lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

Extract generate_text_table from backtesting class

Browse Source
This commit is contained in:
Matthias 2020-01-02 07:26:43 +01:00
parent 3327ebf2b1
commit 18a53f4467
3 changed files with 68 additions and 54 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

53
freqtrade/optimize/backtest_reports.py Normal file
View File

@ -0,0 +1,53 @@
from datetime import timedelta
from typing import Dict
from pandas import DataFrame
from tabulate import tabulate
def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
results: DataFrame, skip_nan: bool = False) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:return: pretty printed table with tabulate as str
"""
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
'profit', 'loss']
for pair in data:
result = results[results.pair == pair]
if skip_nan and result.profit_abs.isnull().all():
continue
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_percent.sum() * 100.0,
result.profit_abs.sum(),
result.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
tabular_data.append([
'TOTAL',
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore

60
freqtrade/optimize/backtesting.py
View File

@ -14,6 +14,7 @@ from tabulate import tabulate
from freqtrade.configuration import (TimeRange, remove_credentials,
validate_config_consistency)
from freqtrade.optimize.backtest_reports import generate_text_table
from freqtrade.data import history
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
@ -129,55 +130,6 @@ class Backtesting:
return data, timerange
def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame,
skip_nan: bool = False) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:return: pretty printed table with tabulate as str
"""
stake_currency = str(self.config.get('stake_currency'))
max_open_trades = self.config.get('max_open_trades')
floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
tabular_data = []
headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
'profit', 'loss']
for pair in data:
result = results[results.pair == pair]
if skip_nan and result.profit_abs.isnull().all():
continue
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_percent.sum() * 100.0,
result.profit_abs.sum(),
result.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
tabular_data.append([
'TOTAL',
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_abs.sum(),
results.profit_percent.sum() * 100.0 / max_open_trades,
str(timedelta(
minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def _generate_text_table_sell_reason(self, data: Dict[str, Dict], results: DataFrame) -> str:
"""
Generate small table outlining Backtest results
@ -509,13 +461,19 @@ class Backtesting:
print(f"Result for strategy {strategy}")
print(' BACKTESTING REPORT '.center(133, '='))
print(self._generate_text_table(data, results))
print(generate_text_table(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results))
print(' SELL REASON STATS '.center(133, '='))
print(self._generate_text_table_sell_reason(data, results))
print(' LEFT OPEN TRADES REPORT '.center(133, '='))
print(self._generate_text_table(data, results.loc[results.open_at_end], True))
print(generate_text_table(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results.loc[results.open_at_end], skip_nan=True))
print()
if len(all_results) > 1:
# Print Strategy summary table

9
tests/optimize/test_backtesting.py
View File

@ -19,6 +19,7 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import get_timerange
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.optimize import setup_configuration, start_backtesting
from freqtrade.optimize.backtest_reports import generate_text_table
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.state import RunMode
from freqtrade.strategy.default_strategy import DefaultStrategy
@ -360,8 +361,8 @@ def test_tickerdata_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
def test_generate_text_table(default_conf, mocker):
patch_exchange(mocker)
default_conf['max_open_trades'] = 2
backtesting = Backtesting(default_conf)
# default_conf['max_open_trades'] = 2
# backtesting = Backtesting(default_conf)
results = pd.DataFrame(
{
@ -384,7 +385,9 @@ def test_generate_text_table(default_conf, mocker):
'| TOTAL | 2 | 15.00 | 30.00 | '
'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |'
)
assert backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results) == result_str
assert generate_text_table(data={'ETH/BTC': {}},
stake_currency='BTC', max_open_trades=2,
results=results) == result_str
def test_generate_text_table_sell_reason(default_conf, mocker):