fix some issue

.gitignore

@@ -4,3 +4,4 @@
 core/db/__pycache__/db_market_data.cpython-312.pyc
 core/biz/__pycache__/metrics_calculation.cpython-312.pyc
 core/biz/__pycache__/market_data_monitor.cpython-312.pyc
+core/db/__pycache__/db_market_data.cpython-312.pyc

core/biz/metrics_calculation.py

@@ -102,6 +102,7 @@ class MetricsCalculation:
         KDJ_K < 30, KDJ_D < 30, KDJ_J < 20: 超卖
         否则为"徘徊"
         """
+        logging.info("设置KDJ形态")
         # 初始化kdj_pattern列
         df["kdj_pattern"] = "徘徊"
 
@@ -150,6 +151,7 @@ class MetricsCalculation:
 
         使用20个周期的滚动窗口计算相对统计特征，避免绝对阈值过于严格的问题
         """
+        logging.info("设置均线多空和发散")
         data["ma_long_short"] = "震荡"
         data["ma_divergence"] = "未知"
 
@@ -464,6 +466,7 @@ class MetricsCalculation:
         超卖：价格接近下轨，且KDJ超卖
         震荡：其他情况
         """
+        logging.info("设置BOLL形态")
         # 初始化boll_pattern列
         df["boll_pattern"] = "震荡"
 
@@ -539,6 +542,7 @@ class MetricsCalculation:
         - 长：K线实体或影线较长
         - 超长：K线实体和影线都很长
         """
+        logging.info("设置K线长度")
         # 检查必要的列是否存在
         required_columns = ["close", "open", "high", "low"]
         missing_columns = [col for col in required_columns if col not in df.columns]
@@ -645,6 +649,7 @@ class MetricsCalculation:
         - 超大实体：实体占比70%-90%
         - 光头光脚：实体占比>90%（非一字情况）
         """
+        logging.info("设置K线形状")
         # 检查必要的列是否存在
         required_columns = ["close", "open", "high", "low"]
         missing_columns = [col for col in required_columns if col not in df.columns]
@@ -840,6 +845,8 @@ class MetricsCalculation:
             "avg_price_range",
             "std_price_range",
             "price_range_zscore",
+            "price_range_ratio_p75",
+            "price_range_zscore_p75",
         ]
         df.drop(columns=temp_columns, inplace=True)
 

core/db/db_market_data.py

@@ -478,7 +478,7 @@ class DBMarketData:
         :param start: 开始时间
         :param end: 结束时间
         """
-        if start is None or end is None:
+        if start is None and end is None:
             sql = """
                 SELECT * FROM crypto_market_data
                 WHERE symbol = :symbol AND bar = :bar

market_data_main.py

@@ -88,20 +88,21 @@ class MarketDataMain:
             logging.error(f"开始时间格式错误: {start}")
             return None
 
-        # 如果bar为5m, 15m:
+        # 如果bar为5m, 15m, 30m:
         # end_time_ts与start_time_ts相差超过1天，则按照1天为单位
         # 如果bar为1H, 4H,
         # end_time_ts与start_time_ts相差超过5天，则按照5天为单位
         # 如果bar为1D, 则end_time_ts与start_time_ts相差超过10天，则按照10天为单位
         # 获取数据，直到end_time_ts
         threshold = None
-        if bar in ["5m", "15m"]:
+        if bar in ["5m", "15m", "30m"]:
             threshold = 86400000
         elif bar in ["1H", "4H"]:
             threshold = 432000000
         elif bar == "1D":
             threshold = 864000000
 
+        get_data = False
         min_start_time_ts = start_time_ts
         while start_time_ts < end_time_ts:
             current_start_time_ts = end_time_ts - threshold
@@ -212,10 +213,11 @@ class MarketDataMain:
                 current_min_start_time_ts = data["timestamp"].min()
                 if current_min_start_time_ts < min_start_time_ts:
                     min_start_time_ts = current_min_start_time_ts
+                get_data = True
             if current_start_time_ts == start_time_ts:
                 break
             end_time_ts = current_start_time_ts
-        if min_start_time_ts is not None:
+        if min_start_time_ts is not None and get_data:
             # 补充技术指标数据
             # 获得min_start_time_ts之前30条数据
             logging.info(f"开始补充技术指标数据: {symbol} {bar}")
@@ -223,7 +225,7 @@ class MarketDataMain:
                 symbol, bar, min_start_time_ts, 30
             )
             if before_data is not None and len(before_data) > 0:
-                earliest_timestamp = before_data[0]["timestamp"]
+                earliest_timestamp = before_data[-1]["timestamp"]
             else:
                 earliest_timestamp = min_start_time_ts
             handle_data = self.db_market_data.query_market_data_by_symbol_bar(