144 lines
4.0 KiB
Python
Executable File
144 lines
4.0 KiB
Python
Executable File
#!/usr/bin/env python3
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import sys
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import logging
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from plotly import tools
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from plotly.offline import plot
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import plotly.graph_objs as go
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from freqtrade import exchange, analyze
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from freqtrade.strategy.strategy import Strategy
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import freqtrade.misc as misc
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import freqtrade.optimize as optimize
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logger = logging.getLogger(__name__)
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def plot_parse_args(args):
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parser = misc.common_args_parser('Graph dataframe')
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misc.backtesting_options(parser)
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misc.scripts_options(parser)
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return parser.parse_args(args)
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def plot_analyzed_dataframe(args) -> None:
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"""
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Calls analyze() and plots the returned dataframe
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:param pair: pair as str
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:return: None
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"""
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pair = args.pair.replace('-', '_')
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timerange = misc.parse_timerange(args.timerange)
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# Init strategy
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strategy = Strategy()
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strategy.init({'strategy': args.strategy})
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tick_interval = strategy.ticker_interval
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tickers = {}
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if args.live:
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logger.info('Downloading pair.')
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# Init Bittrex to use public API
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exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
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tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
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else:
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tickers = optimize.load_data(args.datadir, pairs=[pair],
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ticker_interval=tick_interval,
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refresh_pairs=False,
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timerange=timerange)
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dataframes = optimize.tickerdata_to_dataframe(tickers)
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dataframe = dataframes[pair]
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dataframe = analyze.populate_buy_trend(dataframe)
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dataframe = analyze.populate_sell_trend(dataframe)
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if (len(dataframe.index) > 750):
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logger.warn('Ticker contained more than 750 candles, clipping.')
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df = dataframe.tail(750)
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candles = go.Candlestick(x=df.date,
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open=df.open,
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high=df.high,
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low=df.low,
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close=df.close,
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name='Price')
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df_buy = df[df['buy'] == 1]
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buys = go.Scattergl(
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x=df_buy.date,
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y=df_buy.close,
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mode='markers',
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name='buy',
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marker=dict(
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symbol='triangle-up-dot',
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size=9,
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line=dict(
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width=1,
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),
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color='green',
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)
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)
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df_sell = df[df['sell'] == 1]
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sells = go.Scattergl(
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x=df_sell.date,
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y=df_sell.close,
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mode='markers',
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name='sell',
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marker=dict(
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symbol='triangle-down-dot',
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size=9,
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line=dict(
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width=1,
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),
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color='red',
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)
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)
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bb_lower = go.Scatter(
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x=df.date,
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y=df.bb_lowerband,
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name='BB lower',
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line={'color': "transparent"},
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)
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bb_upper = go.Scatter(
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x=df.date,
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y=df.bb_upperband,
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name='BB upper',
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fill="tonexty",
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fillcolor="rgba(0,176,246,0.2)",
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line={'color': "transparent"},
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)
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macd = go.Scattergl(x=df['date'], y=df['macd'], name='MACD')
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macdsignal = go.Scattergl(x=df['date'], y=df['macdsignal'], name='MACD signal')
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volume = go.Bar(x=df['date'], y=df['volume'], name='Volume')
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fig = tools.make_subplots(
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rows=3,
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cols=1,
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shared_xaxes=True,
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row_width=[1, 1, 4],
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vertical_spacing=0.0001,
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)
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fig.append_trace(candles, 1, 1)
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fig.append_trace(bb_lower, 1, 1)
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fig.append_trace(bb_upper, 1, 1)
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fig.append_trace(buys, 1, 1)
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fig.append_trace(sells, 1, 1)
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fig.append_trace(volume, 2, 1)
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fig.append_trace(macd, 3, 1)
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fig.append_trace(macdsignal, 3, 1)
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fig['layout'].update(title=args.pair)
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fig['layout']['yaxis1'].update(title='Price')
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fig['layout']['yaxis2'].update(title='Volume')
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fig['layout']['yaxis3'].update(title='MACD')
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plot(fig, filename='freqtrade-plot.html')
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if __name__ == '__main__':
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args = plot_parse_args(sys.argv[1:])
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plot_analyzed_dataframe(args)
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