857 lines
30 KiB
Python
857 lines
30 KiB
Python
#!/usr/bin/env python3
|
||
"""
|
||
通达信API数据获取工具
|
||
支持A股、港股实时数据和历史数据
|
||
"""
|
||
|
||
import pandas as pd
|
||
import numpy as np
|
||
from datetime import datetime, timedelta
|
||
from typing import List, Dict, Optional, Tuple
|
||
import warnings
|
||
warnings.filterwarnings('ignore')
|
||
|
||
# 导入数据库管理器
|
||
try:
|
||
from tradingagents.config.database_manager import get_database_manager
|
||
DB_MANAGER_AVAILABLE = True
|
||
except ImportError:
|
||
DB_MANAGER_AVAILABLE = False
|
||
print("⚠️ 数据库缓存管理器不可用，尝试文件缓存")
|
||
|
||
# 导入MongoDB股票信息查询
|
||
try:
|
||
import os
|
||
from pymongo import MongoClient
|
||
MONGODB_AVAILABLE = True
|
||
except ImportError:
|
||
MONGODB_AVAILABLE = False
|
||
print("⚠️ pymongo未安装，无法从MongoDB获取股票名称")
|
||
|
||
try:
|
||
from .cache_manager import get_cache
|
||
FILE_CACHE_AVAILABLE = True
|
||
except ImportError:
|
||
FILE_CACHE_AVAILABLE = False
|
||
print("⚠️ 文件缓存管理器不可用，将直接从API获取数据")
|
||
|
||
try:
|
||
# 通达信Python接口
|
||
import pytdx
|
||
from pytdx.hq import TdxHq_API
|
||
from pytdx.exhq import TdxExHq_API
|
||
TDX_AVAILABLE = True
|
||
except ImportError:
|
||
TDX_AVAILABLE = False
|
||
print("⚠️ pytdx库未安装，无法使用通达信API")
|
||
print("💡 安装命令: pip install pytdx")
|
||
|
||
|
||
class TongDaXinDataProvider:
|
||
"""通达信数据提供器"""
|
||
|
||
def __init__(self):
|
||
print(f"🔍 [DEBUG] 初始化通达信数据提供器...")
|
||
self.api = None
|
||
self.exapi = None # 扩展行情API
|
||
self.connected = False
|
||
|
||
print(f"🔍 [DEBUG] 检查pytdx库可用性: {TDX_AVAILABLE}")
|
||
if not TDX_AVAILABLE:
|
||
error_msg = "pytdx库未安装，请运行: pip install pytdx"
|
||
print(f"❌ [DEBUG] {error_msg}")
|
||
raise ImportError(error_msg)
|
||
print(f"✅ [DEBUG] pytdx库检查通过")
|
||
|
||
def connect(self):
|
||
"""连接通达信服务器"""
|
||
print(f"🔍 [DEBUG] 开始连接通达信服务器...")
|
||
try:
|
||
# 尝试从配置文件加载可用服务器
|
||
print(f"🔍 [DEBUG] 加载服务器配置...")
|
||
working_servers = self._load_working_servers()
|
||
|
||
# 如果没有配置文件，使用默认服务器列表
|
||
if not working_servers:
|
||
print(f"🔍 [DEBUG] 未找到配置文件，使用默认服务器列表")
|
||
working_servers = [
|
||
{'ip': '115.238.56.198', 'port': 7709},
|
||
{'ip': '115.238.90.165', 'port': 7709},
|
||
{'ip': '180.153.18.170', 'port': 7709},
|
||
{'ip': '119.147.212.81', 'port': 7709}, # 备用
|
||
]
|
||
else:
|
||
print(f"🔍 [DEBUG] 从配置文件加载了 {len(working_servers)} 个服务器")
|
||
|
||
# 尝试连接可用服务器
|
||
print(f"🔍 [DEBUG] 创建通达信API实例...")
|
||
self.api = TdxHq_API()
|
||
print(f"🔍 [DEBUG] 开始尝试连接服务器...")
|
||
|
||
for i, server in enumerate(working_servers):
|
||
try:
|
||
print(f"🔍 [DEBUG] 尝试连接服务器 {i+1}/{len(working_servers)}: {server['ip']}:{server['port']}")
|
||
result = self.api.connect(server['ip'], server['port'])
|
||
print(f"🔍 [DEBUG] 连接结果: {result}")
|
||
if result:
|
||
print(f"✅ 通达信API连接成功: {server['ip']}:{server['port']}")
|
||
self.connected = True
|
||
return True
|
||
except Exception as e:
|
||
print(f"⚠️ 服务器 {server['ip']}:{server['port']} 连接失败: {e}")
|
||
continue
|
||
|
||
print("❌ 所有通达信服务器连接失败")
|
||
self.connected = False
|
||
return False
|
||
|
||
except Exception as e:
|
||
print(f"❌ 通达信API连接失败: {e}")
|
||
self.connected = False
|
||
return False
|
||
|
||
def _load_working_servers(self):
|
||
"""加载可用服务器配置"""
|
||
try:
|
||
import json
|
||
import os
|
||
|
||
config_file = 'tdx_servers_config.json'
|
||
if os.path.exists(config_file):
|
||
with open(config_file, 'r', encoding='utf-8') as f:
|
||
config = json.load(f)
|
||
return config.get('working_servers', [])
|
||
except Exception:
|
||
pass
|
||
return []
|
||
|
||
def disconnect(self):
|
||
"""断开连接"""
|
||
try:
|
||
if self.api:
|
||
self.api.disconnect()
|
||
if self.exapi:
|
||
self.exapi.disconnect()
|
||
self.connected = False
|
||
print("✅ 通达信API连接已断开")
|
||
except:
|
||
pass
|
||
|
||
def is_connected(self):
|
||
"""检查连接状态"""
|
||
if not self.connected or not self.api:
|
||
return False
|
||
|
||
# 尝试简单的API调用来验证连接是否有效
|
||
try:
|
||
# 获取市场信息作为连接测试
|
||
result = self.api.get_security_count(0) # 获取深圳市场股票数量
|
||
return result is not None and result > 0
|
||
except Exception as e:
|
||
print(f"🔍 [DEBUG] 连接测试失败: {e}")
|
||
self.connected = False
|
||
return False
|
||
|
||
def _get_stock_name(self, stock_code: str) -> str:
|
||
"""
|
||
获取股票名称
|
||
优先级：缓存 -> MongoDB -> 常用股票映射 -> API获取（仅深圳市场） -> 默认格式
|
||
Args:
|
||
stock_code: 股票代码
|
||
Returns:
|
||
str: 股票名称
|
||
"""
|
||
global _stock_name_cache
|
||
|
||
# 首先检查缓存
|
||
if stock_code in _stock_name_cache:
|
||
return _stock_name_cache[stock_code]
|
||
|
||
# 优先从MongoDB获取
|
||
mongodb_name = _get_stock_name_from_mongodb(stock_code)
|
||
if mongodb_name:
|
||
_stock_name_cache[stock_code] = mongodb_name
|
||
return mongodb_name
|
||
|
||
# 检查常用股票映射表
|
||
if stock_code in _common_stock_names:
|
||
name = _common_stock_names[stock_code]
|
||
_stock_name_cache[stock_code] = name
|
||
return name
|
||
|
||
# 如果API不可用，直接返回默认格式
|
||
if not self.connected:
|
||
if not self.connect():
|
||
default_name = f'股票{stock_code}'
|
||
_stock_name_cache[stock_code] = default_name
|
||
return default_name
|
||
|
||
try:
|
||
# 仅对深圳市场尝试从API获取（上海市场的get_security_list不可用）
|
||
market = self._get_market_code(stock_code)
|
||
if market == 0: # 深圳市场
|
||
try:
|
||
for start_pos in range(0, 2000, 1000): # 分批获取
|
||
stock_list = self.api.get_security_list(market, start_pos)
|
||
if stock_list:
|
||
for stock_info in stock_list:
|
||
if stock_info.get('code') == stock_code:
|
||
stock_name = stock_info.get('name', '').strip()
|
||
if stock_name:
|
||
_stock_name_cache[stock_code] = stock_name
|
||
return stock_name
|
||
except Exception as e:
|
||
print(f"⚠️ 获取深圳股票列表失败: {e}")
|
||
|
||
# 如果都失败了，返回默认格式并缓存
|
||
default_name = f'股票{stock_code}'
|
||
_stock_name_cache[stock_code] = default_name
|
||
return default_name
|
||
|
||
except Exception as e:
|
||
print(f"⚠️ 获取股票名称失败: {e}")
|
||
default_name = f'股票{stock_code}'
|
||
_stock_name_cache[stock_code] = default_name
|
||
return default_name
|
||
|
||
def get_real_time_data(self, stock_code: str) -> Dict:
|
||
"""
|
||
获取股票实时数据
|
||
Args:
|
||
stock_code: 股票代码
|
||
Returns:
|
||
Dict: 实时数据
|
||
"""
|
||
if not self.connected:
|
||
if not self.connect():
|
||
return {}
|
||
|
||
try:
|
||
market = self._get_market_code(stock_code)
|
||
|
||
# 获取实时数据
|
||
data = self.api.get_security_quotes([(market, stock_code)])
|
||
|
||
if not data:
|
||
return {}
|
||
|
||
quote = data[0]
|
||
|
||
# 安全获取字段，避免KeyError
|
||
def safe_get(key, default=0):
|
||
return quote.get(key, default)
|
||
|
||
return {
|
||
'code': stock_code,
|
||
'name': self._get_stock_name(stock_code), # 使用独立的股票名称获取方法
|
||
'price': safe_get('price'),
|
||
'last_close': safe_get('last_close'),
|
||
'open': safe_get('open'),
|
||
'high': safe_get('high'),
|
||
'low': safe_get('low'),
|
||
'volume': safe_get('vol'),
|
||
'amount': safe_get('amount'),
|
||
'change': safe_get('price') - safe_get('last_close'),
|
||
'change_percent': ((safe_get('price') - safe_get('last_close')) / safe_get('last_close') * 100) if safe_get('last_close') > 0 else 0,
|
||
'bid_prices': [safe_get(f'bid{i}') for i in range(1, 6)],
|
||
'bid_volumes': [safe_get(f'bid_vol{i}') for i in range(1, 6)],
|
||
'ask_prices': [safe_get(f'ask{i}') for i in range(1, 6)],
|
||
'ask_volumes': [safe_get(f'ask_vol{i}') for i in range(1, 6)],
|
||
'update_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S')
|
||
}
|
||
|
||
except Exception as e:
|
||
print(f"获取实时数据失败: {e}")
|
||
return {}
|
||
|
||
def get_stock_history_data(self, stock_code: str, start_date: str, end_date: str, period: str = 'D') -> pd.DataFrame:
|
||
"""
|
||
获取股票历史数据
|
||
Args:
|
||
stock_code: 股票代码
|
||
start_date: 开始日期 'YYYY-MM-DD'
|
||
end_date: 结束日期 'YYYY-MM-DD'
|
||
period: 周期 'D'=日线, 'W'=周线, 'M'=月线
|
||
Returns:
|
||
DataFrame: 历史数据
|
||
"""
|
||
if not self.connected:
|
||
if not self.connect():
|
||
return pd.DataFrame()
|
||
|
||
try:
|
||
market = self._get_market_code(stock_code)
|
||
|
||
# 计算需要获取的数据量
|
||
start_dt = datetime.strptime(start_date, '%Y-%m-%d')
|
||
end_dt = datetime.strptime(end_date, '%Y-%m-%d')
|
||
days_diff = (end_dt - start_dt).days
|
||
|
||
# 根据周期调整数据量
|
||
if period == 'D':
|
||
count = min(days_diff + 10, 800) # 日线最多800条
|
||
elif period == 'W':
|
||
count = min(days_diff // 7 + 10, 800)
|
||
elif period == 'M':
|
||
count = min(days_diff // 30 + 10, 800)
|
||
else:
|
||
count = 800
|
||
|
||
# 获取K线数据
|
||
category_map = {'D': 9, 'W': 5, 'M': 6}
|
||
category = category_map.get(period, 9)
|
||
|
||
data = self.api.get_security_bars(category, market, stock_code, 0, count)
|
||
|
||
if not data:
|
||
return pd.DataFrame()
|
||
|
||
# 转换为DataFrame
|
||
df = pd.DataFrame(data)
|
||
|
||
# 处理数据格式
|
||
df['datetime'] = pd.to_datetime(df['datetime'])
|
||
df = df.set_index('datetime')
|
||
df = df.sort_index()
|
||
|
||
# 筛选日期范围
|
||
df = df[start_date:end_date]
|
||
|
||
# 重命名列以匹配Yahoo Finance格式
|
||
df = df.rename(columns={
|
||
'open': 'Open',
|
||
'high': 'High',
|
||
'low': 'Low',
|
||
'close': 'Close',
|
||
'vol': 'Volume',
|
||
'amount': 'Amount'
|
||
})
|
||
|
||
# 添加股票代码信息
|
||
df['Symbol'] = stock_code
|
||
|
||
return df
|
||
|
||
except Exception as e:
|
||
print(f"获取历史数据失败: {e}")
|
||
return pd.DataFrame()
|
||
|
||
def get_stock_technical_indicators(self, stock_code: str, period: int = 20) -> Dict:
|
||
"""
|
||
计算技术指标
|
||
Args:
|
||
stock_code: 股票代码
|
||
period: 计算周期
|
||
Returns:
|
||
Dict: 技术指标数据
|
||
"""
|
||
try:
|
||
# 获取最近的历史数据
|
||
end_date = datetime.now().strftime('%Y-%m-%d')
|
||
start_date = (datetime.now() - timedelta(days=period*2)).strftime('%Y-%m-%d')
|
||
|
||
df = self.get_stock_history_data(stock_code, start_date, end_date)
|
||
|
||
if df.empty:
|
||
return {}
|
||
|
||
# 计算技术指标
|
||
indicators = {}
|
||
|
||
# 移动平均线
|
||
indicators['MA5'] = df['Close'].rolling(5).mean().iloc[-1] if len(df) >= 5 else None
|
||
indicators['MA10'] = df['Close'].rolling(10).mean().iloc[-1] if len(df) >= 10 else None
|
||
indicators['MA20'] = df['Close'].rolling(20).mean().iloc[-1] if len(df) >= 20 else None
|
||
|
||
# RSI
|
||
if len(df) >= 14:
|
||
delta = df['Close'].diff()
|
||
gain = (delta.where(delta > 0, 0)).rolling(14).mean()
|
||
loss = (-delta.where(delta < 0, 0)).rolling(14).mean()
|
||
rs = gain / loss
|
||
indicators['RSI'] = (100 - (100 / (1 + rs))).iloc[-1]
|
||
|
||
# MACD
|
||
if len(df) >= 26:
|
||
exp1 = df['Close'].ewm(span=12).mean()
|
||
exp2 = df['Close'].ewm(span=26).mean()
|
||
macd = exp1 - exp2
|
||
signal = macd.ewm(span=9).mean()
|
||
indicators['MACD'] = macd.iloc[-1]
|
||
indicators['MACD_Signal'] = signal.iloc[-1]
|
||
indicators['MACD_Histogram'] = (macd - signal).iloc[-1]
|
||
|
||
# 布林带
|
||
if len(df) >= 20:
|
||
sma = df['Close'].rolling(20).mean()
|
||
std = df['Close'].rolling(20).std()
|
||
indicators['BB_Upper'] = (sma + 2 * std).iloc[-1]
|
||
indicators['BB_Middle'] = sma.iloc[-1]
|
||
indicators['BB_Lower'] = (sma - 2 * std).iloc[-1]
|
||
|
||
return indicators
|
||
|
||
except Exception as e:
|
||
print(f"计算技术指标失败: {e}")
|
||
return {}
|
||
|
||
def search_stocks(self, keyword: str) -> List[Dict]:
|
||
"""
|
||
搜索股票
|
||
Args:
|
||
keyword: 搜索关键词（股票代码或名称）
|
||
Returns:
|
||
List[Dict]: 搜索结果
|
||
"""
|
||
if not self.connected:
|
||
if not self.connect():
|
||
return []
|
||
|
||
try:
|
||
# 通达信没有直接的搜索API，这里提供一个简化的实现
|
||
# 实际使用中可以维护一个股票代码表
|
||
|
||
# 常见股票代码映射
|
||
stock_mapping = {
|
||
'平安银行': '000001',
|
||
'万科A': '000002',
|
||
'中国平安': '601318',
|
||
'贵州茅台': '600519',
|
||
'招商银行': '600036',
|
||
'五粮液': '000858',
|
||
'格力电器': '000651',
|
||
'美的集团': '000333',
|
||
'中国石化': '600028',
|
||
'工商银行': '601398'
|
||
}
|
||
|
||
results = []
|
||
|
||
# 按关键词搜索
|
||
for name, code in stock_mapping.items():
|
||
if keyword.lower() in name.lower() or keyword in code:
|
||
# 获取实时数据
|
||
realtime_data = self.get_real_time_data(code)
|
||
if realtime_data:
|
||
results.append({
|
||
'code': code,
|
||
'name': name,
|
||
'price': realtime_data.get('price', 0),
|
||
'change_percent': realtime_data.get('change_percent', 0)
|
||
})
|
||
|
||
return results
|
||
|
||
except Exception as e:
|
||
print(f"搜索股票失败: {e}")
|
||
return []
|
||
|
||
def _get_market_code(self, stock_code: str) -> int:
|
||
"""
|
||
根据股票代码判断市场
|
||
Args:
|
||
stock_code: 股票代码
|
||
Returns:
|
||
int: 市场代码 (0=深圳, 1=上海)
|
||
"""
|
||
if stock_code.startswith(('000', '002', '003', '300')):
|
||
return 0 # 深圳
|
||
elif stock_code.startswith(('600', '601', '603', '605', '688')):
|
||
return 1 # 上海
|
||
else:
|
||
return 0 # 默认深圳
|
||
|
||
def get_market_overview(self) -> Dict:
|
||
"""获取市场概览"""
|
||
if not self.connected:
|
||
if not self.connect():
|
||
return {}
|
||
|
||
try:
|
||
# 获取主要指数数据
|
||
indices = {
|
||
'上证指数': ('1', '000001'),
|
||
'深证成指': ('0', '399001'),
|
||
'创业板指': ('0', '399006'),
|
||
'科创50': ('1', '000688')
|
||
}
|
||
|
||
market_data = {}
|
||
|
||
for name, (market, code) in indices.items():
|
||
try:
|
||
data = self.api.get_security_quotes([(int(market), code)])
|
||
if data:
|
||
quote = data[0]
|
||
market_data[name] = {
|
||
'price': quote['price'],
|
||
'change': quote['price'] - quote['last_close'],
|
||
'change_percent': ((quote['price'] - quote['last_close']) / quote['last_close'] * 100) if quote['last_close'] > 0 else 0,
|
||
'volume': quote['vol']
|
||
}
|
||
except:
|
||
continue
|
||
|
||
return market_data
|
||
|
||
except Exception as e:
|
||
print(f"获取市场概览失败: {e}")
|
||
return {}
|
||
|
||
|
||
# 全局实例和缓存
|
||
_tdx_provider = None
|
||
_stock_name_cache = {} # 股票名称缓存，避免重复API调用
|
||
_mongodb_client = None
|
||
_mongodb_db = None
|
||
|
||
def _get_mongodb_connection():
|
||
"""获取MongoDB连接"""
|
||
global _mongodb_client, _mongodb_db
|
||
|
||
if not MONGODB_AVAILABLE:
|
||
return None, None
|
||
|
||
if _mongodb_client is None or _mongodb_db is None:
|
||
try:
|
||
# 从环境变量获取MongoDB配置
|
||
config = {
|
||
'host': os.getenv('MONGODB_HOST', 'localhost'),
|
||
'port': int(os.getenv('MONGODB_PORT', 27018)),
|
||
'username': os.getenv('MONGODB_USERNAME'),
|
||
'password': os.getenv('MONGODB_PASSWORD'),
|
||
'database': os.getenv('MONGODB_DATABASE', 'tradingagents'),
|
||
'auth_source': os.getenv('MONGODB_AUTH_SOURCE', 'admin')
|
||
}
|
||
|
||
# 构建连接字符串
|
||
if config.get('username') and config.get('password'):
|
||
connection_string = f"mongodb://{config['username']}:{config['password']}@{config['host']}:{config['port']}/{config['auth_source']}"
|
||
else:
|
||
connection_string = f"mongodb://{config['host']}:{config['port']}/"
|
||
|
||
# 创建客户端
|
||
_mongodb_client = MongoClient(
|
||
connection_string,
|
||
serverSelectionTimeoutMS=3000 # 3秒超时
|
||
)
|
||
|
||
# 测试连接
|
||
_mongodb_client.admin.command('ping')
|
||
|
||
# 选择数据库
|
||
_mongodb_db = _mongodb_client[config['database']]
|
||
|
||
except Exception as e:
|
||
print(f"⚠️ MongoDB连接失败: {e}")
|
||
_mongodb_client = None
|
||
_mongodb_db = None
|
||
|
||
return _mongodb_client, _mongodb_db
|
||
|
||
def _get_stock_name_from_mongodb(stock_code: str) -> Optional[str]:
|
||
"""从MongoDB获取股票名称"""
|
||
try:
|
||
client, db = _get_mongodb_connection()
|
||
if db is None:
|
||
return None
|
||
|
||
collection = db['stock_basic_info']
|
||
stock_info = collection.find_one({'code': stock_code})
|
||
|
||
if stock_info and 'name' in stock_info:
|
||
return stock_info['name'].strip()
|
||
|
||
return None
|
||
|
||
except Exception as e:
|
||
print(f"⚠️ 从MongoDB获取股票名称失败: {e}")
|
||
return None
|
||
|
||
# 精简的常用股票名称映射（仅包含最常见的股票）
|
||
_common_stock_names = {
|
||
# 深圳主板
|
||
'000001': '平安银行',
|
||
'000002': '万科A',
|
||
'000858': '五粮液',
|
||
'000895': '双汇发展',
|
||
|
||
# 深圳中小板
|
||
'002594': '比亚迪',
|
||
'002415': '海康威视',
|
||
'002304': '洋河股份',
|
||
|
||
# 深圳创业板
|
||
'300059': '东方财富',
|
||
'300750': '宁德时代',
|
||
'300015': '爱尔眼科',
|
||
|
||
# 上海主板
|
||
'600519': '贵州茅台',
|
||
'600036': '招商银行',
|
||
'601398': '工商银行',
|
||
'601127': '小康股份',
|
||
'600000': '浦发银行',
|
||
'601318': '中国平安',
|
||
'600276': '恒瑞医药',
|
||
'600887': '伊利股份',
|
||
|
||
# 科创板
|
||
'688981': '中芯国际',
|
||
'688599': '天合光能',
|
||
}
|
||
|
||
def get_tdx_provider() -> TongDaXinDataProvider:
|
||
"""获取通达信数据提供器实例"""
|
||
global _tdx_provider
|
||
if _tdx_provider is None:
|
||
print(f"🔍 [DEBUG] 创建新的通达信数据提供器实例...")
|
||
_tdx_provider = TongDaXinDataProvider()
|
||
print(f"🔍 [DEBUG] 通达信数据提供器实例创建完成")
|
||
else:
|
||
print(f"🔍 [DEBUG] 使用现有的通达信数据提供器实例")
|
||
# 检查连接状态，如果连接断开则重新创建
|
||
if not _tdx_provider.is_connected():
|
||
print(f"🔍 [DEBUG] 检测到连接断开，重新创建通达信数据提供器...")
|
||
_tdx_provider = TongDaXinDataProvider()
|
||
print(f"🔍 [DEBUG] 通达信数据提供器重新创建完成")
|
||
return _tdx_provider
|
||
|
||
|
||
def get_china_stock_data(stock_code: str, start_date: str, end_date: str) -> str:
|
||
"""
|
||
获取中国股票数据的主要接口函数（支持缓存）
|
||
Args:
|
||
stock_code: 股票代码 (如 '000001')
|
||
start_date: 开始日期 'YYYY-MM-DD'
|
||
end_date: 结束日期 'YYYY-MM-DD'
|
||
Returns:
|
||
str: 格式化的股票数据
|
||
"""
|
||
print(f"📊 正在获取中国股票数据: {stock_code} ({start_date} 到 {end_date})")
|
||
|
||
# 优先尝试从数据库缓存加载数据（使用统一的database_manager）
|
||
try:
|
||
from tradingagents.config.database_manager import get_database_manager
|
||
db_manager = get_database_manager()
|
||
if db_manager.is_mongodb_available():
|
||
# 直接使用MongoDB客户端查询缓存数据
|
||
mongodb_client = db_manager.get_mongodb_client()
|
||
if mongodb_client:
|
||
db = mongodb_client[db_manager.mongodb_config["database"]]
|
||
collection = db.stock_data
|
||
|
||
# 查询最近的缓存数据
|
||
from datetime import datetime, timedelta
|
||
cutoff_time = datetime.utcnow() - timedelta(hours=6)
|
||
|
||
cached_doc = collection.find_one({
|
||
"symbol": stock_code,
|
||
"market_type": "china",
|
||
"created_at": {"$gte": cutoff_time}
|
||
}, sort=[("created_at", -1)])
|
||
|
||
if cached_doc and 'data' in cached_doc:
|
||
print(f"🗄️ 从MongoDB缓存加载数据: {stock_code}")
|
||
return cached_doc['data']
|
||
except Exception as e:
|
||
print(f"⚠️ 从MongoDB加载缓存失败: {e}")
|
||
|
||
# 如果数据库缓存不可用，尝试文件缓存
|
||
if FILE_CACHE_AVAILABLE:
|
||
cache = get_cache()
|
||
cache_key = cache.find_cached_stock_data(
|
||
symbol=stock_code,
|
||
start_date=start_date,
|
||
end_date=end_date,
|
||
data_source="tdx",
|
||
max_age_hours=6 # 6小时内的缓存有效
|
||
)
|
||
|
||
if cache_key:
|
||
cached_data = cache.load_stock_data(cache_key)
|
||
if cached_data:
|
||
print(f"💾 从文件缓存加载数据: {stock_code} -> {cache_key}")
|
||
return cached_data
|
||
|
||
print(f"🌐 从通达信API获取数据: {stock_code}")
|
||
|
||
try:
|
||
provider = get_tdx_provider()
|
||
|
||
# 获取历史数据
|
||
df = provider.get_stock_history_data(stock_code, start_date, end_date)
|
||
|
||
if df.empty:
|
||
error_msg = f"❌ 未能获取股票 {stock_code} 的历史数据"
|
||
print(error_msg)
|
||
return error_msg
|
||
|
||
# 获取实时数据
|
||
realtime_data = provider.get_real_time_data(stock_code)
|
||
|
||
# 获取技术指标
|
||
indicators = provider.get_stock_technical_indicators(stock_code)
|
||
|
||
# 格式化输出
|
||
result = f"""
|
||
# {stock_code} 股票数据分析
|
||
|
||
## 📊 实时行情
|
||
- 股票名称: {realtime_data.get('name', 'N/A')}
|
||
- 当前价格: ¥{realtime_data.get('price', 0):.2f}
|
||
- 涨跌幅: {realtime_data.get('change_percent', 0):.2f}%
|
||
- 成交量: {realtime_data.get('volume', 0):,}手
|
||
- 更新时间: {realtime_data.get('update_time', 'N/A')}
|
||
|
||
## 📈 历史数据概览
|
||
- 数据期间: {start_date} 至 {end_date}
|
||
- 数据条数: {len(df)}条
|
||
- 期间最高: ¥{df['High'].max():.2f}
|
||
- 期间最低: ¥{df['Low'].min():.2f}
|
||
- 期间涨幅: {((df['Close'].iloc[-1] - df['Close'].iloc[0]) / df['Close'].iloc[0] * 100):.2f}%
|
||
|
||
## 🔍 技术指标
|
||
- MA5: ¥{indicators.get('MA5', 0):.2f}
|
||
- MA10: ¥{indicators.get('MA10', 0):.2f}
|
||
- MA20: ¥{indicators.get('MA20', 0):.2f}
|
||
- RSI: {indicators.get('RSI', 0):.2f}
|
||
- MACD: {indicators.get('MACD', 0):.4f}
|
||
|
||
## 📋 最近5日数据
|
||
{df.tail().to_string()}
|
||
|
||
数据来源: 通达信API (实时数据)
|
||
"""
|
||
|
||
# 优先保存到数据库缓存（使用统一的database_manager）
|
||
try:
|
||
from tradingagents.config.database_manager import get_database_manager
|
||
db_manager = get_database_manager()
|
||
if db_manager.is_mongodb_available():
|
||
# 直接使用MongoDB客户端保存数据
|
||
mongodb_client = db_manager.get_mongodb_client()
|
||
if mongodb_client:
|
||
db = mongodb_client[db_manager.mongodb_config["database"]]
|
||
collection = db.stock_data
|
||
|
||
doc = {
|
||
"symbol": stock_code,
|
||
"market_type": "china",
|
||
"data": result,
|
||
"metadata": {
|
||
'start_date': start_date,
|
||
'end_date': end_date,
|
||
'data_source': 'tdx',
|
||
'realtime_data': realtime_data,
|
||
'indicators': indicators,
|
||
'history_count': len(df)
|
||
},
|
||
"created_at": datetime.utcnow(),
|
||
"updated_at": datetime.utcnow()
|
||
}
|
||
|
||
collection.replace_one(
|
||
{"symbol": stock_code, "market_type": "china"},
|
||
doc,
|
||
upsert=True
|
||
)
|
||
print(f"💾 数据已保存到MongoDB: {stock_code}")
|
||
except Exception as e:
|
||
print(f"⚠️ 保存到MongoDB失败: {e}")
|
||
|
||
# 同时保存到文件缓存作为备份
|
||
if FILE_CACHE_AVAILABLE:
|
||
cache = get_cache()
|
||
cache.save_stock_data(
|
||
symbol=stock_code,
|
||
data=result,
|
||
start_date=start_date,
|
||
end_date=end_date,
|
||
data_source="tdx"
|
||
)
|
||
|
||
return result
|
||
|
||
except Exception as e:
|
||
import traceback
|
||
error_details = traceback.format_exc()
|
||
print(f"❌ [DEBUG] 通达信API调用失败:")
|
||
print(f"❌ [DEBUG] 错误类型: {type(e).__name__}")
|
||
print(f"❌ [DEBUG] 错误信息: {str(e)}")
|
||
print(f"❌ [DEBUG] 详细堆栈:")
|
||
print(error_details)
|
||
|
||
return f"""
|
||
❌ 中国股票数据获取失败 - {stock_code}
|
||
错误类型: {type(e).__name__}
|
||
错误信息: {str(e)}
|
||
|
||
🔍 调试信息:
|
||
{error_details}
|
||
|
||
💡 解决建议:
|
||
1. 检查pytdx库是否已安装: pip install pytdx
|
||
2. 确认股票代码格式正确 (如: 000001, 600519)
|
||
3. 检查网络连接是否正常
|
||
4. 尝试重新连接通达信服务器
|
||
|
||
注: 通达信API需要网络连接到通达信服务器
|
||
"""
|
||
|
||
|
||
def get_china_market_overview() -> str:
|
||
"""获取中国股市概览"""
|
||
try:
|
||
provider = get_tdx_provider()
|
||
market_data = provider.get_market_overview()
|
||
|
||
if not market_data:
|
||
return "无法获取市场概览数据"
|
||
|
||
result = "# 中国股市概览\n\n"
|
||
|
||
for name, data in market_data.items():
|
||
change_symbol = "📈" if data['change'] >= 0 else "📉"
|
||
result += f"## {change_symbol} {name}\n"
|
||
result += f"- 当前点位: {data['price']:.2f}\n"
|
||
result += f"- 涨跌点数: {data['change']:+.2f}\n"
|
||
result += f"- 涨跌幅: {data['change_percent']:+.2f}%\n"
|
||
result += f"- 成交量: {data['volume']:,}\n\n"
|
||
|
||
result += f"更新时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n"
|
||
result += "数据来源: 通达信API\n"
|
||
|
||
return result
|
||
|
||
except Exception as e:
|
||
return f"获取市场概览失败: {str(e)}"
|
||
|
||
# 在文件末尾添加以下函数
|
||
|
||
def get_china_stock_data_enhanced(stock_code: str, start_date: str, end_date: str) -> str:
|
||
"""
|
||
增强版中国股票数据获取函数（完整降级机制）
|
||
这是get_china_stock_data的增强版本
|
||
|
||
Args:
|
||
stock_code: 股票代码 (如 '000001')
|
||
start_date: 开始日期 'YYYY-MM-DD'
|
||
end_date: 结束日期 'YYYY-MM-DD'
|
||
Returns:
|
||
str: 格式化的股票数据
|
||
"""
|
||
try:
|
||
from .stock_data_service import get_stock_data_service
|
||
service = get_stock_data_service()
|
||
return service.get_stock_data_with_fallback(stock_code, start_date, end_date)
|
||
except ImportError:
|
||
# 如果新服务不可用，降级到原有函数
|
||
print("⚠️ 增强服务不可用，使用原有函数")
|
||
return get_china_stock_data(stock_code, start_date, end_date)
|
||
except Exception as e:
|
||
print(f"⚠️ 增强服务出错，降级到原有函数: {e}")
|
||
return get_china_stock_data(stock_code, start_date, end_date)
|
||
|
||
# ... existing code ...
|