feat: support indicator alias

backtest/daily_use.py

@@ -13,10 +13,10 @@
 
 def test_stock_bond_ratio():  # 股债性价比回测
 
-    df = get_wind_data(indicator_list=['沪深300PE-TTM', '中债国债到期收益率10y'
+    df = get_wind_data(indicator_list=['沪深300PE:TTM', '中债国债到期收益率10y'
         , '沪深300收盘价'])
 
-    df['股债性价比'] = 1 / df['沪深300PE-TTM'] * 100 - df['中债国债到期收益率10y']
+    df['股债性价比'] = 1 / df['沪深300PE:TTM'] * 100 - df['中债国债到期收益率10y']
 
     def signal_func(factor_series: pd.Series, param: Dict):
         threshold = param.get('threshold')
@@ -61,5 +61,5 @@ def signal_func(factor_series: pd.Series, param: Dict):
     print(ret)
 
 if __name__ == '__main__':
-    # test_stock_bond_ratio()  # 股债性价比回测
+    test_stock_bond_ratio()  # 股债性价比回测
     test_strong_stock_ratio()

backtest/load.py

@@ -502,6 +502,53 @@ def visit_Subscript(self, node):
     return [v.replace('_', ':') for v in variables]
 
 
+def _get_alias_map():
+    '''
+    从数据库中取得指标别名映射表，用于支持用户使用方便的别名
+    '''
+    sql_stat = '''
+    select replace(indicator_name,':', '_') indicator_name, replace(remark,':', '_') remark from (
+    select indicator_name, remark  from edb_desc ed 
+    union 
+    select indicator_name, remark  from wind_desc wd 
+    union
+    select name, remark from indicator_description
+    )
+    where remark is not null
+'''
+    conn = sqlite3.connect(SQLITE_FILE_PATH)
+    df = pd.read_sql(sql_stat, conn)
+    return dict(zip(df['remark'], df['indicator_name']))
+
+
+def _replace_variables_in_expr(expr: str) -> str:
+    expr = expr.replace(':', '_')
+    var_map = _get_alias_map()
+    # 替换表达式中的变量名
+    class CustomVisitor(ast.NodeVisitor):
+        def __init__(self, var_map):
+            self.var_map = var_map
+
+        def visit_Name(self, node):
+            # 如果节点的名称在map中，替换成对应的值
+            if node.id in self.var_map:
+                node.id = self.var_map[node.id]
+            self.generic_visit(node)
+
+    try:
+        # 解析表达式为AST
+        parsed_ast = ast.parse(expr, mode='eval')
+        visitor = CustomVisitor(var_map)
+        visitor.visit(parsed_ast)
+
+        # 将修改后的AST转换回表达式字符串
+        modified_expr = ast.unparse(parsed_ast)  # 需要Python 3.9及以上
+        return modified_expr
+
+    except SyntaxError:
+        raise ValueError(f"无法解析表达式: {expr}")
+
+
 # 所有序列函数的实现
 def ema(series: pd.Series, window: int) -> pd.Series:
     return series.ewm(span=window, adjust=False).mean()
@@ -637,8 +684,8 @@ def visit_Name(self, node):
 
 
 def get_data(indicators: List, start_date: str='20200101'):
-    origin_indicators = [indi for indi in indicators if indi] # 用户看到的带冒号的指标名  不支持 减号 下划线
-    expr_indicators = [indi.replace(':', '_') for indi in indicators if indi]  # 支持 eval的指标名
+    origin_indicators = [_replace_variables_in_expr(indi) for indi in indicators if indi] # 用户看到的带冒号的指标名  不支持 减号 下划线
+    expr_indicators = [_replace_variables_in_expr(indi) for indi in indicators if indi]  # 支持 eval的指标名
     indicators_set = set() # 支持eval的单个指标名
     for indi in expr_indicators:
         if '(' in indi or '-' in indi or '+' in indi: # 若是需要表达式解析的
@@ -650,7 +697,6 @@ def get_data(indicators: List, start_date: str='20200101'):
     for indi in expr_indicators:
         if '(' in indi or '-' in indi or '+' in indi: # 若是需要表达式解析的
             df = calc_complicate_indicator(df, indi)
-    df.columns = [c.replace('_', ':') for c in df.columns]
     return df[origin_indicators]
 
 
@@ -669,8 +715,8 @@ def iReturn(arr, start_date="20050101") -> PDFrame(headings=True, index=True):
 
 @xlo.func
 def iPlot(y_indicators, y2_indicators, start_date="20050101", convert2return=False, title=""):
-    y_indicators = [x for x in y_indicators.flatten().tolist() if x]
-    y2_indicators = [x for x in y2_indicators.flatten().tolist() if x]
+    y_indicators = [_replace_variables_in_expr(x) for x in y_indicators.flatten().tolist() if x]
+    y2_indicators = [_replace_variables_in_expr(x) for x in y2_indicators.flatten().tolist() if x]
     df_data = get_data(y_indicators + y2_indicators, start_date)
     if convert2return:
         df_data = ((df_data.pct_change() + 1).cumprod() - 1) * 100