71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
import pandas as pd
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import MetaTrader5 as mt5
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import logging
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class MT5:
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"""
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A class to connect to and interface with MetaTrader 5
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"""
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def __init__(self):
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# Connect to MetaTrader5. Opens if not already open.
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# Logger
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self.log = logging.getLogger(__name__)
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# Open MT5 and log error if it could not open
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if not mt5.initialize():
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self.log.error("initialize() failed")
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mt5.shutdown()
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# Print connection status
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self.log.debug(mt5.terminal_info())
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# Print data on MetaTrader 5 version
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self.log.debug(mt5.version())
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def __del__(self):
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# shut down connection to the MetaTrader 5 terminal
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mt5.shutdown()
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def get_symbols(self):
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"""
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Gets list of symbols open in MT5 market watch.
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:return: list of symbols
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"""
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# Iterate symbols and get those in market watch.
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symbols = mt5.symbols_get()
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selected_symbols = []
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for symbol in symbols:
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if symbol.visible:
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selected_symbols.append(symbol)
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# Log symbol counts
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total_symbols = mt5.symbols_total()
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num_selected_symbols = len(selected_symbols)
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self.log.info(f"{num_selected_symbols} of {total_symbols} available symbols in Market Watch.")
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return selected_symbols
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def get_prices(self, symbol, from_date, to_date):
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"""
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Gets the 1 weeks of M15 OHLC price data for the specified symbol.
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:param symbol: The MT5 symbol to get the price data for
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:param from_date: Date from when to retrieve data
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:param to_date: Date where to receive data to
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:return: Price data for symbol as dataframe
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"""
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# Get prices from MT5
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prices = mt5.copy_rates_range(symbol.name, mt5.TIMEFRAME_M15, from_date, to_date)
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self.log.info(f"{len(prices)} prices retrieved for {symbol.name}.")
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# Create dataframe from data and convert time in seconds to datetime format
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prices_dataframe = pd.DataFrame(prices)
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prices_dataframe['time'] = pd.to_datetime(prices_dataframe['time'], unit='s')
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return prices_dataframe
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