freqtrade/optimize/optimize_reports/bt_output.py
import logging
from typing import Any, Dict, List
from tabulate import tabulate
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT, Config
from freqtrade.optimize.optimize_reports.optimize_reports import generate_periodic_breakdown_stats
from freqtrade.types import BacktestResultType
from freqtrade.util import decimals_per_coin, fmt_coin
logger = logging.getLogger(__name__)
def _get_line_floatfmt(stake_currency: str) -> List[str]:
"""
Generate floatformat (goes in line with _generate_result_line())
"""
return ['s', 'd', '.2f', f'.{decimals_per_coin(stake_currency)}f',
'.2f', 'd', 's', 's']
def _get_line_header(first_column: str, stake_currency: str,
direction: str = 'Entries') -> List[str]:
"""
Generate header lines (goes in line with _generate_result_line())
"""
return [first_column, direction, 'Avg Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%']
def generate_wins_draws_losses(wins, draws, losses):
if wins > 0 and losses == 0:
wl_ratio = '100'
elif wins == 0:
wl_ratio = '0'
else:
wl_ratio = f'{100.0 / (wins + draws + losses) * wins:.1f}' if losses > 0 else '100'
return f'{wins:>4} {draws:>4} {losses:>4} {wl_ratio:>4}'
def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
headers = _get_line_header('Pair', stake_currency)
floatfmt = _get_line_floatfmt(stake_currency)
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'],
generate_wins_draws_losses(t['wins'], t['draws'], t['losses'])
] for t in pair_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
fallback: str = ''
if (tag_type == "enter_tag"):
headers = _get_line_header("TAG", stake_currency)
else:
headers = _get_line_header("Exit Reason", stake_currency, 'Exits')
fallback = 'exit_reason'
floatfmt = _get_line_floatfmt(stake_currency)
output = [
[
t['key'] if t.get('key') is not None and len(
str(t['key'])) > 0 else t.get(fallback, "OTHER"),
t['trades'],
t['profit_mean_pct'],
t['profit_total_abs'],
t['profit_total_pct'],
t.get('duration_avg'),
generate_wins_draws_losses(
t['wins'],
t['draws'],
t['losses'])] for t in tag_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_periodic_breakdown(days_breakdown_stats: List[Dict[str, Any]],
stake_currency: str, period: str) -> str:
"""
Generate small table with Backtest results by days
:param days_breakdown_stats: Days breakdown metrics
:param stake_currency: Stakecurrency used
:return: pretty printed table with tabulate as string
"""
headers = [
period.capitalize(),
f'Tot Profit {stake_currency}',
'Wins',
'Draws',
'Losses',
]
output = [[
d['date'], fmt_coin(d['profit_abs'], stake_currency, False),
d['wins'], d['draws'], d['loses'],
] for d in days_breakdown_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def text_table_strategy(strategy_results, stake_currency: str) -> str:
"""
Generate summary table per strategy
:param strategy_results: Dict of <Strategyname: DataFrame> containing results for all strategies
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
floatfmt = _get_line_floatfmt(stake_currency)
headers = _get_line_header('Strategy', stake_currency)
# _get_line_header() is also used for per-pair summary. Per-pair drawdown is mostly useless
# therefore we slip this column in only for strategy summary here.
headers.append('Drawdown')
# Align drawdown string on the center two space separator.
if 'max_drawdown_account' in strategy_results[0]:
drawdown = [f'{t["max_drawdown_account"] * 100:.2f}' for t in strategy_results]
else:
# Support for prior backtest results
drawdown = [f'{t["max_drawdown_per"]:.2f}' for t in strategy_results]
dd_pad_abs = max([len(t['max_drawdown_abs']) for t in strategy_results])
dd_pad_per = max([len(dd) for dd in drawdown])
drawdown = [f'{t["max_drawdown_abs"]:>{dd_pad_abs}} {stake_currency} {dd:>{dd_pad_per}}%'
for t, dd in zip(strategy_results, drawdown)]
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'],
generate_wins_draws_losses(t['wins'], t['draws'], t['losses']), drawdown]
for t, drawdown in zip(strategy_results, drawdown)]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_add_metrics(strat_results: Dict) -> str:
if len(strat_results['trades']) > 0:
best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio'])
worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio'])
short_metrics = [
('', ''), # Empty line to improve readability
('Long / Short',
f"{strat_results.get('trade_count_long', 'total_trades')} / "
f"{strat_results.get('trade_count_short', 0)}"),
('Total profit Long %', f"{strat_results['profit_total_long']:.2%}"),
('Total profit Short %', f"{strat_results['profit_total_short']:.2%}"),
('Absolute profit Long', fmt_coin(strat_results['profit_total_long_abs'],
strat_results['stake_currency'])),
('Absolute profit Short', fmt_coin(strat_results['profit_total_short_abs'],
strat_results['stake_currency'])),
] if strat_results.get('trade_count_short', 0) > 0 else []
drawdown_metrics = []
if 'max_relative_drawdown' in strat_results:
# Compatibility to show old hyperopt results
drawdown_metrics.append(
('Max % of account underwater', f"{strat_results['max_relative_drawdown']:.2%}")
)
drawdown_metrics.extend([
('Absolute Drawdown (Account)', f"{strat_results['max_drawdown_account']:.2%}")
if 'max_drawdown_account' in strat_results else (
'Drawdown', f"{strat_results['max_drawdown']:.2%}"),
('Absolute Drawdown', fmt_coin(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', fmt_coin(strat_results['max_drawdown_high'],
strat_results['stake_currency'])),
('Drawdown low', fmt_coin(strat_results['max_drawdown_low'],
strat_results['stake_currency'])),
('Drawdown Start', strat_results['drawdown_start']),
('Drawdown End', strat_results['drawdown_end']),
])
entry_adjustment_metrics = [
('Canceled Trade Entries', strat_results.get('canceled_trade_entries', 'N/A')),
('Canceled Entry Orders', strat_results.get('canceled_entry_orders', 'N/A')),
('Replaced Entry Orders', strat_results.get('replaced_entry_orders', 'N/A')),
] if strat_results.get('canceled_entry_orders', 0) > 0 else []
# Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
# command stores these results and newer version of freqtrade must be able to handle old
# results with missing new fields.
metrics = [
('Backtesting from', strat_results['backtest_start']),
('Backtesting to', strat_results['backtest_end']),
('Max open trades', strat_results['max_open_trades']),
('', ''), # Empty line to improve readability
('Total/Daily Avg Trades',
f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
('Starting balance', fmt_coin(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', fmt_coin(strat_results['final_balance'],
strat_results['stake_currency'])),
('Absolute profit ', fmt_coin(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{strat_results['profit_total']:.2%}"),
('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
('Sortino', f"{strat_results['sortino']:.2f}" if 'sortino' in strat_results else 'N/A'),
('Sharpe', f"{strat_results['sharpe']:.2f}" if 'sharpe' in strat_results else 'N/A'),
('Calmar', f"{strat_results['calmar']:.2f}" if 'calmar' in strat_results else 'N/A'),
('Profit factor', f'{strat_results["profit_factor"]:.2f}' if 'profit_factor'
in strat_results else 'N/A'),
('Expectancy (Ratio)', (
f"{strat_results['expectancy']:.2f} ({strat_results['expectancy_ratio']:.2f})" if
'expectancy_ratio' in strat_results else 'N/A')),
('Trades per day', strat_results['trades_per_day']),
('Avg. daily profit %',
f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
('Avg. stake amount', fmt_coin(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', fmt_coin(strat_results['total_volume'],
strat_results['stake_currency'])),
*short_metrics,
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} "
f"{strat_results['best_pair']['profit_total']:.2%}"),
('Worst Pair', f"{strat_results['worst_pair']['key']} "
f"{strat_results['worst_pair']['profit_total']:.2%}"),
('Best trade', f"{best_trade['pair']} {best_trade['profit_ratio']:.2%}"),
('Worst trade', f"{worst_trade['pair']} "
f"{worst_trade['profit_ratio']:.2%}"),
('Best day', fmt_coin(strat_results['backtest_best_day_abs'],
strat_results['stake_currency'])),
('Worst day', fmt_coin(strat_results['backtest_worst_day_abs'],
strat_results['stake_currency'])),
('Days win/draw/lose', f"{strat_results['winning_days']} / "
f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('Max Consecutive Wins / Loss',
f"{strat_results['max_consecutive_wins']} / {strat_results['max_consecutive_losses']}"
if 'max_consecutive_losses' in strat_results else 'N/A'),
('Rejected Entry signals', strat_results.get('rejected_signals', 'N/A')),
('Entry/Exit Timeouts',
f"{strat_results.get('timedout_entry_orders', 'N/A')} / "
f"{strat_results.get('timedout_exit_orders', 'N/A')}"),
*entry_adjustment_metrics,
('', ''), # Empty line to improve readability
('Min balance', fmt_coin(strat_results['csum_min'], strat_results['stake_currency'])),
('Max balance', fmt_coin(strat_results['csum_max'], strat_results['stake_currency'])),
*drawdown_metrics,
('Market change', f"{strat_results['market_change']:.2%}"),
]
return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
else:
start_balance = fmt_coin(strat_results['starting_balance'], strat_results['stake_currency'])
stake_amount = fmt_coin(
strat_results['stake_amount'], strat_results['stake_currency']
) if strat_results['stake_amount'] != UNLIMITED_STAKE_AMOUNT else 'unlimited'
message = ("No trades made. "
f"Your starting balance was {start_balance}, "
f"and your stake was {stake_amount}."
)
return message
def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str,
backtest_breakdown: List[str]):
"""
Print results for one strategy
"""
# Print results
print(f"Result for strategy {strategy}")
table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency)
if isinstance(table, str):
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if (enter_tags := results.get('results_per_enter_tag')) is not None:
table = text_table_tags("enter_tag", enter_tags, stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' ENTER TAG STATS '.center(len(table.splitlines()[0]), '='))
print(table)
if (exit_reasons := results.get('exit_reason_summary')) is not None:
table = text_table_tags("exit_tag", exit_reasons, stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
for period in backtest_breakdown:
if period in results.get('periodic_breakdown', {}):
days_breakdown_stats = results['periodic_breakdown'][period]
else:
days_breakdown_stats = generate_periodic_breakdown_stats(
trade_list=results['trades'], period=period)
table = text_table_periodic_breakdown(days_breakdown_stats=days_breakdown_stats,
stake_currency=stake_currency, period=period)
if isinstance(table, str) and len(table) > 0:
print(f' {period.upper()} BREAKDOWN '.center(len(table.splitlines()[0]), '='))
print(table)
table = text_table_add_metrics(results)
if isinstance(table, str) and len(table) > 0:
print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '='))
print(table)
if isinstance(table, str) and len(table) > 0:
print('=' * len(table.splitlines()[0]))
print()
def show_backtest_results(config: Config, backtest_stats: BacktestResultType):
stake_currency = config['stake_currency']
for strategy, results in backtest_stats['strategy'].items():
show_backtest_result(
strategy, results, stake_currency,
config.get('backtest_breakdown', []))
if len(backtest_stats['strategy']) > 0:
# Print Strategy summary table
table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
print(f"Backtested {results['backtest_start']} -> {results['backtest_end']} |"
f" Max open trades : {results['max_open_trades']}")
print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
print(table)
print('=' * len(table.splitlines()[0]))
print('\nFor more details, please look at the detail tables above')
def show_sorted_pairlist(config: Config, backtest_stats: BacktestResultType):
if config.get('backtest_show_pair_list', False):
for strategy, results in backtest_stats['strategy'].items():
print(f"Pairs for Strategy {strategy}: \n[")
for result in results['results_per_pair']:
if result["key"] != 'TOTAL':
print(f'"{result["key"]}", // {result["profit_mean"]:.2%}')
print("]")
def generate_edge_table(results: dict) -> str:
floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd')
tabular_data = []
headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio',
'Required Risk Reward', 'Expectancy', 'Total Number of Trades',
'Average Duration (min)']
for result in results.items():
if result[1].nb_trades > 0:
tabular_data.append([
result[0],
result[1].stoploss,
result[1].winrate,
result[1].risk_reward_ratio,
result[1].required_risk_reward,
result[1].expectancy,
result[1].nb_trades,
round(result[1].avg_trade_duration)
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")