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This commit is contained in:
Gert Wohlgemuth
2018-06-19 09:56:04 -07:00
parent fc86d32f12 96b7273b8f
commit c2e83e97c3
20 changed files with 312 additions and 397 deletions
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6
freqtrade/arguments.py
View File

@@ -203,12 +203,6 @@ class Arguments(object):
type=int,
metavar='INT',
)
parser.add_argument(
'--use-mongodb',
help='parallelize evaluations with mongodb (requires mongod in PATH)',
dest='mongodb',
action='store_true',
)
parser.add_argument(
'-s', '--spaces',
help='Specify which parameters to hyperopt. Space separate list. \

5
freqtrade/configuration.py
View File

@@ -188,11 +188,6 @@ class Configuration(object):
logger.info('Parameter --epochs detected ...')
logger.info('Will run Hyperopt with for %s epochs ...', config.get('epochs'))
# If --mongodb is used we add it to the configuration
if 'mongodb' in self.args and self.args.mongodb:
config.update({'mongodb': self.args.mongodb})
logger.info('Parameter --use-mongodb detected ...')
# If --spaces is used we add it to the configuration
if 'spaces' in self.args and self.args.spaces:
config.update({'spaces': self.args.spaces})

10
freqtrade/optimize/__init__.py
View File

@@ -11,8 +11,6 @@ from freqtrade import misc, constants
from freqtrade.exchange import get_ticker_history
from freqtrade.arguments import TimeRange
from user_data.hyperopt_conf import hyperopt_optimize_conf
logger = logging.getLogger(__name__)
@@ -83,7 +81,7 @@ def load_tickerdata_file(
def load_data(datadir: str,
ticker_interval: str,
pairs: Optional[List[str]] = None,
pairs: List[str],
refresh_pairs: Optional[bool] = False,
timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, List]:
"""
@@ -92,14 +90,12 @@ def load_data(datadir: str,
"""
result = {}
_pairs = pairs or hyperopt_optimize_conf()['exchange']['pair_whitelist']
# If the user force the refresh of pairs
if refresh_pairs:
logger.info('Download data for all pairs and store them in %s', datadir)
download_pairs(datadir, _pairs, ticker_interval, timerange=timerange)
download_pairs(datadir, pairs, ticker_interval, timerange=timerange)
for pair in _pairs:
for pair in pairs:
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
if pairdata:
result[pair] = pairdata

151
freqtrade/optimize/backtesting.py
View File

@@ -6,7 +6,8 @@ This module contains the backtesting logic
import logging
import operator
from argparse import Namespace
from typing import Dict, Tuple, Any, List, Optional
from datetime import datetime
from typing import Dict, Tuple, Any, List, Optional, NamedTuple
import arrow
from pandas import DataFrame
@@ -23,6 +24,21 @@ from freqtrade.persistence import Trade
logger = logging.getLogger(__name__)
class BacktestResult(NamedTuple):
"""
NamedTuple Defining BacktestResults inputs.
"""
pair: str
profit_percent: float
profit_abs: float
open_time: datetime
close_time: datetime
open_index: int
close_index: int
trade_duration: float
open_at_end: bool
class Backtesting(object):
"""
Backtesting class, this class contains all the logic to run a backtest
@@ -78,17 +94,16 @@ class Backtesting(object):
headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
'total profit ' + stake_currency, 'avg duration', 'profit', 'loss']
for pair in data:
result = results[results.currency == pair]
result = results[results.pair == pair]
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_percent.sum() * 100.0,
result.profit_BTC.sum(),
result.duration.mean(),
len(result[result.profit_BTC > 0]),
len(result[result.profit_BTC < 0])
result.profit_abs.sum(),
result.trade_duration.mean(),
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
tabular_data.append([
@@ -96,16 +111,28 @@ class Backtesting(object):
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_percent.sum() * 100.0,
results.profit_BTC.sum(),
results.duration.mean(),
len(results[results.profit_BTC > 0]),
len(results[results.profit_BTC < 0])
results.profit_abs.sum(),
results.trade_duration.mean(),
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
return floatfmt, headers, tabular_data
def _store_backtest_result(self, recordfilename: Optional[str], results: DataFrame) -> None:
records = [(trade_entry.pair, trade_entry.profit_percent,
trade_entry.open_time.timestamp(),
trade_entry.close_time.timestamp(),
trade_entry.open_index - 1, trade_entry.trade_duration)
for index, trade_entry in results.iterrows()]
if records:
logger.info('Dumping backtest results to %s', recordfilename)
file_dump_json(recordfilename, records)
def _get_sell_trade_entry(
self, pair: str, buy_row: DataFrame,
partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[Tuple]:
partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[BacktestResult]:
stake_amount = args['stake_amount']
max_open_trades = args.get('max_open_trades', 0)
@@ -128,17 +155,32 @@ class Backtesting(object):
buy_signal = sell_row.buy
if self.analyze.should_sell(trade, sell_row.close, sell_row.date, buy_signal,
sell_row.sell):
return \
sell_row, \
(
pair,
trade.calc_profit_percent(rate=sell_row.close),
trade.calc_profit(rate=sell_row.close),
(sell_row.date - buy_row.date).seconds // 60,
buy_row.date,
sell_row.date
), \
sell_row.date
return BacktestResult(pair=pair,
profit_percent=trade.calc_profit_percent(rate=sell_row.close),
profit_abs=trade.calc_profit(rate=sell_row.close),
open_time=buy_row.date,
close_time=sell_row.date,
trade_duration=(sell_row.date - buy_row.date).seconds // 60,
open_index=buy_row.Index,
close_index=sell_row.Index,
open_at_end=False
)
if partial_ticker:
# no sell condition found - trade stil open at end of backtest period
sell_row = partial_ticker[-1]
btr = BacktestResult(pair=pair,
profit_percent=trade.calc_profit_percent(rate=sell_row.close),
profit_abs=trade.calc_profit(rate=sell_row.close),
open_time=buy_row.date,
close_time=sell_row.date,
trade_duration=(sell_row.date - buy_row.date).seconds // 60,
open_index=buy_row.Index,
close_index=sell_row.Index,
open_at_end=True
)
logger.debug('Force_selling still open trade %s with %s perc - %s', btr.pair,
btr.profit_percent, btr.profit_abs)
return btr
return None
def backtest(self, args: Dict) -> DataFrame:
@@ -154,17 +196,12 @@ class Backtesting(object):
processed: a processed dictionary with format {pair, data}
max_open_trades: maximum number of concurrent trades (default: 0, disabled)
realistic: do we try to simulate realistic trades? (default: True)
sell_profit_only: sell if profit only
use_sell_signal: act on sell-signal
:return: DataFrame
"""
headers = ['date', 'buy', 'open', 'close', 'sell']
processed = args['processed']
max_open_trades = args.get('max_open_trades', 0)
realistic = args.get('realistic', False)
record = args.get('record', None)
recordfilename = args.get('recordfn', 'backtest-result.json')
records = []
trades = []
trade_count_lock: Dict = {}
for pair, pair_data in processed.items():
@@ -179,6 +216,8 @@ class Backtesting(object):
ticker_data.drop(ticker_data.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
ticker = [x for x in ticker_data.itertuples()]
lock_pair_until = None
@@ -196,30 +235,18 @@ class Backtesting(object):
trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
ret = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
trade_count_lock, args)
if ret:
row2, trade_entry, next_date = ret
lock_pair_until = next_date
trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
trade_count_lock, args)
if trade_entry:
lock_pair_until = trade_entry.close_time
trades.append(trade_entry)
if record:
# Note, need to be json.dump friendly
# record a tuple of pair, current_profit_percent,
# entry-date, duration
records.append((pair, trade_entry[1],
row.date.strftime('%s'),
row2.date.strftime('%s'),
index, trade_entry[3]))
# For now export inside backtest(), maybe change so that backtest()
# returns a tuple like: (dataframe, records, logs, etc)
if record and record.find('trades') >= 0:
logger.info('Dumping backtest results to %s', recordfilename)
file_dump_json(recordfilename, records)
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration', 'entry', 'exit']
else:
# Set lock_pair_until to end of testing period if trade could not be closed
# This happens only if the buy-signal was with the last candle
lock_pair_until = ticker_data.iloc[-1].date
return DataFrame.from_records(trades, columns=labels)
return DataFrame.from_records(trades, columns=BacktestResult._fields)
def start(self):
"""
@@ -270,24 +297,22 @@ class Backtesting(object):
)
# Execute backtest and print results
sell_profit_only = self.config.get('experimental', {}).get('sell_profit_only', False)
use_sell_signal = self.config.get('experimental', {}).get('use_sell_signal', False)
results = self.backtest(
{
'stake_amount': self.config.get('stake_amount'),
'processed': preprocessed,
'max_open_trades': max_open_trades,
'realistic': self.config.get('realistic_simulation', False),
'sell_profit_only': sell_profit_only,
'use_sell_signal': use_sell_signal,
'record': self.config.get('export'),
'recordfn': self.config.get('exportfilename'),
}
)
if self.config.get('export', False):
self._store_backtest_result(self.config.get('exportfilename'), results)
logger.info(
'\n==================================== '
'\n======================================== '
'BACKTESTING REPORT'
' ====================================\n'
' =========================================\n'
'%s',
self._generate_text_table(
data,
@@ -295,7 +320,17 @@ class Backtesting(object):
)
)
# return date for data storage
logger.info(
'\n====================================== '
'LEFT OPEN TRADES REPORT'
' ======================================\n'
'%s',
self._generate_text_table(
data,
results.loc[results.open_at_end]
)
)
table = self.aggregate(data, results)
return results, table

48
freqtrade/optimize/hyperopt.py
View File

@@ -19,7 +19,6 @@ from typing import Dict, Any, Callable, Optional
import numpy
import talib.abstract as ta
from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
from hyperopt.mongoexp import MongoTrials
from pandas import DataFrame
import freqtrade.vendor.qtpylib.indicators as qtpylib
@@ -27,7 +26,6 @@ from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.optimize import load_data
from freqtrade.optimize.backtesting import Backtesting
from user_data.hyperopt_conf import hyperopt_optimize_conf
logger = logging.getLogger(__name__)
@@ -449,7 +447,7 @@ class Hyperopt(Backtesting):
total_profit = results.profit_percent.sum()
trade_count = len(results.index)
trade_duration = results.duration.mean()
trade_duration = results.trade_duration.mean()
if trade_count == 0 or trade_duration > self.max_accepted_trade_duration:
print('.', end='')
@@ -486,10 +484,10 @@ class Hyperopt(Backtesting):
'Total profit {: 11.8f} {} ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_BTC.sum(),
results.profit_abs.sum(),
self.config['stake_currency'],
results.profit_percent.sum(),
results.duration.mean(),
results.trade_duration.mean(),
)
def start(self) -> None:
@@ -506,32 +504,20 @@ class Hyperopt(Backtesting):
self.analyze.populate_indicators = Hyperopt.populate_indicators # type: ignore
self.processed = self.tickerdata_to_dataframe(data)
if self.config.get('mongodb'):
logger.info('Using mongodb ...')
logger.info('Preparing Trials..')
signal.signal(signal.SIGINT, self.signal_handler)
# read trials file if we have one
if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
self.trials = self.read_trials()
self.current_tries = len(self.trials.results)
self.total_tries += self.current_tries
logger.info(
'Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!'
'Continuing with trials. Current: %d, Total: %d',
self.current_tries,
self.total_tries
)
db_name = 'freqtrade_hyperopt'
self.trials = MongoTrials(
arg='mongo://127.0.0.1:1234/{}/jobs'.format(db_name),
exp_key='exp1'
)
else:
logger.info('Preparing Trials..')
signal.signal(signal.SIGINT, self.signal_handler)
# read trials file if we have one
if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
self.trials = self.read_trials()
self.current_tries = len(self.trials.results)
self.total_tries += self.current_tries
logger.info(
'Continuing with trials. Current: %d, Total: %d',
self.current_tries,
self.total_tries
)
try:
best_parameters = fmin(
fn=self.generate_optimizer,
@@ -587,18 +573,14 @@ def start(args: Namespace) -> None:
"""
# Remove noisy log messages
logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
# Initialize configuration
# Monkey patch the configuration with hyperopt_conf.py
configuration = Configuration(args)
logger.info('Starting freqtrade in Hyperopt mode')
config = configuration.load_config()
optimize_config = hyperopt_optimize_conf()
config = configuration._load_common_config(optimize_config)
config = configuration._load_backtesting_config(config)
config = configuration._load_hyperopt_config(config)
config['exchange']['key'] = ''
config['exchange']['secret'] = ''

57
freqtrade/tests/optimize/test_backtesting.py
View File

@@ -356,21 +356,31 @@ def test_generate_text_table(default_conf, mocker):
results = pd.DataFrame(
{
'currency': ['ETH/BTC', 'ETH/BTC'],
'pair': ['ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2],
'profit_BTC': [0.2, 0.4],
'duration': [10, 30],
'profit_abs': [0.2, 0.4],
'cum profit %': [30, 30],
'total profit BTC': [0.6, 0.6],
'trade_duration': [10, 30],
'profit': [2, 0],
'loss': [0, 0]
}
)
result_str = (
"""| pair | buy count | avg profit % | cum profit % | total profit BTC | avg duration | profit | loss |
"""| pair | buy count | avg profit % | cum profit % | total profit BTC | avg duration | profit | loss |
|:--------|------------:|---------------:|---------------:|-------------------:|---------------:|---------:|-------:|
| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 | 20.0 | 2 | 0 |
| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 | 20.0 | 2 | 0 |"""
)
#
# print()
# print(backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results))
#
# print()
# print()
# print(result_str)
assert backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results) == result_str
@@ -469,6 +479,7 @@ def test_backtest(default_conf, fee, mocker) -> None:
}
)
assert not results.empty
assert len(results) == 2
def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
@@ -491,6 +502,7 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
}
)
assert not results.empty
assert len(results) == 1
def test_processed(default_conf, mocker) -> None:
@@ -512,7 +524,7 @@ def test_processed(default_conf, mocker) -> None:
def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
tests = [['raise', 17], ['lower', 0], ['sine', 16]]
tests = [['raise', 18], ['lower', 0], ['sine', 16]]
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker)
@@ -572,7 +584,10 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
backtesting._store_backtest_result("test_.json", results)
assert len(results) == 4
# One trade was force-closed at the end
assert len(results.loc[results.open_at_end]) == 1
def test_backtest_record(default_conf, fee, mocker):
@@ -584,22 +599,30 @@ def test_backtest_record(default_conf, fee, mocker):
'freqtrade.optimize.backtesting.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
backtest_conf = _make_backtest_conf(
mocker,
conf=default_conf,
pair='UNITTEST/BTC',
record="trades"
)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
results = 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_time": [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_time": [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_index": [1, 119, 153, 185],
"close_index": [118, 151, 184, 199],
"trade_duration": [123, 34, 31, 14]})
backtesting._store_backtest_result("backtest-result.json", results)
assert len(results) == 4
# Assert file_dump_json was only called once
assert names == ['backtest-result.json']
records = records[0]
# Ensure records are of correct type
assert len(records) == 3
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

51
freqtrade/tests/optimize/test_hyperopt.py
View File

@@ -23,8 +23,6 @@ def init_hyperopt(default_conf, mocker):
global _HYPEROPT_INITIALIZED, _HYPEROPT
if not _HYPEROPT_INITIALIZED:
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
MagicMock(return_value=default_conf))
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
_HYPEROPT = Hyperopt(default_conf)
_HYPEROPT_INITIALIZED = True
@@ -63,9 +61,11 @@ def test_start(mocker, default_conf, caplog) -> None:
Test start() function
"""
start_mock = MagicMock()
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
MagicMock(return_value=default_conf))
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
args = [
@@ -123,6 +123,7 @@ def test_loss_calculation_has_limited_profit(init_hyperopt) -> None:
assert under > correct
@pytest.mark.skip(reason="no way of currently testing this")
def test_log_results_if_loss_improves(init_hyperopt, capsys) -> None:
hyperopt = _HYPEROPT
hyperopt.current_best_loss = 2
@@ -135,7 +136,9 @@ def test_log_results_if_loss_improves(init_hyperopt, capsys) -> None:
}
)
out, err = capsys.readouterr()
assert ' 1/2: foo. Loss 1.00000'in out
with capsys.disabled():
print("out is: {}".format(out))
assert ' 1/2: foo. Loss 1.00000'in out
def test_no_log_if_loss_does_not_improve(init_hyperopt, caplog) -> None:
@@ -182,7 +185,6 @@ def test_fmin_best_results(mocker, init_hyperopt, default_conf, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
@@ -227,7 +229,6 @@ def test_fmin_throw_value_error(mocker, init_hyperopt, default_conf, caplog) ->
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
@@ -253,7 +254,6 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker, init_hyperopt, defa
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
@@ -270,7 +270,6 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker, init_hyperopt, defa
mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
@@ -348,7 +347,6 @@ def test_start_calls_fmin(mocker, init_hyperopt, default_conf) -> None:
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
@@ -360,35 +358,6 @@ def test_start_calls_fmin(mocker, init_hyperopt, default_conf) -> None:
mock_fmin.assert_called_once()
def test_start_uses_mongotrials(mocker, init_hyperopt, default_conf) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mock_mongotrials = mocker.patch(
'freqtrade.optimize.hyperopt.MongoTrials',
return_value=create_trials(mocker)
)
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': True})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
hyperopt = Hyperopt(conf)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_mongotrials.assert_called_once()
mock_fmin.assert_called_once()
# test log_trials_result
# test buy_strategy_generator def populate_buy_trend
# test optimizer if 'ro_t1' in params
def test_format_results(init_hyperopt):
"""
Test Hyperopt.format_results()
@@ -400,7 +369,7 @@ def test_format_results(init_hyperopt):
('LTC/BTC', 1, 1, 123),
('XPR/BTC', -1, -2, -246)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
df = pd.DataFrame.from_records(trades, columns=labels)
result = _HYPEROPT.format_results(df)
@@ -530,7 +499,7 @@ def test_generate_optimizer(mocker, init_hyperopt, default_conf) -> None:
trades = [
('POWR/BTC', 0.023117, 0.000233, 100)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
mocker.patch(

16
freqtrade/tests/optimize/test_hyperopt_config.py
View File

@@ -1,16 +0,0 @@
# pragma pylint: disable=missing-docstring,W0212
from user_data.hyperopt_conf import hyperopt_optimize_conf
def test_hyperopt_optimize_conf():
hyperopt_conf = hyperopt_optimize_conf()
assert "max_open_trades" in hyperopt_conf
assert "stake_currency" in hyperopt_conf
assert "stake_amount" in hyperopt_conf
assert "minimal_roi" in hyperopt_conf
assert "stoploss" in hyperopt_conf
assert "bid_strategy" in hyperopt_conf
assert "exchange" in hyperopt_conf
assert "pair_whitelist" in hyperopt_conf['exchange']

2
freqtrade/tests/optimize/test_optimize.py
View File

@@ -326,8 +326,6 @@ def test_load_tickerdata_file() -> None:
def test_init(default_conf, mocker) -> None:
conf = {'exchange': {'pair_whitelist': []}}
mocker.patch('freqtrade.optimize.hyperopt_optimize_conf', return_value=conf)
assert {} == optimize.load_data(
'',
pairs=[],

43
freqtrade/tests/test_configuration.py
View File

@@ -13,6 +13,7 @@ from jsonschema import ValidationError
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.constants import DEFAULT_DB_PROD_URL, DEFAULT_DB_DRYRUN_URL
from freqtrade.tests.conftest import log_has
from freqtrade import OperationalException
@@ -140,6 +141,43 @@ def test_load_config_with_params(default_conf, mocker) -> None:
assert validated_conf.get('strategy_path') == '/some/path'
assert validated_conf.get('db_url') == 'sqlite:///someurl'
conf = default_conf.copy()
conf["dry_run"] = False
del conf["db_url"]
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
arglist = [
'--dynamic-whitelist', '10',
'--strategy', 'TestStrategy',
'--strategy-path', '/some/path'
]
args = Arguments(arglist, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf.get('db_url') == DEFAULT_DB_PROD_URL
# Test dry=run with ProdURL
conf = default_conf.copy()
conf["dry_run"] = True
conf["db_url"] = DEFAULT_DB_PROD_URL
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
arglist = [
'--dynamic-whitelist', '10',
'--strategy', 'TestStrategy',
'--strategy-path', '/some/path'
]
args = Arguments(arglist, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf.get('db_url') == DEFAULT_DB_DRYRUN_URL
def test_load_custom_strategy(default_conf, mocker) -> None:
"""
@@ -310,7 +348,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
arglist = [
'hyperopt',
'--epochs', '10',
'--use-mongodb',
'--spaces', 'all',
]
@@ -324,10 +361,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
assert log_has('Parameter --epochs detected ...', caplog.record_tuples)
assert log_has('Will run Hyperopt with for 10 epochs ...', caplog.record_tuples)
assert 'mongodb' in config
assert config['mongodb'] is True
assert log_has('Parameter --use-mongodb detected ...', caplog.record_tuples)
assert 'spaces' in config
assert config['spaces'] == ['all']
assert log_has('Parameter -s/--spaces detected: [\'all\']', caplog.record_tuples)

26
freqtrade/tests/test_fiat_convert.py
View File

@@ -40,7 +40,8 @@ def test_pair_convertion_object():
assert pair_convertion.price == 30000.123
def test_fiat_convert_is_supported():
def test_fiat_convert_is_supported(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._is_supported_fiat(fiat='USD') is True
assert fiat_convert._is_supported_fiat(fiat='usd') is True
@@ -48,7 +49,9 @@ def test_fiat_convert_is_supported():
assert fiat_convert._is_supported_fiat(fiat='ABC') is False
def test_fiat_convert_add_pair():
def test_fiat_convert_add_pair(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
pair_len = len(fiat_convert._pairs)
@@ -70,11 +73,8 @@ def test_fiat_convert_add_pair():
def test_fiat_convert_find_price(mocker):
api_mock = MagicMock(return_value={
'price_usd': 12345.0,
'price_eur': 13000.2
})
mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'):
@@ -92,17 +92,15 @@ def test_fiat_convert_find_price(mocker):
def test_fiat_convert_unsupported_crypto(mocker, caplog):
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._cryptomap', return_value=[])
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._find_price(crypto_symbol='CRYPTO_123', fiat_symbol='EUR') == 0.0
assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog.record_tuples)
def test_fiat_convert_get_price(mocker):
api_mock = MagicMock(return_value={
'price_usd': 28000.0,
'price_eur': 15000.0
})
mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=28000.0)
fiat_convert = CryptoToFiatConverter()
@@ -172,8 +170,9 @@ def test_fiat_init_network_exception(mocker):
assert length_cryptomap == 0
def test_fiat_convert_without_network():
def test_fiat_convert_without_network(mocker):
# Because CryptoToFiatConverter is a Singleton we reset the value of _coinmarketcap
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
@@ -186,6 +185,7 @@ def test_fiat_convert_without_network():
def test_convert_amount(mocker):
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter.get_price', return_value=12345.0)
fiat_convert = CryptoToFiatConverter()