def getBars(symbol, start, end=None, timeFrame=INTRADAY):
# definimos o fuso horário como UTC
#timezone = pytz.timezone("Etc/UTC")
#print("timeFrame: ",timeFrame)
#print("symbol: ",symbol)
#print("start: ",start)
#print("end: ",end)
if not connected:
print(
"In order to use this function, you must be connected to B3. Use function connect()"
)
return
if symbol == None or type(symbol) != str:
return None
else:
symbol = symbol.upper()
if timeFrame == DAILY:
timeFrame = mt5.TIMEFRAME_D1
elif timeFrame == INTRADAY:
timeFrame = mt5.TIMEFRAME_M1
else:
timeFrame = mt5.TIMEFRAME_D1
if end == None:
end = datetime.now()
if type(start).__name__ != 'datetime' and type(
start).__name__ != 'Timestamp':
if type(start).__name__ != 'int':
print('Error, start should be a datetime or int, but it is ',
type(start).__name__)
return None
else:
start_day = datetime.now() #- timedelta(days=start)
rates = mt5.copy_rates_from(symbol, timeFrame, start_day, start)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
if len(rates_frame) > 0:
rates_frame['time'] = pd.to_datetime(rates_frame['time'],
unit='s')
#print("rates", rates_frame)
return rates_frame
else:
if type(end).__name__ == 'int':
rates = mt5.copy_rates_from(symbol, timeFrame, start, end)
else:
rates = mt5.copy_rates_range(symbol, timeFrame, start, end)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
if len(rates_frame) > 0:
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
#print("rates", rates_frame)
return rates_frame
def get_prices(self, event, timeframe, fromdate, numberofcandles):
prices = pd.DataFrame()
symbols = self.__companies['Ticker']
tmp = {}
for i in symbols:
# try:
tmp = mt5.copy_rates_from(i, timeframe, fromdate, numberofcandles)
# if (i==symbols[0]):
# prices=pd.DataFrame()
# prices['time'] = pd.to_datetime(tmp['time'], unit='s')
# prices.rename({'time': 'Date'}, axis=1, inplace=True)
# prices.set_index('Date', inplace=True)
# shutdown()
# tmp = web.DataReader(i, self.__api, start_date, end_date)
# print('Fetched prices for: '+i)
# print(tmp.head())
#
# for col in tmp.columns:
# print(col)
# except:
# print('Issue getting prices for: '+i)
# else:
prices[i] = tmp[event]
return prices
def copy(self, symbol, date_from, date_to=None, count=None, timeframe=mt5.TIMEFRAME_H1):
"""
Args:
symbol (list) : List of symbols
Get all symbols : [i.name for i in mt5.symbols_get()]
date_from (datetime): Date, the ticks are requested from
date_to (datetime): Date, up to which the ticks are requested
count (int) : The length of the data (minutes)
timeframe (int) : Time timeframe of data sampling (mt5.TIMEFRAME)
Form : mt5.TIMEFRAME_ + M(minute) / H(hour) / D(day) / W(week) / MN(month) + value
"""
self.data = []
self.date_from = date_from
self.data_to = date_to
self.count = count
for i in range(len(symbol)):
if count:
data = mt5.copy_rates_from(symbol[i], timeframe, date_from, count).tolist()
elif date_to:
data = mt5.copy_rates_range(symbol[i], timeframe, date_from, date_to).tolist()
else:
print('Argument passed in error')
return
if data is None:
print(f'{symbol[i]} data copy error, skip')
else:
self.data += [data]
self.data = torch.FloatTensor(self.data).permute(1, 0, 2)
def DataRequest(ticker, rates, plot):
print("establish connection to MetaTrader 5 terminal...")
if not mt5.initialize():
print("initialize() failed, error code =", mt5.last_error())
quit()
# request rates from ticker
tickerRates = mt5.copy_rates_from(ticker, mt5.TIMEFRAME_M1, datetime.now(),
rates)
#print those values
print("Number of rates returned: " + str(len(tickerRates)))
#create dataframe from rates and handle datetime as string for interpolation on pyplot
tickerFrame = pd.DataFrame(tickerRates)
tickerFrame['time'] = pd.to_datetime(tickerFrame['time'], unit='s')
tickerFrame['time'] = tickerFrame['time'].astype(str)
if (plot):
plt.plot(tickerFrame['time'],
tickerFrame['close'],
'b-',
label='close')
plt.show()
return tickerFrame
def get_bars(symbol, start, end=None, timeFrame=DAILY):
# definimos o fuso horário como UTC
#timezone = pytz.timezone("Etc/UTC")
if symbol == None or type(symbol) != str:
return None
else:
symbol = symbol.upper()
if timeFrame == DAILY:
timeFrame = mt5.TIMEFRAME_D1
elif timeFrame == INTRADAY:
timeFrame = mt5.TIMEFRAME_M1
else:
timeFrame = mt5.TIMEFRAME_D1
if end == None:
end = datetime.now()
if type(start).__name__ != 'datetime':
if type(start).__name__ != 'int':
print(
'Error, start should be a datetime from package datetime or int'
)
else:
start_day = datetime.now() #- timedelta(days=start)
rates = mt5.copy_rates_from(symbol, timeFrame, start_day, start)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
if len(rates_frame) > 0:
rates_frame['time'] = pd.to_datetime(rates_frame['time'],
unit='s')
return rates_frame
else:
rates = mt5.copy_rates_range(symbol, timeFrame, start, end)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
return rates_frame
def getDailYBars(
symbol,
start,
end=None): # sao inclusas barras com tempo de abertura <= end.
# definimos o fuso horário como UTC
#timezone = pytz.timezone("Etc/UTC")
if not connected:
print(
"In order to use this function, you must be connected to B3. Use function connect()"
)
return
if end == None:
end = datetime.now()
if type(start).__name__ != 'datetime':
if type(start).__name__ != 'int':
print(
'Error, start should be a datetime from package datetime or int'
)
else:
start_day = datetime.now() #- timedelta(days=start)
rates = mt5.copy_rates_from(symbol, mt5.TIMEFRAME_D1, start_day,
start)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
return rates_frame
else:
rates = mt5.copy_rates_range(symbol, mt5.TIMEFRAME_D1, start, end)
# criamos a partir dos dados obtidos DataFrame
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
return rates_frame
def ATR_Calculator(y, m, d, symbol):
mt5.initialize()
# 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.datetime(y, m, d, tzinfo=timezone)
# get 11 bars of any symbol that you want in 1D timeframe starting from given time in format of y=Year,m=Month,d=Day
rates = mt5.copy_rates_from(symbol, mt5.TIMEFRAME_D1, utc_from, 32)
# create DataFrame out of the obtained data
rates_frame = pd.DataFrame(rates)
DaysOn = len(rates_frame)
# convert time in seconds into the datetime format
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
# if you need to see the data print rates_frame. Otherwise let it be as a comment
# print(rates_frame)
# create the TR as an array with specified length
if DaysOn < 3:
return None
else:
TR = np.zeros(DaysOn - 2)
# start to fill the TR
for i in range(1, DaysOn - 1):
TR[i -
1] = max(rates_frame['high'][i], rates_frame['close'][i - 1]) - min(
rates_frame['low'][i], rates_frame['close'][i - 1])
# now make the ATR dictionary
ATR = sum(TR[-10:-1]) / 10
ATR = {'time': rates_frame["time"].iloc[-1], 'ATR': ATR}
return ATR
def get_profit(self):
get_rates = None
if self.base[:3].lower() != "usd":
try:
self.us_base = self.base[:3].upper() + "USD"
get_rates = mt.copy_rates_from(self.us_base, mt.TIMEFRAME_M1,
self.time, 10)
if get_rates == None:
self.us_base = "USD" + self.base[:3].upper()
get_rates = mt.copy_rates_from(self.us_base,
mt.TIMEFRAME_M1, self.time,
10)
if get_rates == None:
self.bid = 1.0
self.ask = 1.0
except Exception as e:
print(self.base, self.us_base, e)
"""
elif self.base[:3].lower() == "usd":
try:
self.us_base = self.base[3:6].upper() + "USD"
get_rates = mt.copy_rates_from(self.us_base,
mt.TIMEFRAME_M1,self.time,10)
if get_rates == None:
self.us_base = "USD" + self.base[3:6].upper()
get_rates = mt.copy_rates_from(self.us_base,
mt.TIMEFRAME_M1,self.time,10)
if get_rates == None:
self.bid = 1.0
self.ask = 1.0
except Exception as e:
print(self.base,self.us_base,e)
"""
get_currency = round(self.exchange_rate_difference\
* self.price_per_pip_change,8)
bare_currency = get_currency * pow(10, abs(self.exponent))
if get_rates != None:
self.bid = get_rates[0][1]
self.ask = get_rates[0][3]
self.profit = round(bare_currency * self.ask, 2)
self.profit = self.profit + self.swap
round(self.profit, 2)
else:
self.profit = bare_currency + self.swap
self.profit = round(self.profit, 2)
def data_collection(timeframe, n):
if not mt5.initialize():
print('failed to connect')
quit()
timeframe_dict = {
'H1':mt5.TIMEFRAME_H1,
'D1':mt5.TIMEFRAME_D1,
'W1':mt5.TIMEFRAME_W1
}
currs = ['EUR', 'GBP', 'AUD', 'NZD',
'USD', 'CAD', 'CHF', 'JPY']
ohlc_dict = {}
for curr_no, curr1 in enumerate(currs):
for curr2 in currs[curr_no+1:]:
curr_pair = curr1 + curr2
#Get candles from the past 3 weeks (exclusive of current week)
time_now = pd.Timestamp.now(tz='Etc/UTC')
#four_wks_ago = time_now - dt.timedelta(weeks=3)
#day_of_wk = dt.timedelta(days=four_wks_ago.isoweekday()%7)
#past_4_wks = dt.date(four_wks_ago.year, four_wks_ago.month, four_wks_ago.day) - day_of_wk
#ohlc_arr = mt5.copy_rates_range(curr_pair, timeframe_dict[timeframe],
# pd.to_datetime(past_4_wks), time_now)
ohlc_arr = mt5.copy_rates_from(curr_pair, timeframe_dict[timeframe],
time_now, n)
column_names = {
'open':'Open',
'high':'High',
'low':'Low',
'close':'Close'
}
try:
ohlc_df = pd.DataFrame(ohlc_arr)
ohlc_df.index = pd.to_datetime(ohlc_df.iloc[:, 0], unit='s')
ohlc_df = ohlc_df.drop(columns=['time'])
ohlc_df = ohlc_df.rename(columns=column_names)
ohlc_dict[curr_pair+'_ohlc_df'] = ohlc_df
except:
print('ERROR OCCURRED IN: ', curr_pair)
mt5.shutdown()
return ohlc_dict
def getDataFromMetatrader(currency="EURUSD",
timeframe=mt5.TIMEFRAME_H1,
fromdate=datetime.now(),
count=70000):
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()
eurusd_rates = mt5.copy_rates_from(currency, timeframe, fromdate,
count)
mt5.shutdown()
df = pd.DataFrame(data=eurusd_rates)
df['time'] = pd.to_datetime(df['time'], unit='s')
return df
def get_prices_for_whole_period():
now = datetime.now(timezone)
rates_whole_period = mt5.copy_rates_from(EUR_USD, mt5.TIMEFRAME_H1, now,
barsAmount)
rates_frame = pandas.DataFrame(rates_whole_period)
high_price = rates_frame[[HIGH]]
low_price = rates_frame[[LOW]]
bar_size = high_price[HIGH] - low_price[LOW]
print(
f'Максимальная свеча за весь период: {round(bar_size.max(), round_num)}'
)
print(
f'Минимальная свеча за весь период: {round(bar_size.min(), round_num)}'
)
def inicializa(Ativo, Ano,Mes,Dia,QtdeBar,TimeFrame):
utc_tz = timezone("America/Recife") #timezone("UTC")
try:
#MT5Initialize()
mt5.initialize()
#MT5WaitForTerminal()
mt5.wait()
utc_from = datetime(Ano, Mes, Dia, tzinfo=utc_tz)
#ticksAtivo = MT5CopyRatesFrom(Ativo, TimeFrame, utc_from, QtdeBar)
barsAtivo = mt5.copy_rates_from(Ativo, TimeFrame, utc_from, QtdeBar)
#MT5Shutdown()
mt5.shutdown()
return barsAtivo
except Exception as e:
raise e
def animate(i):
ax1.clear()
rates = mt5.copy_rates_from(pair, timeframe, datetime.now(), array)
rates_frame = pd.DataFrame(rates)
candlestick2_ohlc(ax1,
rates_frame['open'],
rates_frame['high'],
rates_frame['low'],
rates_frame['close'],
width=0.6)
xdate = [datetime.fromtimestamp(i) for i in rates_frame['time']]
ax1.xaxis.set_major_locator(ticker.MaxNLocator(6))
def mydate(x, pos):
try:
return xdate[int(x)]
except IndexError:
return ''
ax1.xaxis.set_major_formatter(ticker.FuncFormatter(mydate))
fig.autofmt_xdate()
fig.tight_layout()
highMA = periodHigh(pair, 10, timeframe, array)
lowMA = periodLow(pair, 10, timeframe, array)
#rates7de = period(pair,7,timeframe,array)
#rates25de = period(pair,25,timeframe,array)
#rates99de = period(pair,99,timeframe,array)
ax1.plot(lowMA)
ax1.plot(highMA)
#ax1.plot(rates99de)
#ax1.plot(rates25de)
#ax1.plot(rates7de)
ask = mt5.symbol_info_tick(pair).ask #BUY
bid = mt5.symbol_info_tick(pair).bid #SELL
print('BUY: ', (ask - lowMA[-1]) / (highMA[-1] - lowMA[-1]))
print('sell: ', (bid - lowMA[-1]) / (highMA[-1] - lowMA[-1]))
def period(pair, period, timeframe, array):
ratesDE = collections.deque([0.0] * array)
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()
currentTime = datetime.now()
rates = mt5.copy_rates_from(pair, timeframe, currentTime, period + array)
for arr in range(array):
calculated = 0
for pos in range(period):
calculated += rates[arr + pos][4]
ratesDE.appendleft(calculated / period)
ratesDE.pop()
ratesDE.reverse()
return ratesDE
def test():
# connect to MetaTrader 5
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()
print('Version:', mt5.version())
#dji = mt5.copy_rates_range('US30Cash', mt5.TIMEFRAME_M30, Now() - DeltaDay(2), Now())
#print(dji)
# request 1000 ticks from EURAUD
euraud_ticks = mt5.copy_ticks_from("US30Cash", datetime(2020,4,17,23), 1000, mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(2020,1,27,13), datetime(2020,1,28,13), mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_M1, datetime(2020,1,28,13), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("EURGBP", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, datetime(2020,1,27,13), datetime(2020,1,28,13))
#print(eurusd_rates)
# shut down connection to MetaTrader 5
mt5.shutdown()
return
def Time_Shift(y, m, d, symbol):
mt5.initialize()
# 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.datetime(y, m, d, tzinfo=timezone)
# get 11 bars of any symbol that you want in 1D timeframe starting from given time in format of y=Year,m=Month,d=Day
rates = mt5.copy_rates_from(symbol, mt5.TIMEFRAME_D1, utc_from, 32)
# 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')
# if you need to see the data print rates_frame. Otherwise let it be as a comment
# print(rates_frame)
# now shift the time to day before
timeshift = rates_frame['time'].iloc[-2].date()
timeshift = str(timeshift)
timeshift = timeshift.split('-')
Y = int(timeshift[0])
M = int(timeshift[1])
D = int(timeshift[2])
return [Y, M, D]
ano = datetime.today().year
mes = datetime.today().month
dia = datetime.today().day
# definimos o fuso horário
timezone = pytz.timezone("Brazil/DeNoronha")
utc_from = datetime(ano, mes, dia, tzinfo=timezone)
# quantidade de pregões desde o dia inicial
range_time = 60 # em dias pois estou usando timeframe diário
print('Executando o programa...')
for ativo in ativos:
try:
# coletando as informações do MT5
rates = mt5.copy_rates_from(ativo, mt5.TIMEFRAME_D1, utc_from,
range_time)
# transformando para dataframe
rf = pd.DataFrame(rates)
# transformando a coluna da data no formato datetime
rf['time'] = pd.to_datetime(rf['time'], unit='s')
# cálculo das médias móveis
rf['MM4'] = rf['close'].rolling(4).mean()
rf['MM17'] = rf['close'].rolling(17).mean()
rf['MM55'] = rf['close'].rolling(55).mean()
if (rf['MM4'][range_time - 1] < rf['MM17'][range_time - 2]) and (
rf['MM4'][range_time - 1] >= rf['MM17'][range_time - 1]) and (
rf['MM17'][range_time - 1] >= rf['MM55'][range_time - 1]):
new_row = {
'Data': rf['time'][range_time],
'Ativo': ativo,
# request connection status and parameters
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())
# request 1000 ticks from EURAUD
euraud_ticks = mt5.copy_ticks_from("ETHLTC.", datetime(2020, 1, 28, 13), 1000,
mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("BCHETH.", datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13),
mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("ETHLTC.", mt5.TIMEFRAME_M1,
datetime(2020, 1, 28, 13), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("BCHETH.", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("ETHEUR.", mt5.TIMEFRAME_M1,
datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13))
# shut down connection to MetaTrader 5
mt5.shutdown()
#DATA
print('euraud_ticks(', len(euraud_ticks), ')')
for val in euraud_ticks[:10]:
print(val)
print('audusd_ticks(', len(audusd_ticks), ')')
for val in audusd_ticks[:10]:
if not mt5.initialize(login=config_dict["user"], server="ModalMais-DMA4 - Beta", password=config_dict["password"]):
print("initialize() failed, error code =", mt5.last_error())
quit(1)
with open("tickers.json") as json_file:
json_dict = json.loads(json_file.read())
string_to_timeframe = {"m1": mt5.TIMEFRAME_M1, "m2": mt5.TIMEFRAME_M2, "m3": mt5.TIMEFRAME_M3, "m4": mt5.TIMEFRAME_M4,
"m5": mt5.TIMEFRAME_M5, "m6": mt5.TIMEFRAME_M6, "m10": mt5.TIMEFRAME_M10,
"m12": mt5.TIMEFRAME_M12, "m15": mt5.TIMEFRAME_M15, "m20": mt5.TIMEFRAME_M20,
"m30": mt5.TIMEFRAME_M30, "h1": mt5.TIMEFRAME_H1, "h2": mt5.TIMEFRAME_H2, "h3": mt5.TIMEFRAME_H3,
"h4": mt5.TIMEFRAME_H4, "h6": mt5.TIMEFRAME_H6, "h8": mt5.TIMEFRAME_H8, "h12": mt5.TIMEFRAME_H12,
"d1": mt5.TIMEFRAME_D1, "w1": mt5.TIMEFRAME_W1, "mn1": mt5.TIMEFRAME_MN1}
timeframe = json_dict["timeframe"]
utc_from = datetime.now()
for ticker in tqdm(json_dict["tickers"]):
try:
rates = mt5.copy_rates_from(ticker, string_to_timeframe[timeframe], utc_from, 9999999)
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
rates_frame = rates_frame.set_index("time")
rates_frame.to_csv(f"../data/{ticker}_{timeframe}.csv")
except KeyError as e:
print(f"Error type: {type(e)}")
print("Try to set unlimited bars on mt5 platform.")
except Exception as e:
print(f"Error on ticker: {ticker}; error: {type(e)}{e}")
mt5.shutdown()
mt5.shutdown()
# request connection status and parameters
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())
# request ticks from GBPUSD
gbpusd_ticks = mt5.copy_ticks_from("GBPUSD", datetime(2021, 1, 18, 13), 1,
mt5.COPY_TICKS_ALL)
# request ticks from GBPJPY within 2020.01.20 13:00 - 2020.03.18 13:00
gbpusdticks = mt5.copy_ticks_range("GBPUSD", datetime(2021, 1, 20, 13),
datetime(now), mt5.COPY_TICKS_ALL)
# get bars from different symbols in 3 different ways
gbpusd_rates = mt5.copy_rates_from("GBPUSD", mt5.TIMEFRAME_M15,
datetime(2020, 1, 20, 13), 1)
gbpusd_rates = mt5.copy_rates_from_pos("GBPUSD", mt5.TIMEFRAME_M15, 0, 1)
gbpusd_rates = mt5.copy_rates_range("GBPUSD", mt5.TIMEFRAME_M15,
datetime(2020, 1, 20, 13),
datetime(2020, 3, 18, 13))
# shut down connection to MetaTrader 5
mt5.shutdown()
#data to be displayed in the terminal
print('gbpusd_ticks(', len(gbpusd_ticks), ')')
for val in gbpusd_ticks[:1]:
print(val)
print('gbpusd_rates(', len(gbpusd_rates), ')')
for val in gbpusd_rates[:1]:
pair = "ETHUSD."
array = [0.0] * 10
rates7de = collections.deque(array)
rates25de = collections.deque(array)
rates99de = collections.deque(array)
# connect to MetaTrader 5
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()
while(True):
signal = ''
currentTime = datetime.now()
rates7 = mt5.copy_rates_from(pair, timeframe, currentTime, 7)
rates25 = mt5.copy_rates_from(pair, timeframe, currentTime, 25)
rates99 = mt5.copy_rates_from(pair, timeframe, currentTime, 99)
ticks = mt5.copy_ticks_from(pair, currentTime, 1, mt5.COPY_TICKS_ALL)
calculated7 = 0
for pos in rates7:
calculated7+=pos[4]
rates7de.appendleft(calculated7/7)
rates7de.pop()
print ('7:', rates7de)
calculated25 = 0
for pos in rates25:
calculated25+=pos[4]
rates25de.appendleft(calculated25/25)
# request connection status and parameters
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())
# request 1000 ticks from EURAUD
euraud_ticks = mt5.copy_ticks_from("USDJPYm", datetime(2020, 1, 28, 13), 1000,
mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("GBPJPYm", datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13),
mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("USDJPYm", mt5.TIMEFRAME_M1,
datetime(2020, 1, 28, 13), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("USDJPYm", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("USDJPYm", mt5.TIMEFRAME_M1,
datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13))
# shut down connection to MetaTrader 5
mt5.shutdown()
#DATA
print('euraud_ticks(', len(euraud_ticks), ')')
for val in euraud_ticks[:10]:
print(val)
print('audusd_ticks(', len(audusd_ticks), ')')
for val in audusd_ticks[:10]:
pd.set_option('display.max_columns', 500) # number of columns to be displayed
pd.set_option('display.width', 1500) # max table width to display
# 导入用于处理时区的pytz模块
import pytz
# 建立与MetaTrader 5程序端的连接
if not mt5.initialize():
print("initialize() failed, error code =", mt5.last_error())
quit()
# 将时区设置为UTC
timezone = pytz.timezone("Etc/UTC")
# 以UTC时区创建'datetime'对象，以避免实现本地时区偏移
utc_from = datetime(2020, 1, 10, tzinfo=timezone)
# 在UTC时区，获取01.10.2020开始的10个EURUSD H4柱形图
rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_H4, utc_from, 10)
# 断开与MetaTrader 5程序端的连接
mt5.shutdown()
# 在新行显示所获得数据的每个元素
print("Display obtained data 'as is'")
for rate in rates:
print(rate)
# 从所获得的数据创建DataFrame
rates_frame = pd.DataFrame(rates)
# 将时间（以秒为单位）转换为日期时间格式
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
# 显示数据
print("\nDisplay dataframe with data")
import MetaTrader5 as mt5
import sys
import pandas as pd
if (sys.argv[1] == None):
pair = "ETHUSD."
else:
pair = sys.argv[1]
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()
timeframe = mt5.TIMEFRAME_M1
quotes = mt5.copy_rates_from(pair, timeframe, datetime.now(), 100)
quotes = pd.DataFrame(quotes)
print(quotes)
fig, ax = plt.subplots()
candlestick2_ohlc(ax,
quotes['open'],
quotes['high'],
quotes['low'],
quotes['close'],
width=0.6)
xdate = [datetime.fromtimestamp(i) for i in quotes['time']]
ax.xaxis.set_major_locator(ticker.MaxNLocator(6))
datetime(now.year, now.month, now.day, now.hour), mt5.COPY_TICKS_ALL)
elif now.weekday() > 0 and now.day == 1 and now.month > 1:
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(now.year, now.month - 1, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour), mt5.COPY_TICKS_ALL)
elif now.weekday() == 0 and now.day == 1 and now.month == 1:
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(now.year-1, december_month, now.day - 3, now.hour),
datetime(now.year, now.month, now.day, now.hour), mt5.COPY_TICKS_ALL)
elif now.weekday() > 0 and now.day == 1 and now.month == 1:
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(now.year-1, december_month, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour), mt5.COPY_TICKS_ALL)
else:
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(now.year, now.month, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour), mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_M1, datetime(now.year, now.month, now.day, now.hour), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("EURGBP", mt5.TIMEFRAME_M1, 0, 1000)
if now.day == 1 and now.month > 1:
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, datetime(now.year, now.month-1, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour))
elif now.day == 1 and now.month == 1:
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, datetime(now.year-1, december_month, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour))
else:
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, datetime(now.year, now.month, now.day - 1, now.hour),
datetime(now.year, now.month, now.day, now.hour))
# shut down connection to MetaTrader 5
mt5.shutdown()
# request connection status and parameters
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())
start_date=datetime(2021,1,27,10)
end_date=datetime(2021,1,27,11)
# request 1000 ticks from EURAUD
#datetime(year,month,day,hour)
euraud_ticks = mt5.copy_ticks_from("EURAUD", start_date, 1000, mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("AUDUSD", start_date, end_date, mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_M1,start_date, 1000)
eurgbp_rates = mt5.copy_rates_from_pos("EURGBP", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, start_date, end_date)
# shut down connection to MetaTrader 5
mt5.shutdown()
#DATA
print('euraud_ticks(', len(euraud_ticks), ')')
for val in euraud_ticks[:10]: print(val)
print('audusd_ticks(', len(audusd_ticks), ')')
for val in audusd_ticks[:10]: print(val)
print('eurusd_rates(', len(eurusd_rates), ')')
for val in eurusd_rates[:10]: print(val)
import pytz
import pandas as pd
import matplotlib.pyplot as plt
# initialize connections
mt5.initialize(
path="C:\\Users\\silin\\AppData\\Roaming\\MetaTrader 5\\terminal64.exe",
login=35146240,
password="******")
# query for forex pair
timezone = pytz.timezone("Etc/UTC")
utc_from = datetime(2020, 1, 1,
tzinfo=timezone) # create date time for the query
rates = mt5.copy_rates_from('EURUSD', mt5.TIMEFRAME_H4, datetime.today(),
10000)
# shutdown connections
mt5.shutdown()
##### work on the data #####
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
##### Implement Order #####
def get_info(symbol):
'''https://www.mql5.com/en/docs/integration/python_metatrader5/mt5symbolinfo_py
'''
# get symbol properties
info = mt5.symbol_info(symbol)
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())
# request 1000 ticks from EURAUD
euraud_ticks = mt5.copy_ticks_from("EURAUD", datetime(2020, 1, 28, 13), 1000,
mt5.COPY_TICKS_ALL)
eurusd_ticks = mt5.copy_ticks_from("EURUSD", datetime(2020, 1, 28, 13), 1000,
mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13),
mt5.COPY_TICKS_ALL)
# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_M1,
datetime(2020, 1, 28, 13), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("EURGBP", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1,
datetime(2020, 1, 27, 13),
datetime(2020, 1, 28, 13))
# shut down connection to MetaTrader 5
mt5.shutdown()
#DATA
print('euraud_ticks(', len(euraud_ticks), ')')
for val in euraud_ticks[:10]:
print(val)
print('audusd_ticks(', len(audusd_ticks), ')')
for val in audusd_ticks[:10]:
def rates_Collection(symbol, timeframe, year, mon, day, num):
timezone = pytz.timezone('Etc/UTC')
utc_from = datetime(year, mon, day, tzinfo=timezone)
rates = mt5.copy_rates_from(symbol, Operation.Period(timeframe),
utc_from, num)
return (rates)
import pandas as pd
import matplotlib.pyplot as plt
import time
from datetime import datetime
import MetaTrader5 as mt5
import ta
import sys
while True:
nem=input('nemad ra vared konid : ')
if not mt5.initialize():
print("initialize() failed")
period=50
shakhes = mt5.copy_rates_from("شاخص کل6", mt5.TIMEFRAME_D1, datetime.now(), period)
nemad = mt5.copy_rates_from(nem, mt5.TIMEFRAME_D1, datetime.now(), period)
mt5.shutdown()
df = pd.DataFrame(nemad)
ds = pd.DataFrame(shakhes)
print(nem,list(df.columns))
df['time'] = pd.to_datetime(df['time'], unit='s')
dfp = df["close"]
dsp = ds["close"]
