MetaTrader 5 Python User Group - how to use Python in Metatrader - page 90

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Authoritative MetaQuotes-Demo tick timestamp and copy_ticks_range time-domain semantics

Alain Verleyen, 2026.09.24 17:35

I reported the documentation issue about datetime and timezone to MetaQuotes. 

Where is the documentation wrong ? Each time it claims the following :

The confusion comes from how Python datetime is working, by default it will use the local timezone, the one of the computer where the python code is running, so to avoid returning different data depending where your code run, it's requested to set UTC timezone for each datetime parameter used in a python/MQL5 functions. So you need to use an UTC timezone datetime to finally receive data using the broker server timezone including DST.

An example to illustrate this :

# set time zone to UTC
timezone = pytz.timezone("Etc/UTC")
# create 'datetime' object in UTC time zone to avoid the implementation of a local time zone offset
utc_from = datetime(2025, 1, 10, 0, 0, tzinfo=timezone)
# get 10 EURUSD H4 bars starting from 01.10.2020 in UTC time zone
rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_H1, utc_from, 1)

# Check without any UTC reference
dt_from = datetime(2025, 1, 10, 0, 0)
ratesCheck = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_H1, dt_from, 1)

 
# shut down connection to the MetaTrader 5 terminal
mt5.shutdown()
# display each element of obtained data in a new line
print("Display obtained 'UTC TZ' data 'as is'")
for rate in rates:
   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 date_from using UTC")
print(rates_frame)  

# display each element of obtained data in a new line
print("Display obtained 'local TZ' data 'as is'")
for rate in rates:
   print(ratesCheck)

# create DataFrame out of the obtained data
rates_frame_check = pd.DataFrame(ratesCheck)
# convert time in seconds into the datetime format
rates_frame_check['time']=pd.to_datetime(rates_frame_check['time'], unit='s')
                           
# display data
print("\nDisplay dataframe with date_from using local time (no TZ specified)")
print(rates_frame_check)  

2026.09.24 13:27:39.878    Display obtained 'UTC TZ' data 'as is'
2026.09.24 13:27:39.878    (1736467200, 1.03011, 1.03011, 1.0294, 1.02998, 288, 4, 0)
2026.09.24 13:27:39.878    
2026.09.24 13:27:39.878    Display dataframe with date_from using UTC
2026.09.24 13:27:39.878            time     open     high     low    close  tick_volume  spread  real_volume
2026.09.24 13:27:39.878    0 2025-01-10  1.03011  1.03011  1.0294  1.02998          288       4            0
2026.09.24 13:27:39.878    Display obtained 'local TZ' data 'as is'
2026.09.24 13:27:39.878    [(1736485200, 1.03016, 1.03031, 1.02975, 1.02983, 698, 0, 0)]
2026.09.24 13:27:39.878    
2026.09.24 13:27:39.878    Display dataframe with date_from using local time (no TZ specified)
2026.09.24 13:27:39.878                     time     open     high      low    close  tick_volume  spread  real_volume
2026.09.24 13:27:39.878    0 2025-01-10 05:00:00  1.03016  1.03031  1.02975  1.02983          698       0            0

2025.10.01 00:00 is 1736467200 (epoch time in seconds) 

2025.10.01 05:00 is 1736485200 with my local timezone shift at that date. If you run this code from a different timezone, the first one will be the same, but the second one will differ.

So you get different data because you request different datetime, python/MQL5 API request UTC datetime. But the data MT5 returns are ALWAYS broker server time data.


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