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get_bars.py

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+import pytz
+from datetime import datetime
+import MetaTrader5 as mt5
+import pandas as pd
+pd.set_option('display.max_columns', 500)  # number of columns to be displayed
+pd.set_option('display.width', 1500)      # max table width to display
+# import pytz module for working with time zone
+
+# establish connection to MetaTrader 5 terminal
+mt5.initialize()
+# file name to export to csv
+file_name = 'EURUSD_H4_20220103_20220203.csv'
+# set time zone to UTC
+timezone = pytz.timezone("Etc/GMT-2")
+# create 'datetime' objects in UTC time zone to avoid the implementation of a local time zone offset
+utc_from = datetime(2022, 1, 3, tzinfo=timezone)
+utc_to = datetime(2022, 2, 3, tzinfo=timezone)
+# get bars from EURUSD H4 within the interval of 2021.05.03 00:00 - 2022.01.03 00:00 in GMT-2 time zone
+rates = mt5.copy_rates_range("EURUSD", mt5.TIMEFRAME_H4, utc_from, utc_to)
+
+# shut down connection to the MetaTrader 5 terminal
+mt5.shutdown()
+
+# display each element of obtained data in a new line
+print("Display obtained data 'as is'")
+counter = 0
+for rate in rates:
+    counter += 1
+    if counter <= 10:
+        print(rate)
+
+# create DataFrame out of the obtained data
+rates_frame = pd.DataFrame(rates)
+# convert time in seconds into the 'datetime' format
+rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
+
+# display data
+print("\nDisplay dataframe with data")
+print(rates_frame.head(10))
+rates_frame.to_csv(file_name, encoding='utf-8', index=False)