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2ed808da1f
freqtrade_origin/tests/optimize/test_optimize_reports.py
Matthias 2ed808da1f Extract .last_result.json to constant
2020-07-03 06:58:27 +02:00

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import re
from pathlib import Path
import pandas as pd
import pytest
from arrow import Arrow
from freqtrade.configuration import TimeRange
from freqtrade.constants import LAST_BT_RESULT_FN
from freqtrade.data import history
from freqtrade.data.btanalysis import get_latest_backtest_filename
from freqtrade.edge import PairInfo
from freqtrade.optimize.optimize_reports import (generate_backtest_stats,
generate_edge_table,
generate_pair_metrics,
generate_sell_reason_stats,
generate_strategy_metrics,
store_backtest_result,
store_backtest_stats,
text_table_bt_results,
text_table_sell_reason,
text_table_strategy)
from freqtrade.strategy.interface import SellType
from tests.conftest import patch_exchange
from tests.data.test_history import _backup_file, _clean_test_file
def test_text_table_bt_results(default_conf, mocker):
results = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2],
'profit_abs': [0.2, 0.4],
'trade_duration': [10, 30],
'wins': [2, 0],
'draws': [0, 0],
'losses': [0, 0]
}
)
result_str = (
'| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |'
' Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'|---------+--------+----------------+----------------+------------------+'
'----------------+----------------+--------+---------+----------|\n'
'| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |\n'
'| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |'
)
pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
max_open_trades=2, results=results)
assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str
def test_generate_backtest_stats(default_conf, testdatadir):
results = {'DefStrat': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
})}
timerange = TimeRange.parse_timerange('1510688220-1510700340')
min_date = Arrow.fromtimestamp(1510688220)
max_date = Arrow.fromtimestamp(1510700340)
btdata = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
stats = generate_backtest_stats(default_conf, btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.datetime
assert strat_stats['backtest_end'] == max_date.datetime
assert strat_stats['total_trades'] == len(results['DefStrat'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown'] == 0.0
results = {'DefStrat': pd.DataFrame(
{"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, -0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
})}
assert strat_stats['max_drawdown'] == 0.0
assert strat_stats['drawdown_start'] == Arrow.fromtimestamp(0).datetime
assert strat_stats['drawdown_end'] == Arrow.fromtimestamp(0).datetime
assert strat_stats['drawdown_end_ts'] == 0
assert strat_stats['drawdown_start_ts'] == 0
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
# Test storing stats
filename = Path(testdatadir / 'btresult.json')
filename_last = Path(testdatadir / LAST_BT_RESULT_FN)
_backup_file(filename_last, copy_file=True)
assert not filename.is_file()
store_backtest_stats(filename, stats)
# get real Filename (it's btresult-<date>.json)
last_fn = get_latest_backtest_filename(filename_last.parent)
assert re.match(r"btresult-.*\.json", last_fn)
filename1 = (testdatadir / last_fn)
assert filename1.is_file()
content = filename1.read_text()
assert 'max_drawdown' in content
assert 'strategy' in content
assert 'pairlist' in content
assert filename_last.is_file()
_clean_test_file(filename_last)
filename1.unlink()
def test_generate_pair_metrics(default_conf, mocker):
results = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2],
'profit_abs': [0.2, 0.4],
'trade_duration': [10, 30],
'wins': [2, 0],
'draws': [0, 0],
'losses': [0, 0]
}
)
pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
max_open_trades=2, results=results)
assert isinstance(pair_results, list)
assert len(pair_results) == 2
assert pair_results[-1]['key'] == 'TOTAL'
assert (
pytest.approx(pair_results[-1]['profit_mean_pct']) == pair_results[-1]['profit_mean'] * 100)
assert (
pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100)
def test_text_table_sell_reason(default_conf):
results = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2, -0.1],
'profit_abs': [0.2, 0.4, -0.2],
'trade_duration': [10, 30, 10],
'wins': [2, 0, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
result_str = (
'| Sell Reason | Sells | Wins | Draws | Losses |'
' Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |\n'
'|---------------+---------+--------+---------+----------+'
'----------------+----------------+------------------+----------------|\n'
'| roi | 2 | 2 | 0 | 0 |'
' 15 | 30 | 0.6 | 15 |\n'
'| stop_loss | 1 | 0 | 0 | 1 |'
' -10 | -10 | -0.2 | -5 |'
)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
results=results)
assert text_table_sell_reason(sell_reason_stats=sell_reason_stats,
stake_currency='BTC') == result_str
def test_generate_sell_reason_stats(default_conf):
results = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2, -0.1],
'profit_abs': [0.2, 0.4, -0.2],
'trade_duration': [10, 30, 10],
'wins': [2, 0, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
results=results)
roi_result = sell_reason_stats[0]
assert roi_result['sell_reason'] == 'roi'
assert roi_result['trades'] == 2
assert pytest.approx(roi_result['profit_mean']) == 0.15
assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
assert pytest.approx(roi_result['profit_mean']) == 0.15
assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
stop_result = sell_reason_stats[1]
assert stop_result['sell_reason'] == 'stop_loss'
assert stop_result['trades'] == 1
assert pytest.approx(stop_result['profit_mean']) == -0.1
assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
assert pytest.approx(stop_result['profit_mean']) == -0.1
assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
def test_text_table_strategy(default_conf, mocker):
results = {}
results['TestStrategy1'] = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2, 0.3],
'profit_abs': [0.2, 0.4, 0.5],
'trade_duration': [10, 30, 10],
'wins': [2, 0, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
results['TestStrategy2'] = pd.DataFrame(
{
'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
'profit_percent': [0.4, 0.2, 0.3],
'profit_abs': [0.4, 0.4, 0.5],
'trade_duration': [15, 30, 15],
'wins': [4, 1, 0],
'draws': [0, 0, 0],
'losses': [0, 0, 1],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}
)
result_str = (
'| Strategy | Buys | Avg Profit % | Cum Profit % | Tot'
' Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'|---------------+--------+----------------+----------------+------------------+'
'----------------+----------------+--------+---------+----------|\n'
'| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |'
' 30.00 | 0:17:00 | 3 | 0 | 0 |\n'
'| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |'
' 45.00 | 0:20:00 | 3 | 0 | 0 |'
)
strategy_results = generate_strategy_metrics(stake_currency='BTC',
max_open_trades=2,
all_results=results)
assert text_table_strategy(strategy_results, 'BTC') == result_str
def test_generate_edge_table(edge_conf, mocker):
results = {}
results['ETH/BTC'] = PairInfo(-0.01, 0.60, 2, 1, 3, 10, 60)
assert generate_edge_table(results).count('+') == 7
assert generate_edge_table(results).count('| ETH/BTC |') == 1
assert generate_edge_table(results).count(
'| Risk Reward Ratio | Required Risk Reward | Expectancy |') == 1
def test_backtest_record(default_conf, fee, mocker):
names = []
records = []
patch_exchange(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch(
'freqtrade.optimize.optimize_reports.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
results = {'DefStrat': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
})}
store_backtest_result(Path("backtest-result.json"), results)
# Assert file_dump_json was only called once
assert names == [Path('backtest-result.json')]
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# reset test to test with strategy name
names = []
records = []
results['Strat'] = results['DefStrat']
results['Strat2'] = results['DefStrat']
store_backtest_result(Path("backtest-result.json"), results)
assert names == [
Path('backtest-result-DefStrat.json'),
Path('backtest-result-Strat.json'),
Path('backtest-result-Strat2.json'),
]
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
# Below follows just a typecheck of the schema/type of trade-records
oix = None
for (pair, profit, date_buy, date_sell, buy_index, dur,
openr, closer, open_at_end, sell_reason) in records:
assert pair == 'UNITTEST/BTC'
assert isinstance(profit, float)
# FIX: buy/sell should be converted to ints
assert isinstance(date_buy, float)
assert isinstance(date_sell, float)
assert isinstance(openr, float)
assert isinstance(closer, float)
assert isinstance(open_at_end, bool)
assert isinstance(sell_reason, str)
isinstance(buy_index, pd._libs.tslib.Timestamp)
if oix:
assert buy_index > oix
oix = buy_index
assert dur > 0
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