Reinstate df - which was removed in #1287

scripts/plot_dataframe.py

@@ -0,0 +1,381 @@
+#!/usr/bin/env python3
+"""
+Script to display when the bot will buy a specific pair
+
+Mandatory Cli parameters:
+-p / --pair: pair to examine
+
+Option but recommended
+-s / --strategy: strategy to use
+
+
+Optional Cli parameters
+-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
+-db / --db-url: Show trades stored in database
+
+
+Indicators recommended
+Row 1: sma, ema3, ema5, ema10, ema50
+Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk
+
+Example of usage:
+> python3 scripts/plot_dataframe.py --pair BTC/EUR -d user_data/data/ --indicators1 sma,ema3
+--indicators2 fastk,fastd
+"""
+import json
+import logging
+import sys
+from argparse import Namespace
+from pathlib import Path
+from typing import Dict, List, Any
+
+import pandas as pd
+import plotly.graph_objs as go
+import pytz
+
+from plotly import tools
+from plotly.offline import plot
+
+import freqtrade.optimize as optimize
+from freqtrade import persistence
+from freqtrade.arguments import Arguments, TimeRange
+from freqtrade.exchange import Exchange
+from freqtrade.optimize.backtesting import setup_configuration
+from freqtrade.persistence import Trade
+from freqtrade.strategy.resolver import StrategyResolver
+
+logger = logging.getLogger(__name__)
+_CONF: Dict[str, Any] = {}
+
+timeZone = pytz.UTC
+
+
+def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame:
+    trades: pd.DataFrame = pd.DataFrame()
+    if args.db_url:
+        persistence.init(_CONF)
+        columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
+
+        for x in Trade.query.all():
+            print("date: {}".format(x.open_date))
+
+        trades = pd.DataFrame([(t.pair, t.calc_profit(),
+                                t.open_date.replace(tzinfo=timeZone),
+                                t.close_date.replace(tzinfo=timeZone) if t.close_date else None,
+                                t.open_rate, t.close_rate,
+                                t.close_date.timestamp() - t.open_date.timestamp() if t.close_date else None)
+                               for t in Trade.query.filter(Trade.pair.is_(pair)).all()],
+                              columns=columns)
+
+    elif args.exportfilename:
+        file = Path(args.exportfilename)
+        # must align with columns in backtest.py
+        columns = ["pair", "profit", "opents", "closets", "index", "duration",
+                   "open_rate", "close_rate", "open_at_end", "sell_reason"]
+        with file.open() as f:
+            data = json.load(f)
+            trades = pd.DataFrame(data, columns=columns)
+        trades = trades.loc[trades["pair"] == pair]
+        if timerange:
+            if timerange.starttype == 'date':
+                trades = trades.loc[trades["opents"] >= timerange.startts]
+            if timerange.stoptype == 'date':
+                trades = trades.loc[trades["opents"] <= timerange.stopts]
+
+        trades['opents'] = pd.to_datetime(trades['opents'],
+                                          unit='s',
+                                          utc=True,
+                                          infer_datetime_format=True)
+        trades['closets'] = pd.to_datetime(trades['closets'],
+                                           unit='s',
+                                           utc=True,
+                                           infer_datetime_format=True)
+    return trades
+
+
+def plot_analyzed_dataframe(args: Namespace) -> None:
+    """
+    Calls analyze() and plots the returned dataframe
+    :return: None
+    """
+    global _CONF
+
+    # Load the configuration
+    _CONF.update(setup_configuration(args))
+
+    print(_CONF)
+    # Set the pair to audit
+    pair = args.pair
+
+    if pair is None:
+        logger.critical('Parameter --pair mandatory;. E.g --pair ETH/BTC')
+        exit()
+
+    if '/' not in pair:
+        logger.critical('--pair format must be XXX/YYY')
+        exit()
+
+    # Set timerange to use
+    timerange = Arguments.parse_timerange(args.timerange)
+
+    # Load the strategy
+    try:
+        strategy = StrategyResolver(_CONF).strategy
+        exchange = Exchange(_CONF)
+    except AttributeError:
+        logger.critical(
+            'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
+            args.strategy
+        )
+        exit()
+
+    # Set the ticker to use
+    tick_interval = strategy.ticker_interval
+
+    # Load pair tickers
+    tickers = {}
+    if args.live:
+        logger.info('Downloading pair.')
+        exchange.refresh_tickers([pair], tick_interval)
+        tickers[pair] = exchange.klines[pair]
+    else:
+        tickers = optimize.load_data(
+            datadir=_CONF.get("datadir"),
+            pairs=[pair],
+            ticker_interval=tick_interval,
+            refresh_pairs=_CONF.get('refresh_pairs', False),
+            timerange=timerange,
+            exchange=Exchange(_CONF)
+        )
+
+        # No ticker found, or impossible to download
+        if tickers == {}:
+            exit()
+
+    # Get trades already made from the DB
+    trades = load_trades(args, pair, timerange)
+
+    dataframes = strategy.tickerdata_to_dataframe(tickers)
+
+    dataframe = dataframes[pair]
+    dataframe = strategy.advise_buy(dataframe, {'pair': pair})
+    dataframe = strategy.advise_sell(dataframe, {'pair': pair})
+
+    if len(dataframe.index) > args.plot_limit:
+        logger.warning('Ticker contained more than %s candles as defined '
+                       'with --plot-limit, clipping.', args.plot_limit)
+    dataframe = dataframe.tail(args.plot_limit)
+
+    trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']]
+    fig = generate_graph(
+        pair=pair,
+        trades=trades,
+        data=dataframe,
+        args=args
+    )
+
+    plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')))
+
+
+def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots:
+    """
+    Generate the graph from the data generated by Backtesting or from DB
+    :param pair: Pair to Display on the graph
+    :param trades: All trades created
+    :param data: Dataframe
+    :param args: sys.argv that contrains the two params indicators1, and indicators2
+    :return: None
+    """
+
+    # Define the graph
+    fig = tools.make_subplots(
+        rows=3,
+        cols=1,
+        shared_xaxes=True,
+        row_width=[1, 1, 4],
+        vertical_spacing=0.0001,
+    )
+    fig['layout'].update(title=pair)
+    fig['layout']['yaxis1'].update(title='Price')
+    fig['layout']['yaxis2'].update(title='Volume')
+    fig['layout']['yaxis3'].update(title='Other')
+
+    # Common information
+    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.Scattergl(
+        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.Scattergl(
+        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',
+        )
+    )
+
+    trade_buys = go.Scattergl(
+        x=trades["opents"],
+        y=trades["open_rate"],
+        mode='markers',
+        name='trade_buy',
+        marker=dict(
+            symbol='square-open',
+            size=11,
+            line=dict(width=2),
+            color='green'
+        )
+    )
+    trade_sells = go.Scattergl(
+        x=trades["closets"],
+        y=trades["close_rate"],
+        mode='markers',
+        name='trade_sell',
+        marker=dict(
+            symbol='square-open',
+            size=11,
+            line=dict(width=2),
+            color='red'
+        )
+    )
+
+    # Row 1
+    fig.append_trace(candles, 1, 1)
+
+    if 'bb_lowerband' in data and 'bb_upperband' in data:
+        bb_lower = go.Scatter(
+            x=data.date,
+            y=data.bb_lowerband,
+            name='BB lower',
+            line={'color': 'rgba(255,255,255,0)'},
+        )
+        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': 'rgba(255,255,255,0)'},
+        )
+        fig.append_trace(bb_lower, 1, 1)
+        fig.append_trace(bb_upper, 1, 1)
+
+    fig = generate_row(fig=fig, row=1, raw_indicators=args.indicators1, data=data)
+    fig.append_trace(buys, 1, 1)
+    fig.append_trace(sells, 1, 1)
+    fig.append_trace(trade_buys, 1, 1)
+    fig.append_trace(trade_sells, 1, 1)
+
+    # Row 2
+    volume = go.Bar(
+        x=data['date'],
+        y=data['volume'],
+        name='Volume'
+    )
+    fig.append_trace(volume, 2, 1)
+
+    # Row 3
+    fig = generate_row(fig=fig, row=3, raw_indicators=args.indicators2, data=data)
+
+    return fig
+
+
+def generate_row(fig, row, raw_indicators, data) -> tools.make_subplots:
+    """
+    Generator all the indicator selected by the user for a specific row
+    """
+    for indicator in raw_indicators.split(','):
+        if indicator in data:
+            scattergl = go.Scattergl(
+                x=data['date'],
+                y=data[indicator],
+                name=indicator
+            )
+            fig.append_trace(scattergl, row, 1)
+        else:
+            logger.info(
+                'Indicator "%s" ignored. Reason: This indicator is not found '
+                'in your strategy.',
+                indicator
+            )
+
+    return fig
+
+
+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.parser.add_argument(
+        '--indicators1',
+        help='Set indicators from your strategy you want in the first row of the graph. Separate '
+             'them with a coma. E.g: ema3,ema5 (default: %(default)s)',
+        type=str,
+        default='sma,ema3,ema5',
+        dest='indicators1',
+    )
+
+    arguments.parser.add_argument(
+        '--indicators2',
+        help='Set indicators from your strategy you want in the third row of the graph. Separate '
+             'them with a coma. E.g: fastd,fastk (default: %(default)s)',
+        type=str,
+        default='macd',
+        dest='indicators2',
+    )
+    arguments.parser.add_argument(
+        '--plot-limit',
+        help='Specify tick limit for plotting - too high values cause huge files - '
+             'Default: %(default)s',
+        dest='plot_limit',
+        default=750,
+        type=int,
+    )
+    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:])