Remove unused process_data() function

src/leadlag/main.py

@@ -505,58 +505,6 @@ async def trigger_strategy_update():
         await trading_strategy.do_strategy(market_data)
 
 
-def process_data():
-    """
-    处理从两个交易所获取的数据，并将匹配的交易对数据保存到数据库
-    现在使用order_book_cache作为Lighter数据源，binance_data_cache作为Binance数据源
-    """
-    if not order_book_cache or not binance_data_cache['latest_prices']:
-        logger.warning("缺少必要的数据，跳过本次处理")
-        return 0
-    
-    # 准备批量写入的数据
-    batch_data = []
-    matching_count = 0
-    
-    # 遍历market_id_to_market_info映射，查找匹配的交易对
-    for market_id, market_info in market_id_to_market_info.items():
-        # 检查Lighter数据是否存在
-        if market_id not in order_book_cache:
-            continue
-            
-        # 获取交易对符号
-        symbol = market_info.get('symbol')
-        # 构造Binance交易对名称
-        binance_symbol = f"{symbol}USDT"
-        
-        # 检查Binance数据是否存在
-        if binance_symbol not in binance_data_cache['latest_prices']:
-            continue
-        
-        # 获取数据
-        order_book_instance = order_book_cache[market_id]
-        binance_latest_price = binance_data_cache['latest_prices'][binance_symbol]
-        
-        # 构建数据记录
-        symbol_data = {
-            'symbol': symbol,
-            'binance_price': binance_latest_price,
-            'timestamp': int(time.time() * 1000)  # 毫秒时间戳
-        }
-        
-        batch_data.append(symbol_data)
-        matching_count += 1
-    
-    # # 如果有匹配的数据，批量写入数据库
-    # if batch_data:
-    #     logger.info(f"找到 {matching_count} 个匹配的交易对，准备写入数据库")
-    #     #write_batch_to_questdb(batch_data)
-    # else:
-    #     logger.warning("没有找到匹配的交易对数据")
-    
-    return matching_count
-
-
 async def main():
     """运行数据收集循环的主函数"""
     global trading_strategy