Merge pull request #2730 from freqtrade/extract_bt_reporting
Extract backtest reporting
This commit is contained in:
Matthias
GitHub
107
freqtrade/optimize/backtest_reports.py
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107
freqtrade/optimize/backtest_reports.py
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@@ -0,0 +1,107 @@
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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 = ['pair', 'buy count', 'avg profit %', 'cum profit %',
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f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
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'profit', 'loss']
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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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])
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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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])
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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(data: Dict[str, Dict], results: DataFrame) -> 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 = ['Sell Reason', 'Count', 'Profit', 'Loss']
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for reason, count in results['sell_reason'].value_counts().iteritems():
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profit = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] >= 0)])
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loss = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] < 0)])
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tabular_data.append([reason.value, count, profit, loss])
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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', 'buy count', 'avg profit %', 'cum profit %',
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f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
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'profit', 'loss']
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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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])
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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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@@ -10,7 +10,6 @@ from pathlib import Path
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from typing import Any, Dict, List, NamedTuple, Optional
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from pandas import DataFrame
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from tabulate import tabulate
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from freqtrade.configuration import (TimeRange, remove_credentials,
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validate_config_consistency)
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@@ -19,6 +18,9 @@ from freqtrade.data.dataprovider import DataProvider
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
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from freqtrade.misc import file_dump_json
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from freqtrade.optimize.backtest_reports import (
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generate_text_table, generate_text_table_sell_reason,
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generate_text_table_strategy)
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from freqtrade.persistence import Trade
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from freqtrade.resolvers import ExchangeResolver, StrategyResolver
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from freqtrade.state import RunMode
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@@ -129,96 +131,6 @@ class Backtesting:
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return data, timerange
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def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame,
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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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:return: pretty printed table with tabulate as str
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"""
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stake_currency = str(self.config.get('stake_currency'))
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max_open_trades = self.config.get('max_open_trades')
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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 = ['pair', 'buy count', 'avg profit %', 'cum profit %',
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'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
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'profit', 'loss']
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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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])
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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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])
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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(self, data: Dict[str, Dict], results: DataFrame) -> str:
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"""
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Generate small table outlining Backtest results
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"""
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tabular_data = []
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headers = ['Sell Reason', 'Count', 'Profit', 'Loss']
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for reason, count in results['sell_reason'].value_counts().iteritems():
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profit = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] >= 0)])
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loss = len(results[(results['sell_reason'] == reason) & (results['profit_abs'] < 0)])
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tabular_data.append([reason.value, count, profit, loss])
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return tabulate(tabular_data, headers=headers, tablefmt="pipe")
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def _generate_text_table_strategy(self, all_results: dict) -> str:
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"""
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Generate summary table per strategy
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"""
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stake_currency = str(self.config.get('stake_currency'))
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max_open_trades = self.config.get('max_open_trades')
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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', 'buy count', 'avg profit %', 'cum profit %',
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'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
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'profit', 'loss']
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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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])
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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 _store_backtest_result(self, recordfilename: Path, results: DataFrame,
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strategyname: Optional[str] = None) -> None:
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@@ -509,16 +421,24 @@ class Backtesting:
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print(f"Result for strategy {strategy}")
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print(' BACKTESTING REPORT '.center(133, '='))
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print(self._generate_text_table(data, results))
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print(generate_text_table(data,
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stake_currency=self.config['stake_currency'],
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max_open_trades=self.config['max_open_trades'],
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results=results))
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print(' SELL REASON STATS '.center(133, '='))
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print(self._generate_text_table_sell_reason(data, results))
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print(generate_text_table_sell_reason(data, results))
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print(' LEFT OPEN TRADES REPORT '.center(133, '='))
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print(self._generate_text_table(data, results.loc[results.open_at_end], True))
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print(generate_text_table(data,
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stake_currency=self.config['stake_currency'],
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max_open_trades=self.config['max_open_trades'],
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results=results.loc[results.open_at_end], skip_nan=True))
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print()
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if len(all_results) > 1:
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# Print Strategy summary table
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print(' Strategy Summary '.center(133, '='))
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print(self._generate_text_table_strategy(all_results))
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print(generate_text_table_strategy(self.config['stake_currency'],
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self.config['max_open_trades'],
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all_results=all_results))
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print('\nFor more details, please look at the detail tables above')
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