aiomql/Untitled.ipynb

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# import shelve
# import pickle
# import zlib
# import lzma
# import pytz
from datetime import datetime, timedelta
from aiomql import MetaTrader, TimeFrame, AccountInfo, TimeFrame, CopyTicks, Account, Symbol
from MetaTrader5 import SymbolInfo
import pandas as pd
from pandas import DataFrame
import pytz

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res = await Account().sign_in()
print(res)

True

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tz = pytz.timezone('Etc/UTC')
sym = Symbol(name='EURUSD')
start = datetime(day=22, month=8, year=2024, tzinfo=tz)
end = datetime(day=26, month=8, year=2024, hour=12, tzinfo=tz)
# rates = await sym.mt5.copy_rates_from(symbol='EURUSD', date_from=end, count=5, timeframe=TimeFrame.H12)
rates = await sym.mt5.copy_rates_from_pos(symbol='EURUSD', start_pos=0, count=5, timeframe=TimeFrame.H12)
df = DataFrame(rates)
df['time'] = pd.to_datetime(df['time'], unit='s')
df.index[-1]

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4

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df.loc[2:6]

Out [30]:

	time	open	high	low	close	tick_volume	spread	real_volume
2	2024-08-25 12:00:00	1.11869	1.11947	1.11849	1.11894	4570	1	0
3	2024-08-26 00:00:00	1.11894	1.12016	1.11628	1.11652	43583	0	0
4	2024-08-26 12:00:00	1.11652	1.11790	1.11501	1.11618	45034	0	0

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now = datetime.now()
st = now.replace(hour=0, minute=0, second=0, day=1, month=1, year=2023)
et = now.replace(hour=9, minute=0, second=0)
diff = et - st
secs = int(diff.total_seconds())
# st = now.replace(hour=0, day=16)
# et = now.replace(hour=9)
# start = now.replace(day=now.day-3, tzinfo=tz)
# end = now.replace(day=now.day-1, tzinfo=tz)

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symbols = {'Volatility 10 Index', 'Volatility 100 (1s) Index', 'Volatility 25 Index'}
timeframes = {TimeFrame.M5, TimeFrame.H1, TimeFrame.M1, TimeFrame.H4, TimeFrame.M30, TimeFrame.M15}
gd = GetData(st, et, timeframes, symbols, name='data')
await gd.fail()

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symbols = {'Volatility 10 Index', 'Volatility 100 (1s) Index', 'Volatility 25 Index'}
timeframes = {TimeFrame.M5, TimeFrame.H1, TimeFrame.M1, TimeFrame.H4, TimeFrame.M30, TimeFrame.M15}
async with MetaTester(st, et, timeframes, symbols, name='data') as mt:
    # res = await mt.copy_ticks_range('Volatility 100 Index', st, et, CopyTicks.ALL)
    # print(res)
    await mt.get_and_save_data()

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df = pd.DataFrame(res)

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# df.set_index(list(range(secs)))
df.drop_duplicates(subset=['time'], keep='last', )

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df = df.set_index('time', drop=False, verify_integrity=True)

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bg = int(st.timestamp())
en = int(secs) + bg
index = range(bg, en)

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bf = len(df.index)
df = df.reindex(index=index, method='nearest')

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last = df.iloc[-1].time
print(datetime.fromtimestamp(last, tz=tz), et)

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acc = AccountInfo(balance=500)
data = MetaTester(start, end).load_data('data')
td = TestData(acc, data)

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ticks = data['ticks']['Volatility 10 Index']

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ticks[-1]

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y = TimeFrame.M5
y.time

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end.timestamp()

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len(ticks)

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type(ticks[0])

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ticks.reshape(8, 86160)

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import numpy as np

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res = np.reshape(ticks, (-1, 8))

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ticks.shape = (86160, 8)

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res = np.hstack(ticks)

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v = np.array((*ticks[0]))

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r = next(iter(ticks))

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v.shape

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ar = list(range(4))
t = np.array(ar)
t.shape = (1, 4)
t

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mt.config.login

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acc = Account()
await acc.sign_in()

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mt5 = MetaTrader()
sym = await mt5.symbol_info('Volatility 100 (1s) Index')
print(sym._asdict)

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n = datetime.now()
start = n.replace(hour=0, day=1, year=2020, month=1)
end = n.replace(hour=15)
res = await mt.copy_rates_range('Volatility 25 Index', TimeFrame.M1, start, end)

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res = pd.DataFrame(res)
len(res.index)

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print(start)

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data = shelve.open('./data/01-08-24_17-08-24', writeback=True)

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data = dict(data)

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data = pickle.dumps(data)

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data = zlib.compress(data, level=9)

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_data = lzma.compress(data)

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fh = lzma.open('./data/ldata.xz', 'w')
fh.write(_data)
fh.close()

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rb = lzma.open('./data/ldata.xz')
rbb = rb.read()
rb.close()

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rbd = lzma.decompress(rbb)

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rdata = pickle.loads(rbd)

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data.keys()

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fh = open('./data/pdata', 'wb')
pickle.dump(rdata, fh)

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fh.close()

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