I promise python compare:

how to read in python hst file from MT4:
Code
import numpy as np
import pandas as pd

def read_hst(filepath):
    with open(filepath, 'rb') as f:
        ver = np.frombuffer(f.read(148)[:4], 'i4')
        dtype = [('time', 'u8'), ('open', 'f8'), ('high', 'f8'), ('low', 'f8'),
                     ('close', 'f8'), ('volume', 'i8'), ('s', 'i4'), ('r', 'i8')]
        df = pd.DataFrame(np.frombuffer(f.read(), dtype=dtype).astype(dtype))
        df['time'] = pd.to_datetime(df['time'], unit='s')
    return df

dMT4=read_hst("EURUSD15.hst")
dMT4.head()


output is:
Code
time	open	high	low	close	volume	s	r
0	2019-06-27 16:00:00	1.13665	1.13678	1.13618	1.13666	1489	0	0
1	2019-06-27 16:15:00	1.13665	1.13672	1.13638	1.13644	989	        0      0
2	2019-06-27 16:30:00	1.13640	1.13671	1.13608	1.13627	1557	0	0
3	2019-06-27 16:45:00	1.13626	1.13628	1.13564	1.13585	1274	0	0
4	2019-06-27 17:00:00	1.13587	1.13707	1.13574	1.13699	1592	0	0


how to read in python history file from ZORRO:

Code
def read_t6(filepath):
    with open(filepath, 'rb') as f:
        dtype = [('time', 'f8'), ('high', 'f4'), ('low', 'f4'), ('open', 'f4'),
                     ('close', 'f4'), ('val', 'f4'), ('vol', 'f4')]
        df = pd.DataFrame(np.frombuffer(f.read(), dtype=dtype).astype(dtype))
        df['time'] = pd.to_datetime(df['time'],unit='D', origin=pd.Timestamp('1899-12-30'))
        df=df.set_index("time")
        ohlc_dict = {'open':'first', 'high':'max', 'low':'min', 'close': 'last'}
        
    return df.resample('15Min').agg(ohlc_dict)
dT6=read_t6("EURUSD_2020.t6")
dT6.head()


Now I work on the compare this dataset - datetime

come later....