Merge pull request #111 from gcarq/memoryfix-hyperopt
Memory fix hyperopt
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commit
77887d6fbc
@ -66,14 +66,13 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.ix[
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dataframe.loc[
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(dataframe['close'] < dataframe['sma']) &
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(dataframe['tema'] <= dataframe['blower']) &
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(dataframe['mfi'] < 25) &
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(dataframe['fastd'] < 25) &
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(dataframe['adx'] > 30),
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'buy'] = 1
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dataframe.ix[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
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return dataframe
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@ -83,10 +82,9 @@ def populate_sell_trend(dataframe: DataFrame) -> DataFrame:
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.ix[
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dataframe.loc[
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(crossed_above(dataframe['rsi'], 70)),
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'sell'] = 1
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dataframe.ix[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']
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return dataframe
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@ -106,6 +104,9 @@ def analyze_ticker(pair: str) -> DataFrame:
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dataframe = populate_indicators(dataframe)
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dataframe = populate_buy_trend(dataframe)
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dataframe = populate_sell_trend(dataframe)
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# TODO: buy_price and sell_price are only used by the plotter, should probably be moved there
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dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
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dataframe.loc[dataframe['sell'] == 1, 'sell_price'] = dataframe['close']
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return dataframe
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@ -163,9 +163,9 @@ def min_roi_reached(trade: Trade, current_rate: float, current_time: datetime) -
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logger.debug('Stop loss hit.')
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return True
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for duration, threshold in sorted(_CONF['minimal_roi'].items()):
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# Check if time matches and current rate is above threshold
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time_diff = (current_time - trade.open_date).total_seconds() / 60
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for duration, threshold in sorted(_CONF['minimal_roi'].items()):
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if time_diff > float(duration) and current_profit > threshold:
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return True
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@ -5,7 +5,7 @@ import pytest
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from pandas import DataFrame
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from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
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get_signal, SignalType
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get_signal, SignalType, populate_sell_trend
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@pytest.fixture
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@ -26,7 +26,11 @@ def test_dataframe_correct_length(result):
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def test_populates_buy_trend(result):
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dataframe = populate_buy_trend(populate_indicators(result))
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assert 'buy' in dataframe.columns
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assert 'buy_price' in dataframe.columns
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def test_populates_buy_trend(result):
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dataframe = populate_sell_trend(populate_indicators(result))
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assert 'sell' in dataframe.columns
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def test_returns_latest_buy_signal(mocker):
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@ -1,4 +1,5 @@
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# pragma pylint: disable=missing-docstring
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from typing import Dict
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import logging
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import os
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@ -7,7 +8,8 @@ import arrow
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from pandas import DataFrame
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from freqtrade import exchange
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from freqtrade.analyze import analyze_ticker
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from freqtrade.analyze import parse_ticker_dataframe, populate_indicators, \
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populate_buy_trend, populate_sell_trend
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from freqtrade.exchange import Bittrex
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from freqtrade.main import min_roi_reached
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from freqtrade.persistence import Trade
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@ -25,15 +27,22 @@ def print_pair_results(pair, results):
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print(format_results(results[results.currency == pair]))
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def backtest(backtest_conf, backdata, mocker):
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def preprocess(backdata) -> Dict[str, DataFrame]:
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processed = {}
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for pair, pair_data in backdata.items():
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processed[pair] = populate_indicators(parse_ticker_dataframe(pair_data))
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return processed
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def backtest(backtest_conf, processed, mocker):
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trades = []
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exchange._API = Bittrex({'key': '', 'secret': ''})
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mocked_history = mocker.patch('freqtrade.analyze.get_ticker_history')
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mocker.patch.dict('freqtrade.main._CONF', backtest_conf)
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mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
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for pair, pair_data in backdata.items():
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mocked_history.return_value = pair_data
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ticker = analyze_ticker(pair)[['close', 'date', 'buy', 'sell']].copy()
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for pair, pair_data in processed.items():
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pair_data['buy'] = 0
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pair_data['sell'] = 0
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ticker = populate_sell_trend(populate_buy_trend(pair_data))
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# for each buy point
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for row in ticker[ticker.buy == 1].itertuples(index=True):
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trade = Trade(
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@ -50,13 +59,12 @@ def backtest(backtest_conf, backdata, mocker):
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trades.append((pair, current_profit, row2.Index - row.Index))
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break
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labels = ['currency', 'profit', 'duration']
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results = DataFrame.from_records(trades, columns=labels)
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return results
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return DataFrame.from_records(trades, columns=labels)
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@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
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def test_backtest(backtest_conf, backdata, mocker, report=True):
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results = backtest(backtest_conf, backdata, mocker)
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results = backtest(backtest_conf, preprocess(backdata), mocker)
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print('====================== BACKTESTING REPORT ================================')
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for pair in backdata:
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@ -9,7 +9,7 @@ import pytest
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from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
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from pandas import DataFrame
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from freqtrade.tests.test_backtesting import backtest, format_results
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from freqtrade.tests.test_backtesting import backtest, format_results, preprocess
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from freqtrade.vendor.qtpylib.indicators import crossed_above
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logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
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@ -59,7 +59,6 @@ def buy_strategy_generator(params):
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dataframe.loc[
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reduce(lambda x, y: x & y, conditions),
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'buy'] = 1
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dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
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return dataframe
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return populate_buy_trend
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@ -67,12 +66,13 @@ def buy_strategy_generator(params):
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@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
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def test_hyperopt(backtest_conf, backdata, mocker):
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mocked_buy_trend = mocker.patch('freqtrade.analyze.populate_buy_trend')
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mocked_buy_trend = mocker.patch('freqtrade.tests.test_backtesting.populate_buy_trend')
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processed = preprocess(backdata)
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def optimizer(params):
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mocked_buy_trend.side_effect = buy_strategy_generator(params)
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results = backtest(backtest_conf, backdata, mocker)
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results = backtest(backtest_conf, processed, mocker)
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result = format_results(results)
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@ -146,3 +146,8 @@ def test_hyperopt(backtest_conf, backdata, mocker):
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print('Best parameters {}'.format(best))
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newlist = sorted(trials.results, key=itemgetter('loss'))
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print('Result: {}'.format(newlist[0]['result']))
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if __name__ == '__main__':
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# for profiling with cProfile and line_profiler
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pytest.main([__file__, '-s'])
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