏展示页面"""
|
||
return render_template('bigscreen.html')
|
||
|
||
|
||
@app.route('/bigscreenv2')
|
||
def bigscreen_page_v2():
|
||
"""渲染大屏展示页面"""
|
||
return render_template('bigscreen_v2.html')
|
||
|
||
@app.route('/api/bigscreen_data', methods=['GET'])
|
||
def bigscreen_data():
|
||
"""聚合大屏所需的12张图数据，便于前端一次性加载"""
|
||
try:
|
||
# 资金流向
|
||
north = hsgt_monitor.fetch_northbound_data()
|
||
south = hsgt_monitor.fetch_southbound_data()
|
||
# 融资融券
|
||
rzrq = em_rzrq_collector.get_chart_data(limit_days=90)
|
||
# 恐贪指数
|
||
fear_greed = fear_greed_manager.get_index_data(limit=180)
|
||
# 概念板块
|
||
concepts = [
|
||
("先进封装", "xjfz"),
|
||
("芯片", "xp"),
|
||
("消费电子概念", "xfdz"),
|
||
("机器人概念", "jqr")
|
||
]
|
||
concept_data = {}
|
||
for cname, key in concepts:
|
||
res = industry_analyzer.get_concept_analysis(cname, 'pe', None)
|
||
if res.get('success'):
|
||
# PE主线
|
||
pe = {
|
||
'dates': res['valuation']['dates'],
|
||
'values': res['valuation']['avg_values']
|
||
}
|
||
# 拥挤度
|
||
crowding = res.get('crowding', {})
|
||
crowding_obj = {
|
||
'dates': crowding.get('dates', []),
|
||
'values': crowding.get('percentiles', [])
|
||
} if crowding else {'dates': [], 'values': []}
|
||
concept_data[key] = {'pe': pe, 'crowding': crowding_obj}
|
||
else:
|
||
concept_data[key] = {'pe': {'dates': [], 'values': []}, 'crowding': {'dates': [], 'values': []}}
|
||
return jsonify({
|
||
'status': 'success',
|
||
'northbound': {
|
||
'dates': north.get('times', []),
|
||
'values': north.get('data', {}).get('total', [])
|
||
} if north.get('success') else {'dates': [], 'values': []},
|
||
'southbound': {
|
||
'dates': south.get('times', []),
|
||
'values': south.get('data', {}).get('total', [])
|
||
} if south.get('success') else {'dates': [], 'values': []},
|
||
'rzrq': {
|
||
'dates': rzrq.get('dates', []),
|
||
'values': rzrq.get('series', [{}])[0].get('data', [])
|
||
} if rzrq.get('success') and rzrq.get('series') else {'dates': [], 'values': []},
|
||
'fear_greed': {
|
||
'dates': fear_greed.get('dates', []),
|
||
'values': fear_greed.get('values', [])
|
||
} if fear_greed.get('success') else {'dates': [], 'values': []},
|
||
'concepts': concept_data
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"大屏数据聚合失败: {str(e)}")
|
||
return jsonify({'status': 'error', 'message': str(e)})
|
||
|
||
@app.route('/api/pep_stock_info_by_shortname', methods=['GET'])
|
||
def get_pep_stock_info_by_shortname():
|
||
"""根据股票简称查询pep_stock_info集合中的全部字段"""
|
||
short_name = request.args.get('short_name')
|
||
if not short_name:
|
||
return jsonify({'success': False, 'message': '缺少必要参数: short_name'}), 400
|
||
try:
|
||
analyzer = FinancialAnalyzer()
|
||
result = analyzer.get_pep_stock_info_by_shortname(short_name)
|
||
return jsonify(result)
|
||
except Exception as e:
|
||
return jsonify({'success': False, 'message': f'服务器错误: {str(e)}'}), 500
|
||
|
||
@app.route('/api/pep_stock_info_by_code', methods=['GET'])
|
||
def get_pep_stock_info_by_code():
|
||
"""根据股票代码查询Redis中的实时行情并返回指定结构"""
|
||
short_code = request.args.get('code')
|
||
if not short_code:
|
||
return jsonify({'success': False, 'message': '缺少必要参数: short_code'}), 400
|
||
try:
|
||
# 兼容600001.SH/SH600001等格式
|
||
from src.quantitative_analysis.batch_stock_price_collector import get_stock_realtime_info_from_redis
|
||
result = get_stock_realtime_info_from_redis(short_code)
|
||
if result:
|
||
return jsonify(result)
|
||
else:
|
||
return jsonify({'success': False, 'message': f'未找到股票 {short_code} 的实时行情'}), 404
|
||
except Exception as e:
|
||
return jsonify({'success': False, 'message': f'服务器错误: {str(e)}'}), 500
|
||
|
||
@app.route('/api/industry/crowding/filter', methods=['GET'])
|
||
def filter_industry_crowding():
|
||
"""根据拥挤度百分位区间筛选行业和概念板块"""
|
||
try:
|
||
min_val = float(request.args.get('min', 0))
|
||
max_val = float(request.args.get('max', 100))
|
||
from src.valuation_analysis.industry_analysis import IndustryAnalyzer
|
||
analyzer = IndustryAnalyzer()
|
||
result = analyzer.filter_crowding_by_percentile(min_val, max_val)
|
||
return jsonify({
|
||
'status': 'success',
|
||
'min': min_val,
|
||
'max': max_val,
|
||
'result': result
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"筛选行业/概念拥挤度接口异常: {str(e)}")
|
||
return jsonify({
|
||
'status': 'error',
|
||
'message': str(e)
|
||
}), 500
|
||
|
||
@app.route('/api/quantitative/momentum_by_plate', methods=['GET'])
|
||
def get_momentum_by_plate():
|
||
"""
|
||
根据行业或概念板块名称，批量获取所有成分股的动量数据
|
||
---
|
||
parameters:
|
||
- name: name
|
||
in: query
|
||
type: string
|
||
required: true
|
||
description: 行业或概念的名称.
|
||
- name: type
|
||
in: query
|
||
type: string
|
||
required: false
|
||
description: 板块类型, 'industry' (默认) 或 'concept'.
|
||
responses:
|
||
200:
|
||
description: A list of momentum indicators for stocks in the plate.
|
||
schema:
|
||
type: object
|
||
properties:
|
||
success:
|
||
type: boolean
|
||
data:
|
||
type: array
|
||
items:
|
||
type: object
|
||
"""
|
||
try:
|
||
plate_name = request.args.get('name')
|
||
plate_type = request.args.get('type', 'industry')
|
||
|
||
if not plate_name:
|
||
return jsonify({'success': False, 'message': '必须提供板块名称(name参数)'}), 400
|
||
|
||
is_concept = plate_type.lower() == 'concept'
|
||
|
||
analyzer = MomentumAnalyzer()
|
||
result = analyzer.analyze_momentum_by_name(plate_name, is_concept=is_concept)
|
||
|
||
if result.get('success'):
|
||
return jsonify(result)
|
||
else:
|
||
return jsonify(result), 404
|
||
|
||
except Exception as e:
|
||
logger.error(f"批量获取板块动量数据接口异常: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': str(e)
|
||
}), 500
|
||
|
||
@app.route('/scheduler/batch_stock_price/collection', methods=['GET'])
|
||
def run_batch_stock_price_collection():
|
||
"""批量采集A股行情并保存到数据库"""
|
||
try:
|
||
fetch_and_store_stock_data()
|
||
return jsonify({"status": "success", "message": "批量采集A股行情并保存到数据库成功"})
|
||
except Exception as e:
|
||
logger.error(f"批量采集A股行情失败: {str(e)}")
|
||
return jsonify({"status": "error", "message": str(e)})
|
||
|
||
@app.route('/scheduler/batch_hk_stock_price/collection', methods=['GET'])
|
||
def run_batch_hk_stock_price_collection():
|
||
"""批量采集港股行情并保存到数据库"""
|
||
try:
|
||
fetch_and_store_hk_stock_data()
|
||
return jsonify({"status": "success", "message": "批量采集A股行情并保存到数据库成功"})
|
||
except Exception as e:
|
||
logger.error(f"批量采集A股行情失败: {str(e)}")
|
||
return jsonify({"status": "error", "message": str(e)})
|
||
|
||
@app.route('/api/portfolio/industry_allocation', methods=['GET'])
|
||
def get_portfolio_industry_allocation():
|
||
"""获取行业持仓占比数据"""
|
||
try:
|
||
# 导入持仓分析器
|
||
from src.valuation_analysis.portfolio_analyzer import PortfolioAnalyzer
|
||
|
||
# 创建分析器实例
|
||
analyzer = PortfolioAnalyzer()
|
||
|
||
# 获取行业持仓分配数据
|
||
result = analyzer.analyze_portfolio_allocation()
|
||
|
||
if result.get("success"):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result["data"]
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get("message", "获取持仓数据失败")
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取行业持仓占比失败: {str(e)}")
|
||
return jsonify({'status': 'error', 'message': str(e)})
|
||
|
||
@app.route('/api/notice/list', methods=['GET'])
|
||
def get_notice_list():
|
||
"""获取重要提醒列表"""
|
||
try:
|
||
# 导入提醒服务
|
||
from src.valuation_analysis.notice_service import NoticeService
|
||
|
||
# 创建提醒服务实例
|
||
notice_service = NoticeService()
|
||
|
||
# 获取动态提醒数据
|
||
result = notice_service.get_dynamic_notices()
|
||
|
||
if result.get("success"):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result["data"]
|
||
})
|
||
else:
|
||
# 如果动态提醒失败，返回默认提醒
|
||
logger.warning(f"动态提醒获取失败: {result.get('message')}，使用默认提醒")
|
||
default_notices = [
|
||
"📈 上证指数突破3200点，市场情绪回暖",
|
||
"💰 北向资金今日净流入85.6亿元",
|
||
"📊 科技板块PE估值处于历史低位",
|
||
"🔥 新能源概念股集体上涨，涨幅超3%",
|
||
"⚠️ 医药板块回调，建议关注低吸机会",
|
||
"📈 融资融券余额连续三日增长",
|
||
"💰 消费板块资金流入明显",
|
||
"📊 市场恐贪指数回升至65",
|
||
"🤖 机器人概念板块技术面突破",
|
||
"📦 先进封装概念获政策支持"
|
||
]
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": default_notices
|
||
})
|
||
except Exception as e:
|
||
logger.error(f"获取提醒列表失败: {str(e)}")
|
||
return jsonify({'status': 'error', 'message': str(e)})
|
||
|
||
@app.route('/api/portfolio/summary', methods=['GET'])
|
||
def get_portfolio_summary():
|
||
"""获取持仓摘要信息"""
|
||
try:
|
||
# 导入持仓分析器
|
||
from src.valuation_analysis.portfolio_analyzer import PortfolioAnalyzer
|
||
|
||
# 创建分析器实例
|
||
analyzer = PortfolioAnalyzer()
|
||
|
||
# 获取持仓摘要数据
|
||
result = analyzer.get_portfolio_summary()
|
||
|
||
if result.get("success"):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result["data"]
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get("message", "获取持仓摘要失败")
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取持仓摘要失败: {str(e)}")
|
||
return jsonify({'status': 'error', 'message': str(e)})
|
||
|
||
@app.route('/api/portfolio/industry_holdings', methods=['GET'])
|
||
def get_industry_holdings_detail():
|
||
"""获取指定行业的详细持仓信息"""
|
||
try:
|
||
industry_name = request.args.get('industry_name')
|
||
if not industry_name:
|
||
return jsonify({'status': 'error', 'message': '缺少必要参数: industry_name'}), 400
|
||
|
||
# 导入持仓分析器
|
||
from src.valuation_analysis.portfolio_analyzer import PortfolioAnalyzer
|
||
|
||
# 创建分析器实例
|
||
analyzer = PortfolioAnalyzer()
|
||
|
||
# 获取行业详细持仓数据
|
||
result = analyzer.get_industry_holdings_detail(industry_name)
|
||
|
||
if result.get("success"):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": result["data"]
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get("message", "获取行业持仓详情失败")
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取行业持仓详情失败: {str(e)}")
|
||
return jsonify({'status': 'error', 'message': str(e)})
|
||
|
||
|
||
@app.route('/api/valuation/indicator', methods=['POST'])
|
||
def analyze_valuation_indicator():
|
||
"""分析股票应该使用PE还是PB估值
|
||
POST参数:
|
||
- stock_code: 股票代码 (例如: 000001)
|
||
- stock_name: 股票名称 (例如: 平安银行)
|
||
|
||
返回格式:
|
||
{
|
||
"status": "success",
|
||
"data": {
|
||
"recommended_indicator": "PB",
|
||
"reasoning": "平安银行属于金融服务业，作为商业银行，其商业模式基于资产负债管理。金融机构的盈利受拨备、利率、市场波动影响而不够稳定。基于金融业的特殊性，PB是更合适的估值指标..."
|
||
}
|
||
}
|
||
"""
|
||
try:
|
||
# 从POST表单参数获取
|
||
stock_code = request.form.get('stock_code')
|
||
stock_name = request.form.get('stock_name')
|
||
|
||
if not stock_code or not stock_name:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": "缺少必要参数: stock_code 或 stock_name"
|
||
}), 400
|
||
|
||
# 导入估值指标分析器
|
||
try:
|
||
from src.valuation_analysis.valuation_indicator_analyzer import ValuationIndicatorAnalyzer
|
||
logger.info("成功导入估值指标分析器")
|
||
except ImportError as e:
|
||
logger.error(f"无法导入估值指标分析器: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"服务器配置错误: 估值指标分析器不可用，错误详情: {str(e)}"
|
||
}), 500
|
||
|
||
# 创建分析器实例
|
||
analyzer = ValuationIndicatorAnalyzer()
|
||
|
||
# 执行分析
|
||
result = analyzer.analyze_valuation_indicator(stock_code, stock_name)
|
||
|
||
if result.get("success"):
|
||
return jsonify({
|
||
"status": "success",
|
||
"data": {
|
||
"recommended_indicator": result.get("recommended_indicator"),
|
||
"reasoning": result.get("reasoning", "")
|
||
}
|
||
})
|
||
else:
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": result.get("error", "分析失败，无详细信息")
|
||
}), 500
|
||
|
||
except Exception as e:
|
||
logger.error(f"估值指标分析失败: {str(e)}")
|
||
return jsonify({
|
||
"status": "error",
|
||
"message": f"估值指标分析失败: {str(e)}"
|
||
}), 500
|
||
|
||
if __name__ == '__main__':
|
||
|
||
# 启动Web服务器
|
||
app.run(host='0.0.0.0', port=5000, debug=True)
|