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# 数据获取模块
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import os
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import time
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import pandas as pd
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from typing import Dict, Optional, List
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from qihuo_analyzer.utils.config_manager import config_manager
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# 尝试导入tqsdk，如果失败则使用模拟数据
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try:
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from tqsdk import TqApi, TqAuth
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TQSDK_AVAILABLE = True
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except Exception as e:
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print(f"tqsdk导入失败：{e}，将使用模拟数据")
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TQSDK_AVAILABLE = False
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class DataFetcher:
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"""数据获取器"""
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def __init__(self):
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self.api = None
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def connect(self) -> bool:
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"""连接API"""
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try:
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if TQSDK_AVAILABLE:
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# 使用天勤TQSDK连接
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from qihuo_analyzer.utils.config_manager import config_manager
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username = os.getenv('TQSDK_USERNAME', '')
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password = os.getenv('TQSDK_PASSWORD', '')
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if username and password:
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self.api = TqApi(auth=TqAuth(username, password))
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print("API连接成功")
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return True
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else:
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print("TQSDK账号密码未配置，将使用模拟数据")
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self.api = None
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return False
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else:
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# 模拟API，用于测试
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print("使用模拟API")
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self.api = None
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return False
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except Exception as e:
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print(f"API连接失败：{e}")
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# 模拟API，用于测试
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self.api = None
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return False
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def disconnect(self):
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"""断开连接"""
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if self.api:
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try:
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self.api.close()
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print("API连接已断开")
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except:
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pass
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def _convert_duration(self, duration: str) -> int:
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"""将时间周期字符串转换为分钟数
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Args:
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duration: 时间周期，如 '1m', '5m', '15m', '1h', '1d'
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Returns:
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分钟数
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"""
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duration_map = {
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'1m': 1,
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'5m': 5,
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'15m': 15,
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'30m': 30,
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'1h': 60,
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'2h': 120,
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'4h': 240,
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'6h': 360,
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'12h': 720,
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'1d': 1440,
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'1w': 10080
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}
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return duration_map.get(duration, 60) # 默认60分钟
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def _convert_symbol(self, symbol: str) -> str:
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"""将合约代码转换为TQSDK格式
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Args:
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symbol: 合约代码，如 'CU2603'
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Returns:
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TQSDK格式的合约代码，如 'SHFE.cu2603'
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"""
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# 交易所映射
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exchange_map = {
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'CU': 'SHFE', # 铜 - 上海期货交易所
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'AL': 'SHFE', # 铝 - 上海期货交易所
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'ZN': 'SHFE', # 锌 - 上海期货交易所
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'PB': 'SHFE', # 铅 - 上海期货交易所
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'NI': 'SHFE', # 镍 - 上海期货交易所
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'SN': 'SHFE', # 锡 - 上海期货交易所
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'AU': 'SHFE', # 黄金 - 上海期货交易所
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'AG': 'SHFE', # 白银 - 上海期货交易所
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'RB': 'SHFE', # 螺纹钢 - 上海期货交易所
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'HC': 'SHFE', # 热轧卷板 - 上海期货交易所
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'BU': 'SHFE', # 沥青 - 上海期货交易所
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'RU': 'SHFE', # 橡胶 - 上海期货交易所
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'FU': 'SHFE', # 燃油 - 上海期货交易所
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'SC': 'INE', # 原油 - 上海国际能源交易中心
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'I': 'DCE', # 铁矿石 - 大连商品交易所
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'J': 'DCE', # 焦炭 - 大连商品交易所
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'JM': 'DCE', # 焦煤 - 大连商品交易所
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'A': 'DCE', # 大豆 - 大连商品交易所
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'B': 'DCE', # 豆粕 - 大连商品交易所
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'M': 'DCE', # 豆粕 - 大连商品交易所
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'Y': 'DCE', # 豆油 - 大连商品交易所
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'P': 'DCE', # 棕榈油 - 大连商品交易所
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'C': 'DCE', # 玉米 - 大连商品交易所
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'CS': 'DCE', # 玉米淀粉 - 大连商品交易所
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'L': 'DCE', # 聚乙烯 - 大连商品交易所
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'V': 'DCE', # 聚氯乙烯 - 大连商品交易所
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'PP': 'DCE', # 聚丙烯 - 大连商品交易所
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'TA': 'CZCE', # PTA - 郑州商品交易所
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'CF': 'CZCE', # 棉花 - 郑州商品交易所
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'SR': 'CZCE', # 白糖 - 郑州商品交易所
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'MA': 'CZCE', # 甲醇 - 郑州商品交易所
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'ZC': 'CZCE', # 动力煤 - 郑州商品交易所
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'FG': 'CZCE', # 玻璃 - 郑州商品交易所
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'RM': 'CZCE', # 菜籽粕 - 郑州商品交易所
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'OI': 'CZCE', # 菜籽油 - 郑州商品交易所
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'RS': 'CZCE', # 菜籽 - 郑州商品交易所
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'WH': 'CZCE', # 强麦 - 郑州商品交易所
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'JR': 'CZCE', # 粳稻 - 郑州商品交易所
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'LR': 'CZCE', # 晚籼稻 - 郑州商品交易所
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}
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# 提取品种代码和合约月份
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if len(symbol) >= 4:
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product_code = symbol[:2].upper()
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contract_month = symbol[2:].lower()
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# 获取交易所代码
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exchange = exchange_map.get(product_code, 'SHFE')
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# 构建TQSDK格式的合约代码
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tq_symbol = f"{exchange}.{product_code.lower()}{contract_month}"
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return tq_symbol
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else:
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return symbol
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def get_product_name_cn(self, symbol: str) -> str:
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"""获取合约的中文名称
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Args:
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symbol: 合约代码，如 'CU2603'
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Returns:
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合约的中文名称，如 '铜'
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"""
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# 品种中文名称映射
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product_name_map = {
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'CU': '铜',
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'AL': '铝',
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'ZN': '锌',
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'PB': '铅',
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'NI': '镍',
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'SN': '锡',
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'AU': '黄金',
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'AG': '白银',
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'RB': '螺纹钢',
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'HC': '热轧卷板',
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'BU': '沥青',
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'RU': '橡胶',
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'FU': '燃油',
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'SC': '原油',
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'I': '铁矿石',
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'J': '焦炭',
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'JM': '焦煤',
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'A': '大豆',
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'B': '豆粕',
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'M': '豆粕',
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'Y': '豆油',
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'P': '棕榈油',
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'C': '玉米',
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'CS': '玉米淀粉',
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'L': '聚乙烯',
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'V': '聚氯乙烯',
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'PP': '聚丙烯',
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'TA': 'PTA',
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'CF': '棉花',
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'SR': '白糖',
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'MA': '甲醇',
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'ZC': '动力煤',
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'FG': '玻璃',
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'RM': '菜籽粕',
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'OI': '菜籽油',
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'RS': '菜籽',
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'WH': '强麦',
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'JR': '粳稻',
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'LR': '晚籼稻',
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}
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if len(symbol) >= 2:
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product_code = symbol[:2].upper()
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return product_name_map.get(product_code, product_code)
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else:
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return symbol
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def get_kline_data(self, symbol: str, duration: str, count: int = 200) -> Optional[pd.DataFrame]:
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"""获取K线数据
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Args:
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symbol: 合约代码
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duration: 时间周期，如 '1m', '5m', '15m', '1h', '1d'
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count: 数据数量
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Returns:
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K线数据DataFrame，如果无法获取真实数据则返回None
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"""
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try:
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if TQSDK_AVAILABLE and self.api:
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# 转换合约代码为TQSDK格式
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tq_symbol = self._convert_symbol(symbol)
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print(f"使用TQSDK格式合约代码: {tq_symbol}")
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# 转换时间周期为分钟数
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duration_minutes = self._convert_duration(duration)
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# 使用真实API获取数据
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klines = self.api.get_kline_serial(tq_symbol, duration_minutes, data_length=count)
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# 等待数据准备就绪
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import time
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start_time = time.time()
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timeout = 5 # 5秒超时
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while True:
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if hasattr(klines, 'datetime') and len(klines.datetime) > 0:
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break
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if time.time() - start_time > timeout:
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print("获取K线数据超时")
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return None
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time.sleep(0.1)
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# 转换为DataFrame
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data = {
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'datetime': klines.datetime,
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'open': klines.open,
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'high': klines.high,
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'low': klines.low,
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'close': klines.close,
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'volume': klines.volume,
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'open_interest': klines.open_oi
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}
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df = pd.DataFrame(data)
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df['datetime'] = pd.to_datetime(df['datetime'], unit='ns')
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df.set_index('datetime', inplace=True)
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print(f"成功获取K线数据，数据长度: {len(df)}")
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return df
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else:
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# 不再自动返回模拟数据，返回None
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print(f"无法获取真实数据：{'API未连接' if not self.api else 'TQSDK不可用'}")
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return None
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except Exception as e:
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print(f"获取K线数据失败：{e}")
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# 不再自动返回模拟数据，返回None
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return None
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def get_tick_data(self, symbol: str, count: int = 1000) -> Optional[pd.DataFrame]:
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"""获取Tick数据"""
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try:
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if TQSDK_AVAILABLE and self.api:
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# 使用真实API获取数据
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ticks = self.api.get_tick_serial(symbol, data_length=count)
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self.api.wait_update()
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# 转换为DataFrame
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data = {
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'datetime': ticks.datetime,
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'last_price': ticks.last_price,
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'volume': ticks.volume,
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'open_interest': ticks.open_interest,
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'bid_price1': ticks.bid_price1,
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'bid_volume1': ticks.bid_volume1,
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'ask_price1': ticks.ask_price1,
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'ask_volume1': ticks.ask_volume1
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}
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df = pd.DataFrame(data)
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df['datetime'] = pd.to_datetime(df['datetime'], unit='ns')
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df.set_index('datetime', inplace=True)
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return df
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else:
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# 返回模拟数据
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return self._get_mock_tick_data(symbol, count)
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except Exception as e:
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print(f"获取Tick数据失败：{e}")
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return self._get_mock_tick_data(symbol, count)
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def get_contract_info(self, symbol: str) -> Optional[Dict]:
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"""获取合约信息"""
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try:
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if TQSDK_AVAILABLE and self.api:
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# 使用真实API获取数据
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quote = self.api.get_quote(symbol)
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self.api.wait_update()
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return {
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'symbol': symbol,
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'name': quote.instrument_name,
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'exchange': quote.exchange_id,
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'product': quote.product_id,
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'price_tick': quote.price_tick,
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'volume_multiple': quote.volume_multiple,
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'margin_rate': quote.margin_rate,
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'expire_datetime': quote.expire_datetime,
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'create_datetime': quote.create_datetime
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}
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else:
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# 返回模拟数据
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return self._get_mock_contract_info(symbol)
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except Exception as e:
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print(f"获取合约信息失败：{e}")
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return self._get_mock_contract_info(symbol)
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def get_market_data(self, symbols: List[str]) -> Dict[str, Dict]:
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"""批量获取市场数据"""
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market_data = {}
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for symbol in symbols:
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try:
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if TQSDK_AVAILABLE and self.api:
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quote = self.api.get_quote(symbol)
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self.api.wait_update()
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market_data[symbol] = {
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'latest_price': quote.last_price,
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'open': quote.open,
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'high': quote.high,
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'low': quote.low,
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'pre_close': quote.pre_close,
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'volume': quote.volume,
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'open_interest': quote.open_interest,
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'bid_price1': quote.bid_price1,
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'ask_price1': quote.ask_price1
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}
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else:
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# 模拟数据
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market_data[symbol] = self._get_mock_market_data(symbol)
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except Exception as e:
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print(f"获取{symbol}市场数据失败：{e}")
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market_data[symbol] = self._get_mock_market_data(symbol)
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return market_data
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def _get_mock_kline_data(self, symbol: str, duration: str, count: int) -> pd.DataFrame:
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"""获取模拟K线数据"""
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# 生成时间序列
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end_time = pd.Timestamp.now()
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if duration == '1m':
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freq = '1T'
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elif duration == '5m':
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freq = '5T'
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elif duration == '15m':
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freq = '15T'
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elif duration == '1h':
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freq = '1H'
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elif duration == '1d':
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freq = '1D'
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else:
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freq = '1H'
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datetime_index = pd.date_range(end=end_time, periods=count, freq=freq)
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# 生成随机价格数据
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base_price = 3500
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price_changes = np.random.normal(0, 5, count)
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prices = base_price + np.cumsum(price_changes)
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# 生成其他数据
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opens = prices * (1 + np.random.normal(0, 0.001, count))
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highs = np.maximum(prices, opens) * (1 + np.random.normal(0, 0.002, count))
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lows = np.minimum(prices, opens) * (1 - np.random.normal(0, 0.002, count))
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volumes = np.random.randint(1000, 10000, count)
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open_interests = np.random.randint(10000, 100000, count)
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# 创建DataFrame
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df = pd.DataFrame({
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'open': opens,
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'high': highs,
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|
'low': lows,
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|
'close': prices,
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|
|
'volume': volumes,
|
|
|
'open_interest': open_interests
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|
|
}, index=datetime_index)
|
|
|
|
|
|
return df
|
|
|
|
|
|
def _get_mock_tick_data(self, symbol: str, count: int) -> pd.DataFrame:
|
|
|
"""获取模拟Tick数据"""
|
|
|
# 生成时间序列
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|
|
end_time = pd.Timestamp.now()
|
|
|
datetime_index = pd.date_range(end=end_time, periods=count, freq='1S')
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|
|
|
|
|
# 生成随机价格数据
|
|
|
base_price = 3500
|
|
|
price_changes = np.random.normal(0, 0.5, count)
|
|
|
last_prices = base_price + np.cumsum(price_changes)
|
|
|
|
|
|
# 生成其他数据
|
|
|
volumes = np.random.randint(10, 100, count)
|
|
|
open_interests = np.random.randint(10000, 100000, count)
|
|
|
bid_prices = last_prices * (1 - np.random.normal(0, 0.0005, count))
|
|
|
ask_prices = last_prices * (1 + np.random.normal(0, 0.0005, count))
|
|
|
bid_volumes = np.random.randint(10, 50, count)
|
|
|
ask_volumes = np.random.randint(10, 50, count)
|
|
|
|
|
|
# 创建DataFrame
|
|
|
df = pd.DataFrame({
|
|
|
'last_price': last_prices,
|
|
|
'volume': volumes,
|
|
|
'open_interest': open_interests,
|
|
|
'bid_price1': bid_prices,
|
|
|
'bid_volume1': bid_volumes,
|
|
|
'ask_price1': ask_prices,
|
|
|
'ask_volume1': ask_volumes
|
|
|
}, index=datetime_index)
|
|
|
|
|
|
return df
|
|
|
|
|
|
def _get_mock_contract_info(self, symbol: str) -> Dict:
|
|
|
"""获取模拟合约信息"""
|
|
|
return {
|
|
|
'symbol': symbol,
|
|
|
'name': symbol,
|
|
|
'exchange': 'SHFE',
|
|
|
'product': symbol[:2],
|
|
|
'price_tick': 1,
|
|
|
'volume_multiple': 10,
|
|
|
'margin_rate': 0.1,
|
|
|
'expire_datetime': int(time.time() * 1e9) + 90 * 24 * 3600 * 1e9,
|
|
|
'create_datetime': int(time.time() * 1e9) - 180 * 24 * 3600 * 1e9
|
|
|
}
|
|
|
|
|
|
def _get_mock_market_data(self, symbol: str) -> Dict:
|
|
|
"""获取模拟市场数据"""
|
|
|
base_price = 3500
|
|
|
return {
|
|
|
'latest_price': base_price + np.random.normal(0, 10),
|
|
|
'open': base_price,
|
|
|
'high': base_price + 20,
|
|
|
'low': base_price - 20,
|
|
|
'pre_close': base_price,
|
|
|
'volume': np.random.randint(10000, 100000),
|
|
|
'open_interest': np.random.randint(100000, 1000000),
|
|
|
'bid_price1': base_price - 1,
|
|
|
'ask_price1': base_price + 1
|
|
|
}
|
|
|
|
|
|
def get_all_symbols(self) -> List[str]:
|
|
|
"""获取所有品种列表
|
|
|
|
|
|
Returns:
|
|
|
List[str]: 所有品种的合约代码列表
|
|
|
"""
|
|
|
try:
|
|
|
if TQSDK_AVAILABLE and self.api:
|
|
|
# TQSDK 没有 get_instrument_info 方法，我们使用模拟数据
|
|
|
print("TQSDK 不支持获取所有品种列表，使用模拟数据")
|
|
|
return self._get_mock_all_symbols()
|
|
|
else:
|
|
|
# 返回模拟数据
|
|
|
print("使用模拟品种列表")
|
|
|
return self._get_mock_all_symbols()
|
|
|
except Exception as e:
|
|
|
print(f"获取所有品种列表失败：{e}")
|
|
|
return self._get_mock_all_symbols()
|
|
|
|
|
|
def _get_mock_all_symbols(self) -> List[str]:
|
|
|
"""获取模拟品种列表"""
|
|
|
# 返回常用的期货品种
|
|
|
return [
|
|
|
"CU2603", "AL2603", "ZN2603", "PB2603", "NI2603", "SN2603",
|
|
|
"AU2603", "AG2603", "RB2603", "HC2603", "BU2603", "RU2603",
|
|
|
"SC2603", "I2603", "J2603", "JM2603", "A2603", "M2603",
|
|
|
"Y2603", "P2603", "C2603", "CS2603", "L2603", "V2603",
|
|
|
"PP2603", "TA2603", "CF2603", "SR2603", "MA2603", "FG2603"
|
|
|
]
|
|
|
|
|
|
|
|
|
# 导入numpy
|
|
|
import numpy as np
|
