Refactor and translate comments and docstrings in utility modules to English for better clarity and maintainability. Update Gunicorn and application startup messages for consistency in language. Enhance documentation with English translations for better accessibility.

backend_api_python/app/routes/indicator.py

@@ -210,7 +210,7 @@ def save_indicator():
 
         now = _now_ts()  # For BIGINT fields (createtime, updatetime)
 
-        # 检查用户是否是管理员（管理员发布的指标自动通过审核）
+        # Check whether the user is an administrator (indicators published by the administrator automatically pass the review)
         user_role = getattr(g, 'user_role', 'user')
         is_admin = user_role == 'admin'
         
@@ -222,7 +222,7 @@ def save_indicator():
             except Exception:
                 pass
             if indicator_id and indicator_id > 0:
-                # 检查是否从未发布改为发布，需要设置审核状态
+                # Check whether the change from unpublished to published requires setting the review status
                 if publish_to_community:
                     cur.execute(
                         "SELECT publish_to_community, review_status FROM qd_indicator_codes WHERE id = ? AND user_id = ?",
@@ -230,8 +230,8 @@ def save_indicator():
                     )
                     existing = cur.fetchone()
                     was_published = existing and existing.get('publish_to_community')
-                    # 如果之前未发布，现在发布，设置审核状态
-                    # 管理员发布的直接通过，普通用户需要待审核
+                    # If it has not been published before, publish it now and set the review status
+                    # Posted by the administrator, it passes directly, and ordinary users need to wait for review.
                     new_review_status = 'approved' if is_admin else 'pending'
                     if not was_published:
                         cur.execute(
@@ -248,7 +248,7 @@ def save_indicator():
                              new_review_status, user_id if is_admin else None, now, indicator_id, user_id),
                         )
                     else:
-                        # 已发布过的更新，保持原审核状态
+                        # Updates that have been released will remain in their original review status.
                         cur.execute(
                             """
                             UPDATE qd_indicator_codes
@@ -261,7 +261,7 @@ def save_indicator():
                             (name, code, description, publish_to_community, pricing_type, price, preview_image, vip_free, now, indicator_id, user_id),
                         )
                 else:
-                    # 取消发布，清除审核状态
+                    # Unpublish and clear review status
                     cur.execute(
                         """
                         UPDATE qd_indicator_codes
@@ -275,7 +275,7 @@ def save_indicator():
                         (name, code, description, publish_to_community, pricing_type, price, preview_image, now, indicator_id, user_id),
                     )
             else:
-                # 新建指标 - 管理员发布的直接通过，普通用户需要待审核
+                # New indicators - those released by administrators are passed directly, ordinary users need to wait for review
                 review_status = None
                 if publish_to_community:
                     review_status = 'approved' if is_admin else 'pending'
@@ -329,12 +329,12 @@ def delete_indicator():
 @login_required
 def get_indicator_params():
     """
-    获取指标的参数声明
+    Get parameter declaration of indicator
     
-    用于前端在策略创建时显示可配置的参数表单。
+    Used by the front end to display a configurable parameter form when creating a policy.
     
     Query params:
-        indicator_id: 指标ID
+        indicator_id: indicator ID
         
     Returns:
         params: [
@@ -342,7 +342,7 @@ def get_indicator_params():
                 "name": "ma_fast",
                 "type": "int",
                 "default": 5,
-                "description": "短期均线周期"
+                "description": "Short-term moving average cycle"
             },
             ...
         ]
@@ -541,7 +541,7 @@ def ai_generate():
     if not prompt:
         # Keep SSE contract (match PHP behavior) so frontend doesn't look "stuck".
         def _err_stream():
-            yield "data: " + json.dumps({"error": "提示词不能为空"}, ensure_ascii=False) + "\n\n"
+            yield "data: " + json.dumps({"error": "The prompt word cannot be empty"}, ensure_ascii=False) + "\n\n"
             yield "data: [DONE]\n\n"
 
         return Response(
@@ -740,22 +740,22 @@ IMPORTANT: Output Python code directly, without explanations, without descriptio
 @login_required
 def call_indicator():
     """
-    调用另一个指标（供前端 Pyodide 环境使用）
+    Call another indicator (for use by the front-end Pyodide environment)
     
     POST /api/indicator/callIndicator
     Body: {
-        "indicatorRef": int | str,  # 指标ID或名称
-        "klineData": List[Dict],      # K线数据
-        "params": Dict,              # 传递给被调用指标的参数（可选）
-        "currentIndicatorId": int     # 当前指标ID（用于循环依赖检测，可选）
+        "indicatorRef": int | str, # indicator ID or name
+        "klineData": List[Dict], # K-line data
+        "params": Dict, # Parameters passed to the called indicator (optional)
+        "currentIndicatorId": int # Current indicator ID (used for circular dependency detection, optional)
     }
     
     Returns:
         {
             "code": 1,
             "data": {
-                "df": List[Dict],    # 执行后的DataFrame（转换为JSON）
-                "columns": List[str]  # DataFrame的列名
+                "df": List[Dict], # DataFrame after execution (converted to JSON)
+                "columns": List[str] # DataFrame column name
             }
         }
     """
@@ -780,32 +780,32 @@ def call_indicator():
                 "data": None
             }), 400
         
-        # 获取用户ID
+        # Get user ID
         user_id = g.user_id
         
-        # 创建 IndicatorCaller
+        # Create IndicatorCaller
         indicator_caller = IndicatorCaller(user_id, current_indicator_id)
         
-        # 将前端传入的K线数据转换为DataFrame
+        # Convert the K-line data passed in from the front end into a DataFrame
         df = pd.DataFrame(kline_data)
         
-        # 确保必要的列存在
+        # Make sure necessary columns exist
         required_columns = ['open', 'high', 'low', 'close', 'volume']
         for col in required_columns:
             if col not in df.columns:
                 df[col] = 0.0
         
-        # 转换数据类型
+        # Convert data type
         df['open'] = df['open'].astype('float64')
         df['high'] = df['high'].astype('float64')
         df['low'] = df['low'].astype('float64')
         df['close'] = df['close'].astype('float64')
         df['volume'] = df['volume'].astype('float64')
         
-        # 调用指标
+        # call indicator
         result_df = indicator_caller.call_indicator(indicator_ref, df, params)
         
-        # 将DataFrame转换为JSON格式（前端可以使用的格式）
+        # Convert the DataFrame to JSON format (a format that the front end can use)
         result_dict = result_df.to_dict(orient='records')
         
         return jsonify({