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