complete market monitor functions.

core/biz/market_monitor.py

@@ -8,7 +8,13 @@ import logging
 logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
 
 
-def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
+def create_metrics_report(
+    row: pd.Series, 
+    next_bar_row: pd.Series, 
+    btc_bar_row: pd.Series,
+    only_output_huge_volume: bool = False,
+    only_output_rise: bool = False
+):
     """
     创建指标报告
     """
@@ -18,6 +24,7 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
     bar = row["bar"]
     window_size = row["window_size"]
     date_time = row["date_time"]
+    if only_output_huge_volume:
         if huge_volume == 1:
             logging.info(
                 f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 巨量"
@@ -27,6 +34,10 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
                 f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 非巨量，此次不发送相关数据"
             )
             return
+    else:
+        logging.info(
+                f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time}"
+            )
 
     # fill -1 to nan
     row = row.fillna(1)
@@ -41,8 +52,10 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
             f"symbol: {symbol} {bar} window_size: {window_size} date_time: {date_time} 下跌，不发送相关数据"
         )
         return
-
+    if huge_volume == 1:
-    contents.append(f"# 交易巨量报告")
+        contents.append(f"## 交易巨量报告")
+    else:
+        contents.append(f"## 交易量报告")
     contents.append(f"## {symbol} {bar} 滑动窗口: {window_size} 时间: {date_time}")
     contents.append(f"### 价格信息")
     contents.append(f"当前价格: {close}, 开盘价: {open}, 最高价: {high}, 最低价: {low}")
@@ -222,28 +235,83 @@ def create_metrics_report(row: pd.Series, only_output_rise: bool = False):
         if k_shape_value < 1:
             long_short_info["空"].append(f"K线形态: {k_shape}")
 
-    
     if k_up_down == "阳线":
         if is_long and not is_over_buy:
             long_short_info["多"].append(f"量价关系: 非超买且放量上涨")
         if is_short and is_over_sell:
-            long_short_info["多"].append(f"量价关系: 空头态势且超卖，但出现放量上涨，可能反转")
+            long_short_info["多"].append(
+                f"量价关系: 空头态势且超卖，但出现放量上涨，可能反转"
+            )
     if k_up_down == "阴线":
         if is_long and is_over_buy:
             if close_80_high or close_90_high or high_80_high or high_90_high:
-                long_short_info["空"].append(f"量价关系: 多头态势且超买, 目前是价位高点，但出现放量下跌，可能反转")
+                long_short_info["空"].append(
+                    f"量价关系: 多头态势且超买, 目前是价位高点，但出现放量下跌，可能反转"
+                )
         if is_short and not is_over_sell:
             long_short_info["空"].append(f"量价关系: 空头态势且非超卖，出现放量下跌")
 
     contents.append(f"### 技术指标信息")
+    if ma_long_short_value == 1:
+        contents.append(f"均线势头: 震荡")
     long_info_list = long_short_info["多"]
     short_info_list = long_short_info["空"]
-    if len(long_info_list) > 0:
     contents.append(f"#### 多头指标信号")
+    if len(long_info_list) > 0:
         contents.append(f"{"\n".join(long_info_list)}")
-    if len(short_info_list) > 0:
+    else:
+        contents.append(f"无多头指标信号")
+    
     contents.append(f"#### 空头指标信号")
+    if len(short_info_list) > 0:
         contents.append(f"{"\n".join(short_info_list)}")
+    else:
+        contents.append(f"无空头指标信号")
+
+    if next_bar_row is not None:
+        contents.append(f"## {symbol} 与更长周期技术形态对比")
+        contents.extend(get_long_short_over_buy_sell(next_bar_row))
+    if btc_bar_row is not None:
+        contents.append(f"## {symbol} 与BTC相同周期技术形态对比")
+        contents.extend(get_long_short_over_buy_sell(btc_bar_row))
 
     mark_down_text = "\n\n".join(contents)
     return mark_down_text
+
+
+def get_long_short_over_buy_sell(
+    row: pd.Series,
+):
+    result = {}
+    symbol = row["symbol"]
+    bar = row["bar"]
+    ma_long_short = str(row["ma_long_short"])
+    macd_signal = str(row["macd_signal"])
+    macd_divergence = str(row["macd_divergence"])
+    kdj_signal = str(row["kdj_signal"])
+    kdj_pattern = str(row["kdj_pattern"])
+    rsi_signal = str(row["rsi_signal"])
+    boll_signal = str(row["boll_signal"])
+    boll_pattern = str(row["boll_pattern"])
+    contents = []
+    contents.append(f"### {symbol} {bar} 对比形态")
+    if ma_long_short in ["多", "空"]:
+        contents.append(f"均线形态: {ma_long_short}")
+    else:
+        contents.append(f"均线形态: 震荡")
+    if macd_signal in ["金叉", "死叉"]:
+        contents.append(f"MACD信号: {macd_signal}")
+    if macd_divergence in ["顶背离", "底背离"]:
+        contents.append(f"MACD背离: {macd_divergence}")
+    if kdj_signal in ["金叉", "死叉"]:
+        contents.append(f"KDJ信号: {kdj_signal}")
+    if kdj_pattern in ["超超买", "超买", "超超卖", "超卖"]:
+        contents.append(f"KDJ形态: {kdj_pattern}")
+    if rsi_signal in ["超超买", "超买", "超超卖", "超卖"]:
+        contents.append(f"RSI形态: {rsi_signal}")
+    if boll_signal in ["突破下轨", "击穿上轨"]:
+        contents.append(f"BOLL信号: {boll_signal}")
+    if boll_pattern in ["超超买", "超买", "超超卖", "超卖"]:
+        contents.append(f"BOLL形态: {boll_pattern}")
+    return contents
+

market_monitor_main.py

@@ -27,7 +27,7 @@ class MarketMonitorMain:
         self.start_date = MONITOR_CONFIG.get("volume_monitor", {}).get(
             "initial_date", "2025-05-01 00:00:00"
         )
-        self.latest_record_file_path = "./output/latest_record.json"
+        self.latest_record_file_path = "./output/record/latest_record.json"
         self.latest_record = self.get_latest_record()
         self.output_folder = "./output/report/market_monitor/"
         os.makedirs(self.output_folder, exist_ok=True)
@@ -48,6 +48,8 @@ class MarketMonitorMain:
         """
         获取最新记录
         """
+        os.makedirs(os.path.dirname(self.latest_record_file_path), exist_ok=True)
+        try:
             if os.path.exists(self.latest_record_file_path):
                 with open(self.latest_record_file_path, "r", encoding="utf-8") as f:
                     return json.load(f)
@@ -55,6 +57,9 @@ class MarketMonitorMain:
                 with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
                     json.dump({}, f, ensure_ascii=False, indent=4)
                 return {}
+        except Exception as e:
+            logging.error(f"获取最后一次报表生成记录失败: {e}")
+            return {}
 
     def monitor_realtime_market(
         self,
@@ -67,10 +72,14 @@ class MarketMonitorMain:
         监控最新市场数据
         考虑到速度，暂不与数据库交互，直接从api获取数据
         """
+        # 获得当前时间字符串
+        now_datetime = datetime.now()
+        now_datetime_str = now_datetime.strftime("%Y-%m-%d %H:%M:%S")
+        end_time = transform_date_time_to_timestamp(now_datetime_str)
         real_time_data = self.market_data_main.market_data.get_realtime_kline_data(
             symbol=symbol,
             bar=bar,
-            end_time=None,
+            end_time=end_time,
             limit=50,
         )
 
@@ -79,10 +88,14 @@ class MarketMonitorMain:
             return
 
         latest_realtime_timestamp = real_time_data["timestamp"].iloc[-1]
+        latest_realtime_timestamp = int(latest_realtime_timestamp)
         latest_record_timestamp = (
-            self.latest_record.get(symbol, {}).get(bar, {}).get("timestamp", 0)
+            self.latest_record.get(symbol, {}).get(bar, {}).get("timestamp", None)
         )
         latest_reatime_datetime = timestamp_to_datetime(latest_realtime_timestamp)
+        if latest_record_timestamp is not None:
+            latest_record_timestamp = int(latest_record_timestamp)
+            
             latest_record_datetime = timestamp_to_datetime(latest_record_timestamp)
             if (
                 latest_record_timestamp is not None
@@ -92,15 +105,11 @@ class MarketMonitorMain:
                     f"最新市场数据时间戳 {latest_reatime_datetime} 小于等于最新记录时间戳 {latest_record_datetime}， 不进行监控"
                 )
                 return
-        else:
-            self.latest_record[symbol] = {bar: {"timestamp": latest_realtime_timestamp}}
-            with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
-                json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
-
-        
             logging.info(
-            f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间 {latest_record_datetime}"
+            f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间 {latest_record_datetime}")
-        )
+        else:
+            logging.info(
+            f"最新市场数据时间 {latest_reatime_datetime}, 上一次记录时间为空")
 
         real_time_data = self.market_data_main.add_new_columns(real_time_data)
         logging.info(f"开始计算技术指标: {symbol} {bar}")
@@ -111,7 +120,7 @@ class MarketMonitorMain:
             window_size=self.window_size,
             threshold=self.huge_volume_main.threshold,
             check_price=True,
-            only_output_huge_volume=only_output_huge_volume,
+            only_output_huge_volume=False,
             output_excel=False,
         )
         if real_time_data is None or len(real_time_data) == 0:
@@ -119,20 +128,42 @@ class MarketMonitorMain:
                 f"计算大成交量失败: {symbol} {bar} 窗口大小: {self.window_size}"
             )
             return
+        realtime_row = real_time_data.iloc[-1]
 
-        report = create_metrics_report(real_time_data, only_output_rise)
+        if only_output_huge_volume:
+            if realtime_row["huge_volume"] == 1:
+                logging.info(f"监控到巨量: {symbol} {bar} 窗口大小: {self.window_size}")
+            else:
+                logging.info(f"监控到非巨量: {symbol} {bar} 窗口大小: {self.window_size}，退出本次监控")
+                return
+        if only_output_rise:
+            if realtime_row["pct_change"] > 0:
+                logging.info(f"监控到上涨: {symbol} {bar} 窗口大小: {self.window_size}")
+            else:
+                logging.info(f"监控到下跌: {symbol} {bar} 窗口大小: {self.window_size}，退出本次监控")
+                return
+
+        next_bar_row = self.get_other_realtime_data(symbol, bar, end_time, next=True)
+        if 'BTC-USDT' in symbol:
+            btc_bar_row = None
+        else:
+            btc_bar_row = self.get_other_realtime_data('BTC-USDT', bar, end_time, next=False)
+
+        
+        report = create_metrics_report(realtime_row, next_bar_row, btc_bar_row, only_output_huge_volume, only_output_rise)
         text_length = len(report.encode("utf-8"))
+
         logging.info(f"发送报告到企业微信，字节数: {text_length}")
         self.wechat.send_markdown(report)
-        self.latest_record[symbol][bar]["timestamp"] = latest_realtime_timestamp
+
-        with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
-            json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
         # remove punction in latest_reatime_datetime
-        latest_reatime_datetime = re.sub(r"[\:\-\s]", "", latest_reatime_datetime)
+        file_datetime = re.sub(r"[\:\-\s]", "", latest_reatime_datetime)
-        report_file_name = f"{symbol}_{bar}_{self.window_size}_{latest_reatime_datetime}.md"
+        report_file_name = (
+            f"{symbol}_{bar}_{self.window_size}_{file_datetime}.md"
+        )
         report_file_path = os.path.join(self.output_folder, report_file_name)
         with open(report_file_path, "w", encoding="utf-8") as f:
-            f.write(report.replace(":", "_"))
+            f.write(report)
         report_file_byte_size = os.path.getsize(report_file_path)
         report_data = {
             "symbol": symbol,
@@ -143,22 +174,68 @@ class MarketMonitorMain:
             "report": report,
             "report_file_path": report_file_path,
             "report_file_name": report_file_name,
-            "report_file_byte_size": report_file_byte_size
+            "report_file_byte_size": report_file_byte_size,
         }
         report_data = pd.DataFrame([report_data])
         logging.info(f"插入数据到数据库")
         self.db_market_monitor.insert_data_to_mysql(report_data)
+        if self.latest_record.get(symbol, None) is None:
+            self.latest_record[symbol] = {bar: {"timestamp": latest_realtime_timestamp}}
+        else:
+            self.latest_record[symbol][bar]["timestamp"] = latest_realtime_timestamp
+        with open(self.latest_record_file_path, "w", encoding="utf-8") as f:
+            json.dump(self.latest_record, f, ensure_ascii=False, indent=4)
+
+    def get_other_realtime_data(self, symbol: str, bar: str, end_time: int, next: bool = True):
+        """
+        获取下一个长周期实时数据
+        """
+        if next:
+            # 获得bar在self.market_data_main.bars中的索引
+            bar_index = self.market_data_main.bars.index(bar)
+            if bar_index == len(self.market_data_main.bars) - 1:
+                logging.error(f"已经是最后一个bar: {bar}")
+                return None
+            # 获得下一个bar
+            bar = self.market_data_main.bars[bar_index + 1]
+            # 获得下一个bar的实时数据
+        data = self.market_data_main.market_data.get_realtime_kline_data(
+            symbol=symbol, bar=bar, end_time=end_time, limit=50
+        )
+        if data is None or len(data) == 0:
+            logging.error(f"获取实时数据失败: {symbol}, {bar}")
+            return None
+        data = self.market_data_main.add_new_columns(data)
+        logging.info(f"开始计算技术指标: {symbol} {bar}")
+        data = self.market_data_main.calculate_metrics(data)
+        row = data.iloc[-1]
+        return row
 
     def batch_monitor_realtime_market(
         self,
         only_output_huge_volume: bool = True,
-        only_output_rise: bool = False,
+        only_output_rise: bool = True,
     ):
         for symbol in self.market_data_main.symbols:
             for bar in self.market_data_main.bars:
+                logging.info(f"开始监控: {symbol} {bar} 窗口大小: {self.window_size} 行情数据")
+                try:
                     self.monitor_realtime_market(
                         symbol,
                         bar,
                         only_output_huge_volume,
                         only_output_rise,
                     )
+                except Exception as e:
+                    logging.error(f"监控失败: {symbol} {bar} 窗口大小: {self.window_size} 行情数据: {e}")
+                    continue
+
+
+if __name__ == "__main__":
+    market_monitor_main = MarketMonitorMain()
+    market_monitor_main.monitor_realtime_market(
+        symbol="ETH-USDT",
+        bar="5m",
+        only_output_huge_volume=True,
+        only_output_rise=False,
+    )

monitor_schedule.py

@@ -0,0 +1,20 @@
+from market_monitor_main import MarketMonitorMain
+import logging
+import time
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s: %(message)s")
+
+
+def monitor_schedule():
+    market_monitor_main = MarketMonitorMain()
+    logging.info("开始监控")
+    while True: # 每分钟监控一次
+        market_monitor_main.batch_monitor_realtime_market(
+            only_output_huge_volume=True,
+            only_output_rise=False,
+        )
+        logging.info("本次循环监控结束，等待1分钟")
+        time.sleep(60)
+
+if __name__ == "__main__":
+    monitor_schedule()

sql/query/sql_playground.sql

@@ -1,3 +1,5 @@
+select * from crypto_market_monitor;
+delete from crypto_market_monitor where timestamp=1754382900000;
 select date_time, open, high, low, close, k_shape from crypto_market_data
 WHERE symbol='XCH-USDT' and bar='5m' and date_time > '2025-08-04 15:00:00'
 order by timestamp ;
@@ -6,6 +8,10 @@ select * from crypto_market_data
 WHERE symbol='XCH-USDT' and bar='5m' and date_time > '2025-08-04 15:00:00'
 order by timestamp asc;
 
+select * from crypto_huge_volume
+WHERE symbol='XCH-USDT' and bar='5m' #and date_time > '2025-08-04 15:00:00'
+order by timestamp asc;
+
 
 delete FROM crypto_market_data where symbol != 'XCH-USDT';