Make plot_dataframe able to show trades stored in database. (#692)
* Show trades stored in db on the graph
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@ -43,6 +43,10 @@ python scripts/plot_dataframe.py -p BTC_ETH --timerange=100-200
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```
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Timerange doesn't work with live data.
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To plot trades stored in a database use `--db-url` argument:
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```
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python scripts/plot_dataframe.py --db-url tradesv3.dry_run.sqlite -p BTC_ETH
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```
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## Plot profit
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@ -260,6 +260,13 @@ class Arguments(object):
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default=None
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)
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self.parser.add_argument(
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'-db', '--db-url',
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help='Show trades stored in database.',
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dest='db_url',
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default=None
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)
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def testdata_dl_options(self) -> None:
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"""
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Parses given arguments for testdata download
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@ -10,6 +10,7 @@ Optional Cli parameters
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-d / --datadir: path to pair backtest data
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--timerange: specify what timerange of data to use.
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-l / --live: Live, to download the latest ticker for the pair
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-db / --db-url: Show trades stored in database
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"""
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import logging
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import sys
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@ -21,13 +22,18 @@ 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 typing import Dict, List, Any
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from sqlalchemy import create_engine
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from freqtrade.arguments import Arguments
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from freqtrade.analyze import Analyze
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from freqtrade import exchange
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import freqtrade.optimize as optimize
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from freqtrade import persistence
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from freqtrade.persistence import Trade
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logger = logging.getLogger(__name__)
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_CONF: Dict[str, Any] = {}
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def plot_analyzed_dataframe(args: Namespace) -> None:
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"""
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@ -68,6 +74,12 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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dataframe = analyze.populate_buy_trend(dataframe)
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dataframe = analyze.populate_sell_trend(dataframe)
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trades = []
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if args.db_url:
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engine = create_engine('sqlite:///' + args.db_url)
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persistence.init(_CONF, engine)
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trades = Trade.query.filter(Trade.pair.is_(pair)).all()
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if len(dataframe.index) > 750:
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logger.warning('Ticker contained more than 750 candles, clipping.')
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data = dataframe.tail(750)
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@ -108,6 +120,31 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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)
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)
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trade_buys = go.Scattergl(
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x=[t.open_date.isoformat() for t in trades],
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y=[t.open_rate for t in trades],
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mode='markers',
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name='trade_buy',
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marker=dict(
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symbol='square-open',
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size=11,
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line=dict(width=2),
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color='green'
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)
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)
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trade_sells = go.Scattergl(
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x=[t.close_date.isoformat() for t in trades],
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y=[t.close_rate for t in trades],
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mode='markers',
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name='trade_sell',
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marker=dict(
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symbol='square-open',
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size=11,
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line=dict(width=2),
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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=data.date,
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y=data.bb_lowerband,
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@ -142,6 +179,8 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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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.append_trace(trade_buys, 1, 1)
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fig.append_trace(trade_sells, 1, 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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