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Don't use Arrow to get min/max backtest dates

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Matthias
2021-05-06 19:34:10 +02:00
parent 32577cc0cd
commit 4f529fe424
5 changed files with 17 additions and 17 deletions
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4
freqtrade/optimize/backtesting.py
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@@ -456,8 +456,8 @@ class Backtesting:
# Execute backtest and store results
results = self.backtest(
processed=preprocessed,
start_date=min_date.datetime,
end_date=max_date.datetime,
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=self.config.get('position_stacking', False),
enable_protections=self.config.get('enable_protections', False),

6
freqtrade/optimize/hyperopt.py
View File

@@ -273,8 +273,8 @@ class Hyperopt:
bt_results = self.backtesting.backtest(
processed=processed,
start_date=self.min_date.datetime,
end_date=self.max_date.datetime,
start_date=self.min_date,
end_date=self.max_date,
max_open_trades=self.max_open_trades,
position_stacking=self.position_stacking,
enable_protections=self.config.get('enable_protections', False),
@@ -314,7 +314,7 @@ class Hyperopt:
if trade_count >= self.config['hyperopt_min_trades']:
loss = self.calculate_loss(results=backtesting_results['results'],
trade_count=trade_count,
min_date=min_date.datetime, max_date=max_date.datetime,
min_date=min_date, max_date=max_date,
config=self.config, processed=processed)
return {
'loss': loss,

13
freqtrade/optimize/optimize_reports.py
View File

@@ -3,7 +3,6 @@ from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Dict, List, Union
from arrow import Arrow
from numpy import int64
from pandas import DataFrame
from tabulate import tabulate
@@ -259,7 +258,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
def generate_strategy_stats(btdata: Dict[str, DataFrame],
strategy: str,
content: Dict[str, Any],
min_date: Arrow, max_date: Arrow,
min_date: datetime, max_date: datetime,
market_change: float
) -> Dict[str, Any]:
"""
@@ -314,10 +313,10 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'profit_median': results['profit_ratio'].median() if len(results) > 0 else 0,
'profit_total': results['profit_abs'].sum() / starting_balance,
'profit_total_abs': results['profit_abs'].sum(),
'backtest_start': min_date.datetime,
'backtest_start_ts': min_date.int_timestamp * 1000,
'backtest_end': max_date.datetime,
'backtest_end_ts': max_date.int_timestamp * 1000,
'backtest_start': min_date,
'backtest_start_ts': int(min_date.timestamp() * 1000),
'backtest_end': max_date,
'backtest_end_ts': int(max_date.timestamp() * 1000),
'backtest_days': backtest_days,
'backtest_run_start_ts': content['backtest_start_time'],
@@ -397,7 +396,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
def generate_backtest_stats(btdata: Dict[str, DataFrame],
all_results: Dict[str, Dict[str, Union[DataFrame, Dict]]],
min_date: Arrow, max_date: Arrow
min_date: datetime, max_date: datetime
) -> Dict[str, Any]:
"""
:param btdata: Backtest data