add BacktestresultTuple
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xmatthias
parent
c1b2e06eda
commit
9c57d3aa8b
@ -6,7 +6,7 @@ This module contains the backtesting logic
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import logging
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import operator
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from argparse import Namespace
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from typing import Dict, Tuple, Any, List, Optional
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from typing import Dict, Tuple, Any, List, Optional, NamedTuple
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import arrow
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from pandas import DataFrame
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@ -23,6 +23,18 @@ from freqtrade.persistence import Trade
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logger = logging.getLogger(__name__)
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class BacktestResult(NamedTuple):
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"""
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NamedTuple Defining BacktestResults inputs.
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"""
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pair: str
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profit_percent: float
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profit_abs: float
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open_time: float
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close_time: float
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trade_duration: float
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class Backtesting(object):
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"""
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Backtesting class, this class contains all the logic to run a backtest
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@ -73,15 +85,15 @@ class Backtesting(object):
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headers = ['pair', 'buy count', 'avg profit %',
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'total profit ' + stake_currency, 'avg duration', 'profit', 'loss']
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for pair in data:
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result = results[results.currency == pair]
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result = results[results.pair == pair]
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tabular_data.append([
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pair,
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len(result.index),
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result.profit_percent.mean() * 100.0,
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result.profit_BTC.sum(),
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result.duration.mean(),
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len(result[result.profit_BTC > 0]),
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len(result[result.profit_BTC < 0])
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result.profit_abs.sum(),
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result.trade_duration.mean(),
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len(result[result.profit_abs > 0]),
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len(result[result.profit_abs < 0])
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])
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# Append Total
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@ -89,16 +101,16 @@ class Backtesting(object):
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'TOTAL',
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len(results.index),
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results.profit_percent.mean() * 100.0,
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results.profit_BTC.sum(),
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results.duration.mean(),
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len(results[results.profit_BTC > 0]),
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len(results[results.profit_BTC < 0])
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results.profit_abs.sum(),
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results.trade_duration.mean(),
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len(results[results.profit_abs > 0]),
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len(results[results.profit_abs < 0])
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])
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return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="pipe")
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def _get_sell_trade_entry(
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self, pair: str, buy_row: DataFrame,
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partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[Tuple]:
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partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[BacktestResult]:
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stake_amount = args['stake_amount']
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max_open_trades = args.get('max_open_trades', 0)
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@ -121,28 +133,27 @@ class Backtesting(object):
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buy_signal = sell_row.buy
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if self.analyze.should_sell(trade, sell_row.close, sell_row.date, buy_signal,
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sell_row.sell):
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return \
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sell_row, \
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(
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pair,
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trade.calc_profit_percent(rate=sell_row.close),
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trade.calc_profit(rate=sell_row.close),
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(sell_row.date - buy_row.date).seconds // 60
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)
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return BacktestResult(pair=pair,
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profit_percent=trade.calc_profit_percent(rate=sell_row.close),
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profit_abs=trade.calc_profit(rate=sell_row.close),
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open_time=buy_row.date,
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close_time=sell_row.date,
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trade_duration=(sell_row.date - buy_row.date).seconds // 60
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)
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if partial_ticker:
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# no sell condition found - trade stil open at end of backtest period
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sell_row = partial_ticker[-1]
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logger.info('Force_selling still open trade %s with %s perc - %s', pair,
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trade.calc_profit_percent(rate=sell_row.close),
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trade.calc_profit(rate=sell_row.close))
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return \
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sell_row, \
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(
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pair,
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trade.calc_profit_percent(rate=sell_row.close),
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trade.calc_profit(rate=sell_row.close),
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(sell_row.date - buy_row.date).seconds // 60
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)
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btr = BacktestResult(pair=pair,
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profit_percent=trade.calc_profit_percent(rate=sell_row.close),
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profit_abs=trade.calc_profit(rate=sell_row.close),
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open_time=buy_row.date,
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close_time=sell_row.date,
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trade_duration=(sell_row.date - buy_row.date).seconds // 60
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)
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logger.info('Force_selling still open trade %s with %s perc - %s', btr.pair,
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btr.profit_percent, btr.profit_abs)
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return btr
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return None
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def backtest(self, args: Dict) -> DataFrame:
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@ -202,20 +213,19 @@ class Backtesting(object):
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trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
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ret = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
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trade_count_lock, args)
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trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
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trade_count_lock, args)
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if ret:
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row2, trade_entry = ret
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lock_pair_until = row2.date
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if trade_entry:
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lock_pair_until = trade_entry.close_time
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trades.append(trade_entry)
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if record:
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# Note, need to be json.dump friendly
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# record a tuple of pair, current_profit_percent,
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# entry-date, duration
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records.append((pair, trade_entry[1],
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row.date.strftime('%s'),
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row2.date.strftime('%s'),
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records.append((pair, trade_entry.profit_percent,
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trade_entry.open_time.strftime('%s'),
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trade_entry.close_time.strftime('%s'),
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index, trade_entry[3]))
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else:
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# Set lock_pair_until to end of testing period if trade could not be closed
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@ -228,7 +238,7 @@ class Backtesting(object):
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logger.info('Dumping backtest results to %s', recordfilename)
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file_dump_json(recordfilename, records)
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labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
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return DataFrame.from_records(trades, columns=labels)
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return DataFrame.from_records(trades, columns=BacktestResult._fields)
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def start(self) -> None:
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"""
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