Refactor code for improved readability and consistency

- Cleaned up whitespace and formatting in various files including http.py, language.py, logger.py, safe_exec.py, and SQL migration scripts.
- Consolidated import statements and removed unnecessary blank lines.
- Updated logging configuration for better clarity.
- Enhanced the safe execution code with improved error handling and logging.
- Removed commented-out code and unnecessary variables in backfill_zero_trades.py and other scripts.
- Added a pyproject.toml for Ruff and Vulture configuration.
- Introduced requirements-dev.txt for development dependencies.
- Removed commented-out stock entries in init.sql for cleaner migration scripts.

docs/examples/cross_sectional_momentum_rsi.py

@@ -3,17 +3,17 @@
 # Cross-Sectional Strategy Indicator Example
 # Momentum + RSI Composite Score
 # ============================================================
-# 
+#
 # 使用方法:
 # 1. 在交易助手中创建截面策略
 # 2. 选择此指标作为策略指标
 # 3. 配置标的列表、持仓大小、做多比例等参数
-# 
+#
 # 评分逻辑:
 # - 动量因子 (20周期): 价格变化率，越高越好
 # - RSI指标 (14周期): 反转RSI值，越低越好（100 - RSI）
 # - 综合评分: 70% 动量 + 30% RSI反转值
-# 
+#
 # ============================================================
 
 # 截面策略指标
@@ -28,11 +28,11 @@ for symbol, df in data.items():
     if len(df) < 20:
         scores[symbol] = 0
         continue
-    
+
     # === 1. 计算动量因子 (20周期) ===
     # 动量 = (当前价格 / 20周期前价格 - 1) * 100
     momentum = (df['close'].iloc[-1] / df['close'].iloc[-20] - 1) * 100
-    
+
     # === 2. 计算RSI指标 (14周期) ===
     def calculate_rsi(prices, period=14):
         """计算RSI指标"""
@@ -42,18 +42,18 @@ for symbol, df in data.items():
         rs = gain / loss
         rsi = 100 - (100 / (1 + rs))
         return rsi.iloc[-1]
-    
+
     rsi_value = calculate_rsi(df['close'], 14)
-    
+
     # === 3. 综合评分 ===
     # 动量越高 = 评分越高
     # RSI越低（超卖）= 评分越高（100 - RSI）
     # 权重: 70% 动量 + 30% RSI反转值
     momentum_score = momentum
     rsi_score = 100 - rsi_value  # 反转RSI（RSI越低，评分越高）
-    
+
     composite_score = momentum_score * 0.7 + rsi_score * 0.3
-    
+
     scores[symbol] = composite_score
 
 # === 可选: 手动指定排序 ===

docs/examples/dual_ma_with_params.py

@@ -2,13 +2,13 @@
 # 双均线策略 (支持外部参数配置)
 # Dual Moving Average Strategy with External Parameters
 # ============================================================
-# 
+#
 # 使用方法:
 # 1. 在交易助手中选择此指标
 # 2. 根据不同币种配置不同参数
 #    - BTC/USDT: sma_short=5, sma_long=10
 #    - ETH/USDT: sma_short=5, sma_long=20
-# 
+#
 # ============================================================
 
 # === 参数声明 (会在前端表单中显示) ===

docs/examples/multi_indicator_composite.py

@@ -2,12 +2,12 @@
 # 多指标组合策略 (均线+RSI+MACD)
 # Multi-Indicator Composite Strategy
 # ============================================================
-# 
+#
 # 使用方法:
 # 1. 可配置均线周期、RSI阈值等参数
 # 2. 买入条件: RSI超卖 + MACD金叉 + 成交量放大
 # 3. 卖出条件: RSI超买 或 MACD死叉
-# 
+#
 # ============================================================
 
 # === 参数声明 ===
@@ -78,7 +78,7 @@ buy = ma_golden | rsi_buy  # 均线金叉 或 RSI超卖
 
 if use_macd:
     buy = buy & (macd > macd_signal)  # 需要MACD向上
-    
+
 if use_volume:
     buy = buy & volume_up  # 需要成交量放大