添加1分钟时间打印log

K线动能理论.txt

@@ -2,8 +2,11 @@
 5m, 15m, 30m, 1h, 2h, 4h, 8h, 12h, 16h, 1d, 2d, 3d, 1w, 2w, 1M
 
 参考时间周期
-大周期：1h, 4h, 1d
+大周期：1h
-小周期：30m, 15m, 5m
+小周期：15m
+
+价格在1h周期ema156之上为大周期上涨，反之为大周期下跌
+在1h大周期上涨时，小周期15m，下跌触碰到
 
 顺大逆小
 大周期看多，小周期跌完做多，跌完：顶分型和EMA52归零轴反弹

strategies/ChanLun_EMA52.py

@@ -106,7 +106,9 @@ class ChanLun_EMA52(IStrategy):
 		dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
 		last_price = dataframe.iloc[-1]['close']
 		tf_ema52_list = self.chan.check_price_ema52(last_price)
-		print(tf_ema52_list)
+		if self.last_time + timedelta(minutes=1) < datetime.now():
+			print(tf_ema52_list)
+			self.last_time = datetime.now()
 		return dataframe
 	def init_dataframes(self, dataframe_1m):
 		dataframe_15m = self.dp.get_pair_dataframe(pair=self.pair, timeframe='15m')

web/app.py

@@ -45,7 +45,7 @@ china_stock = ChinaStockData()
 logger = logging.getLogger(__name__)
 
 DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://127.0.0.1:9009"))
-DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://192.168.1.9:9009"))
+#DATA_SERVICE_URL = os.environ.get("DATA_SERVICE_URL", os.environ.get("DATASVC_URL", "http://192.168.1.9:9009"))
 DEFAULT_TIMEFRAME_LABELS = OrderedDict([
     ("1m", "1分钟"),
     ("3m", "3分钟"),