176 lines
6.6 KiB
Python
176 lines
6.6 KiB
Python
from datetime import timedelta
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from typing import Dict
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from pandas import DataFrame
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from tabulate import tabulate
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def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
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results: DataFrame, skip_nan: bool = False) -> str:
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"""
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Generates and returns a text table for the given backtest data and the results dataframe
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:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
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:param stake_currency: stake-currency - used to correctly name headers
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:param max_open_trades: Maximum allowed open trades
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:param results: Dataframe containing the backtest results
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:param skip_nan: Print "left open" open trades
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:return: pretty printed table with tabulate as string
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"""
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floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
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tabular_data = []
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headers = [
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'Pair',
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'Buys',
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'Avg Profit %',
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'Cum Profit %',
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f'Tot Profit {stake_currency}',
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'Tot Profit %',
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'Avg Duration',
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'Wins',
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'Draws',
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'Losses'
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]
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for pair in data:
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result = results[results.pair == pair]
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if skip_nan and result.profit_abs.isnull().all():
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continue
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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_percent.sum() * 100.0,
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result.profit_abs.sum(),
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result.profit_percent.sum() * 100.0 / max_open_trades,
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str(timedelta(
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minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
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len(result[result.profit_abs > 0]),
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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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tabular_data.append([
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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_percent.sum() * 100.0,
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results.profit_abs.sum(),
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results.profit_percent.sum() * 100.0 / max_open_trades,
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str(timedelta(
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minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
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len(results[results.profit_abs > 0]),
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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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# Ignore type as floatfmt does allow tuples but mypy does not know that
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return tabulate(tabular_data, headers=headers,
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floatfmt=floatfmt, tablefmt="pipe") # type: ignore
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def generate_text_table_sell_reason(
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data: Dict[str, Dict], stake_currency: str, max_open_trades: int, results: DataFrame
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) -> str:
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"""
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Generate small table outlining Backtest results
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:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
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:param results: Dataframe containing the backtest results
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:return: pretty printed table with tabulate as string
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"""
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tabular_data = []
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headers = [
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"Sell Reason",
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"Sells",
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"Wins",
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"Draws",
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"Losses",
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"Avg Profit %",
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"Cum Profit %",
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f"Tot Profit {stake_currency}",
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"Tot Profit %",
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]
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for reason, count in results['sell_reason'].value_counts().iteritems():
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result = results.loc[results['sell_reason'] == reason]
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wins = len(result[result['profit_abs'] > 0])
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draws = len(result[result['profit_abs'] == 0])
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loss = len(result[result['profit_abs'] < 0])
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profit_mean = round(result['profit_percent'].mean() * 100.0, 2)
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profit_sum = round(result["profit_percent"].sum() * 100.0, 2)
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profit_tot = result['profit_abs'].sum()
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profit_percent_tot = round(result['profit_percent'].sum() * 100.0 / max_open_trades, 2)
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tabular_data.append(
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[
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reason.value,
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count,
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wins,
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draws,
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loss,
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profit_mean,
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profit_sum,
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profit_tot,
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profit_percent_tot,
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]
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)
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return tabulate(tabular_data, headers=headers, tablefmt="pipe")
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def generate_text_table_strategy(stake_currency: str, max_open_trades: str,
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all_results: Dict) -> str:
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"""
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Generate summary table per strategy
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:param stake_currency: stake-currency - used to correctly name headers
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:param max_open_trades: Maximum allowed open trades used for backtest
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:param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
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:return: pretty printed table with tabulate as string
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"""
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floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
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tabular_data = []
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headers = ['Strategy', 'Buys', 'Avg Profit %', 'Cum Profit %',
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f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
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'Wins', 'Draws', 'Losses']
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for strategy, results in all_results.items():
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tabular_data.append([
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strategy,
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len(results.index),
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results.profit_percent.mean() * 100.0,
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results.profit_percent.sum() * 100.0,
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results.profit_abs.sum(),
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results.profit_percent.sum() * 100.0 / max_open_trades,
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str(timedelta(
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minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
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len(results[results.profit_abs > 0]),
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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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# Ignore type as floatfmt does allow tuples but mypy does not know that
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return tabulate(tabular_data, headers=headers,
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floatfmt=floatfmt, tablefmt="pipe") # type: ignore
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def generate_edge_table(results: dict) -> str:
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floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
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tabular_data = []
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headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio',
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'Required Risk Reward', 'Expectancy', 'Total Number of Trades',
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'Average Duration (min)']
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for result in results.items():
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if result[1].nb_trades > 0:
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tabular_data.append([
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result[0],
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result[1].stoploss,
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result[1].winrate,
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result[1].risk_reward_ratio,
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result[1].required_risk_reward,
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result[1].expectancy,
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result[1].nb_trades,
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round(result[1].avg_trade_duration)
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])
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# Ignore type as floatfmt does allow tuples but mypy does not know that
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return tabulate(tabular_data, headers=headers,
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floatfmt=floatfmt, tablefmt="pipe") # type: ignore
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