init

Bithumb.py

@@ -1,17 +1,19 @@
-import pybithumb
-from hts.HTS import HTS
-import pandas as pd
-from sklearn.linear_model import LinearRegression
-from sklearn.preprocessing import StandardScaler, MinMaxScaler
-import plotly.graph_objects as go
-from plotly import subplots
-import plotly.io as po
-from math import nan
 import csv
 import os
-from hts.BuySellChecker import BuySellChecker
+import time
+import pybithumb
+import pandas as pd
+from math import nan
+import plotly.io as po
+from plotly import subplots
+import plotly.graph_objects as go
 from datetime import datetime
+from sklearn.linear_model import LinearRegression
+from sklearn.preprocessing import StandardScaler, MinMaxScaler
+
 from stock.analysis.AnalyzerSqlite import AnalyzerSqlite
+from hts.BuySellChecker import BuySellChecker
+from hts.HTS import HTS
 
 class Bithumb(HTS):
 
@@ -660,6 +662,7 @@ if __name__ == "__main__":
             for ticker in tickers:
                 print(ticker, datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
                 bithumb.buyRealTime(ticker, isRealTime)
+            time.sleep(5)
     else:
         for ticker in tickers:
             print(ticker, datetime.now().strftime('%Y-%m-%d %H:%M:%S'))