#!/usr/bin/env python3 """ Script to display when the bot will buy a specific pair Mandatory Cli parameters: -p / --pair: pair to examine Optional Cli parameters -s / --strategy: strategy to use -d / --datadir: path to pair backtest data --timerange: specify what timerange of data to use. -l / --live: Live, to download the latest ticker for the pair """ import logging import sys from argparse import Namespace from typing import List from plotly import tools from plotly.offline import plot import plotly.graph_objs as go from freqtrade.arguments import Arguments from freqtrade.analyze import Analyze from freqtrade import exchange import freqtrade.optimize as optimize logger = logging.getLogger(__name__) def plot_analyzed_dataframe(args: Namespace) -> None: """ Calls analyze() and plots the returned dataframe :return: None """ pair = args.pair.replace('-', '_') timerange = Arguments.parse_timerange(args.timerange) # Init strategy try: analyze = Analyze({'strategy': args.strategy}) except AttributeError: logger.critical( 'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"', args.strategy ) exit() tick_interval = analyze.strategy.ticker_interval tickers = {} if args.live: logger.info('Downloading pair.') # Init Bittrex to use public API exchange.init({'key': '', 'secret': ''}) tickers[pair] = exchange.get_ticker_history(pair, tick_interval) else: tickers = optimize.load_data( datadir=args.datadir, pairs=[pair], ticker_interval=tick_interval, refresh_pairs=False, timerange=timerange ) dataframes = analyze.tickerdata_to_dataframe(tickers) dataframe = dataframes[pair] dataframe = analyze.populate_buy_trend(dataframe) dataframe = analyze.populate_sell_trend(dataframe) if len(dataframe.index) > 750: logger.warning('Ticker contained more than 750 candles, clipping.') data = dataframe.tail(750) candles = go.Candlestick( x=data.date, open=data.open, high=data.high, low=data.low, close=data.close, name='Price' ) df_buy = data[data['buy'] == 1] buys = go.Scatter( x=df_buy.date, y=df_buy.close, mode='markers', name='buy', marker=dict( symbol='triangle-up-dot', size=9, line=dict(width=1), color='green', ) ) df_sell = data[data['sell'] == 1] sells = go.Scatter( x=df_sell.date, y=df_sell.close, mode='markers', name='sell', marker=dict( symbol='triangle-down-dot', size=9, line=dict(width=1), color='red', ) ) bb_lower = go.Scatter( x=data.date, y=data.bb_lowerband, name='BB lower', line={'color': "transparent"}, ) bb_upper = go.Scatter( x=data.date, y=data.bb_upperband, name='BB upper', fill="tonexty", fillcolor="rgba(0,176,246,0.2)", line={'color': "transparent"}, ) macd = go.Scattergl(x=data['date'], y=data['macd'], name='MACD') macdsignal = go.Scattergl(x=data['date'], y=data['macdsignal'], name='MACD signal') volume = go.Bar(x=data['date'], y=data['volume'], name='Volume') fig = tools.make_subplots( rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 4], vertical_spacing=0.0001, ) fig.append_trace(candles, 1, 1) fig.append_trace(bb_lower, 1, 1) fig.append_trace(bb_upper, 1, 1) fig.append_trace(buys, 1, 1) fig.append_trace(sells, 1, 1) fig.append_trace(volume, 2, 1) fig.append_trace(macd, 3, 1) fig.append_trace(macdsignal, 3, 1) fig['layout'].update(title=args.pair) fig['layout']['yaxis1'].update(title='Price') fig['layout']['yaxis2'].update(title='Volume') fig['layout']['yaxis3'].update(title='MACD') plot(fig, filename='freqtrade-plot.html') def plot_parse_args(args: List[str]) -> Namespace: """ Parse args passed to the script :param args: Cli arguments :return: args: Array with all arguments """ arguments = Arguments(args, 'Graph dataframe') arguments.scripts_options() arguments.common_args_parser() arguments.optimizer_shared_options(arguments.parser) arguments.backtesting_options(arguments.parser) return arguments.parse_args() def main(sysargv: List[str]) -> None: """ This function will initiate the bot and start the trading loop. :return: None """ logger.info('Starting Plot Dataframe') plot_analyzed_dataframe( plot_parse_args(sysargv) ) if __name__ == '__main__': main(sys.argv[1:])