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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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from qihuo_analyzer.data.api_adapters import DataAdapterFactory
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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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# 使用适配器工厂创建数据适配器
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self.adapter = DataAdapterFactory.create_adapter()
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self.api_connected = False
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def connect(self) -> bool:
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"""连接API"""
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try:
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# 使用适配器的connect方法
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success = self.adapter.connect()
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self.api_connected = success
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return success
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except Exception as e:
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print(f"API连接失败：{e}")
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self.api_connected = False
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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_connected:
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try:
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# 使用适配器的disconnect方法
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self.adapter.disconnect()
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self.api_connected = False
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except:
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pass
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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模拟数据
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"""
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try:
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# 使用适配器的get_kline_data方法
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result = self.adapter.get_kline_data(symbol, duration, count)
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if result is None:
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# 如果适配器返回None，使用模拟数据
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print("适配器返回None，使用模拟K线数据")
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return self._get_mock_kline_data(symbol, duration, count)
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return result
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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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return self._get_mock_kline_data(symbol, duration, count)
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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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# 使用适配器的get_tick_data方法
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result = self.adapter.get_tick_data(symbol, count)
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if result is None:
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# 如果适配器返回None，使用模拟数据
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return self._get_mock_tick_data(symbol, count)
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return result
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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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# 使用适配器的get_contract_info方法
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result = self.adapter.get_contract_info(symbol)
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if result is None:
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# 如果适配器返回None，使用模拟数据
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return self._get_mock_contract_info(symbol)
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return result
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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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try:
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# 使用适配器的get_market_data方法
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result = self.adapter.get_market_data(symbols)
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if result:
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return result
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else:
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# 如果适配器返回空，使用模拟数据
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market_data = {}
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for symbol in symbols:
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market_data[symbol] = self._get_mock_market_data(symbol)
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return market_data
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except Exception as e:
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print(f"获取市场数据失败：{e}")
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# 使用模拟数据
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market_data = {}
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for symbol in symbols:
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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 == '30m':
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freq = '30T'
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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,
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'open_interest': open_interests
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}, index=datetime_index)
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return df
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def _get_mock_tick_data(self, symbol: str, count: int) -> pd.DataFrame:
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"""获取模拟Tick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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datetime_index = pd.date_range(end=end_time, periods=count, freq='1S')
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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, 0.5, count)
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last_prices = base_price + np.cumsum(price_changes)
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# 生成其他数据
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volumes = np.random.randint(10, 100, count)
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open_interests = np.random.randint(10000, 100000, count)
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bid_prices = last_prices * (1 - np.random.normal(0, 0.0005, count))
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ask_prices = last_prices * (1 + np.random.normal(0, 0.0005, count))
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bid_volumes = np.random.randint(10, 50, count)
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ask_volumes = np.random.randint(10, 50, count)
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# 创建DataFrame
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df = pd.DataFrame({
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'last_price': last_prices,
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'volume': volumes,
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'open_interest': open_interests,
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'bid_price1': bid_prices,
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'bid_volume1': bid_volumes,
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'ask_price1': ask_prices,
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'ask_volume1': ask_volumes
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}, index=datetime_index)
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return df
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def _get_mock_contract_info(self, symbol: str) -> Dict:
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"""获取模拟合约信息"""
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return {
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'symbol': symbol,
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'name': symbol,
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'exchange': 'SHFE',
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'product': symbol[:2],
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'price_tick': 1,
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'volume_multiple': 10,
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'margin_rate': 0.1,
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'expire_datetime': int(time.time() * 1e9) + 90 * 24 * 3600 * 1e9,
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'create_datetime': int(time.time() * 1e9) - 180 * 24 * 3600 * 1e9
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}
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def _get_mock_market_data(self, symbol: str) -> Dict:
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"""获取模拟市场数据"""
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base_price = 3500
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return {
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'latest_price': base_price + np.random.normal(0, 10),
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'open': base_price,
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'high': base_price + 20,
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'low': base_price - 20,
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'pre_close': base_price,
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'volume': np.random.randint(10000, 100000),
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'open_interest': np.random.randint(100000, 1000000),
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'bid_price1': base_price - 1,
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'ask_price1': base_price + 1
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}
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def get_all_symbols(self) -> List[str]:
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"""获取所有品种列表
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Returns:
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List[str]: 所有品种的合约代码列表
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"""
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try:
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# 使用适配器的get_all_symbols方法
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result = self.adapter.get_all_symbols()
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if result:
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return result
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else:
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# 如果适配器返回空，使用本地枚举数据
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print("使用本地枚举品种列表")
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symbols_by_exchange = self.get_all_symbols_by_exchange()
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symbols = []
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for exchange, products in symbols_by_exchange.items():
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for product, product_contracts in products.items():
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# 使用每个品种的第一个合约作为代表
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if product_contracts:
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symbols.append(product_contracts[0])
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return symbols
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except Exception as e:
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print(f"获取所有品种列表失败：{e}")
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return self._get_mock_all_symbols()
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def _get_mock_all_symbols(self) -> List[str]:
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"""获取模拟品种列表"""
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# 返回用户指定的所有期货品种
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return [
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"AU2603", "AG2603", "CU2603", "NI2603", "SN2603", "FG2603",
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"LY2603", "SA2603", "JM2603", "RB2603", "ALO2603", "MA2603",
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"V2603", "FU2603", "SC2603", "AL2603", "P2603", "LI2603",
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"SI2603", "RU2603", "BR2603", "ZN2603", "NR2603", "SP2603",
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"IM2603", "IC2603", "LU2603", "IH2603"
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]
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def get_all_symbols_by_exchange(self) -> Dict[str, Dict[str, List[str]]]:
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"""获取所有品种列表，按交易所-合约划分
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Returns:
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Dict[str, Dict[str, List[str]]]: 按交易所-合约划分的品种列表
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"""
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# 本地枚举数据，按交易所-合约划分
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symbols_by_exchange = {
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"SHFE": { # 上海期货交易所
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"AU": ["AU2603", "AU2604", "AU2605", "AU2606", "AU2607", "AU2608", "AU2609"], # 黄金
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"AG": ["AG2603", "AG2604", "AG2605", "AG2606", "AG2607", "AG2608", "AG2609"], # 白银
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"CU": ["CU2603", "CU2604", "CU2605", "CU2606", "CU2607", "CU2608", "CU2609"]#, # 铜
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# "NI": ["NI2603", "NI2604", "NI2605", "NI2606", "NI2607", "NI2608", "NI2609"], # 镍
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# "SN": ["SN2603", "SN2604", "SN2605", "SN2606", "SN2607", "SN2608", "SN2609"], # 锡
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# "FG": ["FG2603", "FG2604", "FG2605", "FG2606", "FG2607", "FG2608", "FG2609"], # 玻璃
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# "RB": ["RB2603", "RB2604", "RB2605", "RB2606", "RB2607", "RB2608", "RB2609"], # 螺纹钢
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# "AL": ["AL2603", "AL2604", "AL2605", "AL2606", "AL2607", "AL2608", "AL2609"], # 铝
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# "ZN": ["ZN2603", "ZN2604", "ZN2605", "ZN2606", "ZN2607", "ZN2608", "ZN2609"], # 锌
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# "RU": ["RU2603", "RU2604", "RU2605", "RU2606", "RU2607", "RU2608", "RU2609"], # 橡胶
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# "NR": ["NR2603", "NR2604", "NR2605", "NR2606", "NR2607", "NR2608", "NR2609"], # 20号胶
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# "FU": ["FU2603", "FU2604", "FU2605", "FU2606", "FU2607", "FU2608", "FU2609"], # 燃油
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# "SC": ["SC2603", "SC2604", "SC2605", "SC2606", "SC2607", "SC2608", "SC2609"], # 原油
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# "LU": ["LU2603", "LU2604", "LU2605", "LU2606", "LU2607", "LU2608", "LU2609"], # 低硫燃油
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# "ALO": ["ALO2603", "ALO2604", "ALO2605", "ALO2606", "ALO2607", "ALO2608", "ALO2609"], # 氧化铝
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# "LI": ["LI2603", "LI2604", "LI2605", "LI2606", "LI2607", "LI2608", "LI2609"], # 碳酸锂
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# "SI": ["SI2603", "SI2604", "SI2605", "SI2606", "SI2607", "SI2608", "SI2609"] # 工业硅
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}#,
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# "INE": { # 上海国际能源交易中心
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# "SC": ["SC2603", "SC2604", "SC2605", "SC2606", "SC2607", "SC2608", "SC2609"], # 原油
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# "LU": ["LU2603", "LU2604", "LU2605", "LU2606", "LU2607", "LU2608", "LU2609"] # 低硫燃油
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# },
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# "DCE": { # 大连商品交易所
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# "JM": ["JM2603", "JM2604", "JM2605", "JM2606", "JM2607", "JM2608", "JM2609"], # 焦煤
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# "P": ["P2603", "P2604", "P2605", "P2606", "P2607", "P2608", "P2609"], # 棕榈油
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# "V": ["V2603", "V2604", "V2605", "V2606", "V2607", "V2608", "V2609"], # PVC
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# "MA": ["MA2603", "MA2604", "MA2605", "MA2606", "MA2607", "MA2608", "MA2609"], # 甲醇
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# "BR": ["BR2603", "BR2604", "BR2605", "BR2606", "BR2607", "BR2608", "BR2609"] # 合成橡胶
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# },
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# "CZCE": { # 郑州商品交易所
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# "FG": ["FG2603", "FG2604", "FG2605", "FG2606", "FG2607", "FG2608", "FG2609"], # 玻璃
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# "MA": ["MA2603", "MA2604", "MA2605", "MA2606", "MA2607", "MA2608", "MA2609"], # 甲醇
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# "V": ["V2603", "V2604", "V2605", "V2606", "V2607", "V2608", "V2609"], # PVC
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# "SA": ["SA2603", "SA2604", "SA2605", "SA2606", "SA2607", "SA2608", "SA2609"], # 纯碱
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# "LY": ["LY2603", "LY2604", "LY2605", "LY2606", "LY2607", "LY2608", "LY2609"] # 烧碱
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# },
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|
|
# "CFFEX": { # 中国金融期货交易所
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# "IH": ["IH2603", "IH2604", "IH2605", "IH2606", "IH2607", "IH2608", "IH2609"], # 上证50
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# "IC": ["IC2603", "IC2604", "IC2605", "IC2606", "IC2607", "IC2608", "IC2609"], # 中证500
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|
# "IM": ["IM2603", "IM2604", "IM2605", "IM2606", "IM2607", "IM2608", "IM2609"] # 中证1000
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|
# },
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|
|
# "GEM": { # 广州期货交易所
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|
# "SI": ["SI2603", "SI2604", "SI2605", "SI2606", "SI2607", "SI2608", "SI2609"], # 工业硅
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# "SP": ["SP2603", "SP2604", "SP2605", "SP2606", "SP2607", "SP2608", "SP2609"] # 多晶硅
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|
|
# }
|
|
|
}
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|
|
|
|
|
return symbols_by_exchange
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|
|
|
|
|
def get_contract_months(self, product_code: str) -> List[str]:
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|
|
"""获取合约的所有月份
|
|
|
|
|
|
Args:
|
|
|
product_code: 品种代码，如 "CU"
|
|
|
|
|
|
Returns:
|
|
|
List[str]: 该品种的所有合约月份列表
|
|
|
"""
|
|
|
# 本地枚举的合约月份
|
|
|
contract_months = ["2603", "2604", "2605", "2606", "2607", "2608", "2609"]
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|
|
|
|
|
# 生成完整的合约代码
|
|
|
return [f"{product_code}{month}" for month in contract_months]
|
|
|
|
|
|
def get_contracts(self, exchange: str = '', symbol: str = '') -> List[Dict]:
|
|
|
"""获取合约列表
|
|
|
|
|
|
Args:
|
|
|
exchange: 交易所代码，如 'SHFE'
|
|
|
symbol: 品种代码，如 'CU'
|
|
|
|
|
|
Returns:
|
|
|
List[Dict]: 合约列表，每个合约包含代码、名称等信息
|
|
|
"""
|
|
|
try:
|
|
|
# 获取所有品种按交易所划分
|
|
|
symbols_by_exchange = self.get_all_symbols_by_exchange()
|
|
|
|
|
|
contracts = []
|
|
|
|
|
|
# 遍历交易所
|
|
|
for exch, products in symbols_by_exchange.items():
|
|
|
# 如果指定了交易所，只处理该交易所
|
|
|
if exchange and exch != exchange:
|
|
|
continue
|
|
|
|
|
|
# 遍历品种
|
|
|
for product, product_contracts in products.items():
|
|
|
# 如果指定了品种，只处理该品种
|
|
|
if symbol and product != symbol:
|
|
|
continue
|
|
|
|
|
|
# 获取品种中文名称
|
|
|
product_name = self.get_product_name_cn(product)
|
|
|
|
|
|
# 遍历合约
|
|
|
for contract in product_contracts:
|
|
|
contracts.append({
|
|
|
'symbol': contract,
|
|
|
'product': product,
|
|
|
'product_name': product_name,
|
|
|
'exchange': exch,
|
|
|
'month': contract[-4:]
|
|
|
})
|
|
|
|
|
|
return contracts
|
|
|
except Exception as e:
|
|
|
print(f"获取合约列表失败：{e}")
|
|
|
# 返回模拟数据
|
|
|
return [
|
|
|
{'symbol': 'CU2603', 'product': 'CU', 'product_name': '铜', 'exchange': 'SHFE', 'month': '2603'},
|
|
|
{'symbol': 'AL2603', 'product': 'AL', 'product_name': '铝', 'exchange': 'SHFE', 'month': '2603'},
|
|
|
{'symbol': 'ZN2603', 'product': 'ZN', 'product_name': '锌', 'exchange': 'SHFE', 'month': '2603'}
|
|
|
]
|
|
|
|
|
|
|
|
|
# 导入numpy
|
|
|
import numpy as np
|
