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don't copy tickerdata_to_dataframe into backtesting

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it's used only once, so this does not make sense and hides the origin of
the function
This commit is contained in:
Matthias 2018-10-17 19:47:19 +02:00
parent f9bbeb79fa
commit 8a3272e7c5
4 changed files with 13 additions and 14 deletions
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3
freqtrade/optimize/backtesting.py
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@ -88,7 +88,6 @@ class Backtesting(object):
""" """
self.strategy = strategy self.strategy = strategy
self.ticker_interval = self.config.get('ticker_interval') self.ticker_interval = self.config.get('ticker_interval')
self.tickerdata_to_dataframe = strategy.tickerdata_to_dataframe
self.advise_buy = strategy.advise_buy self.advise_buy = strategy.advise_buy
self.advise_sell = strategy.advise_sell self.advise_sell = strategy.advise_sell
@ -371,7 +370,7 @@ class Backtesting(object):
self._set_strategy(strat) self._set_strategy(strat)
# need to reprocess data every time to populate signals # need to reprocess data every time to populate signals
preprocessed = self.tickerdata_to_dataframe(data) preprocessed = self.strategy.tickerdata_to_dataframe(data)
# Print timeframe # Print timeframe
min_date, max_date = self.get_timeframe(preprocessed) min_date, max_date = self.get_timeframe(preprocessed)

2
freqtrade/optimize/hyperopt.py
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@ -352,7 +352,7 @@ class Hyperopt(Backtesting):
if self.has_space('buy'): if self.has_space('buy'):
self.strategy.advise_indicators = Hyperopt.populate_indicators # type: ignore self.strategy.advise_indicators = Hyperopt.populate_indicators # type: ignore
dump(self.tickerdata_to_dataframe(data), TICKERDATA_PICKLE) dump(self.strategy.tickerdata_to_dataframe(data), TICKERDATA_PICKLE)
self.exchange = None # type: ignore self.exchange = None # type: ignore
self.load_previous_results() self.load_previous_results()

16
freqtrade/tests/optimize/test_backtesting.py
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@ -89,7 +89,7 @@ def simple_backtest(config, contour, num_results, mocker) -> None:
backtesting = Backtesting(config) backtesting = Backtesting(config)
data = load_data_test(contour) data = load_data_test(contour)
processed = backtesting.tickerdata_to_dataframe(data) processed = backtesting.strategy.tickerdata_to_dataframe(data)
assert isinstance(processed, dict) assert isinstance(processed, dict)
results = backtesting.backtest( results = backtesting.backtest(
{ {
@ -125,7 +125,7 @@ def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
backtesting = Backtesting(conf) backtesting = Backtesting(conf)
return { return {
'stake_amount': conf['stake_amount'], 'stake_amount': conf['stake_amount'],
'processed': backtesting.tickerdata_to_dataframe(data), 'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'max_open_trades': 10, 'max_open_trades': 10,
'position_stacking': False, 'position_stacking': False,
'record': record 'record': record
@ -313,7 +313,7 @@ def test_backtesting_init(mocker, default_conf) -> None:
backtesting = Backtesting(default_conf) backtesting = Backtesting(default_conf)
assert backtesting.config == default_conf assert backtesting.config == default_conf
assert backtesting.ticker_interval == '5m' assert backtesting.ticker_interval == '5m'
assert callable(backtesting.tickerdata_to_dataframe) assert callable(backtesting.strategy.tickerdata_to_dataframe)
assert callable(backtesting.advise_buy) assert callable(backtesting.advise_buy)
assert callable(backtesting.advise_sell) assert callable(backtesting.advise_sell)
get_fee.assert_called() get_fee.assert_called()
@ -327,7 +327,7 @@ def test_tickerdata_to_dataframe(default_conf, mocker) -> None:
tickerlist = {'UNITTEST/BTC': tick} tickerlist = {'UNITTEST/BTC': tick}
backtesting = Backtesting(default_conf) backtesting = Backtesting(default_conf)
data = backtesting.tickerdata_to_dataframe(tickerlist) data = backtesting.strategy.tickerdata_to_dataframe(tickerlist)
assert len(data['UNITTEST/BTC']) == 99 assert len(data['UNITTEST/BTC']) == 99
# Load strategy to compare the result between Backtesting function and strategy are the same # Load strategy to compare the result between Backtesting function and strategy are the same
@ -340,7 +340,7 @@ def test_get_timeframe(default_conf, mocker) -> None:
patch_exchange(mocker) patch_exchange(mocker)
backtesting = Backtesting(default_conf) backtesting = Backtesting(default_conf)
data = backtesting.tickerdata_to_dataframe( data = backtesting.strategy.tickerdata_to_dataframe(
optimize.load_data( optimize.load_data(
None, None,
ticker_interval='1m', ticker_interval='1m',
@ -520,7 +520,7 @@ def test_backtest(default_conf, fee, mocker) -> None:
pair = 'UNITTEST/BTC' pair = 'UNITTEST/BTC'
data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC']) data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
data = trim_dictlist(data, -200) data = trim_dictlist(data, -200)
data_processed = backtesting.tickerdata_to_dataframe(data) data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
results = backtesting.backtest( results = backtesting.backtest(
{ {
'stake_amount': default_conf['stake_amount'], 'stake_amount': default_conf['stake_amount'],
@ -571,7 +571,7 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
results = backtesting.backtest( results = backtesting.backtest(
{ {
'stake_amount': default_conf['stake_amount'], 'stake_amount': default_conf['stake_amount'],
'processed': backtesting.tickerdata_to_dataframe(data), 'processed': backtesting.strategy.tickerdata_to_dataframe(data),
'max_open_trades': 1, 'max_open_trades': 1,
'position_stacking': False 'position_stacking': False
} }
@ -585,7 +585,7 @@ def test_processed(default_conf, mocker) -> None:
backtesting = Backtesting(default_conf) backtesting = Backtesting(default_conf)
dict_of_tickerrows = load_data_test('raise') dict_of_tickerrows = load_data_test('raise')
dataframes = backtesting.tickerdata_to_dataframe(dict_of_tickerrows) dataframes = backtesting.strategy.tickerdata_to_dataframe(dict_of_tickerrows)
dataframe = dataframes['UNITTEST/BTC'] dataframe = dataframes['UNITTEST/BTC']
cols = dataframe.columns cols = dataframe.columns
# assert the dataframe got some of the indicator columns # assert the dataframe got some of the indicator columns

6
freqtrade/tests/optimize/test_hyperopt.py
View File

@ -194,7 +194,7 @@ def test_start_calls_optimizer(mocker, default_conf, caplog) -> None:
default_conf.update({'spaces': 'all'}) default_conf.update({'spaces': 'all'})
hyperopt = Hyperopt(default_conf) hyperopt = Hyperopt(default_conf)
hyperopt.tickerdata_to_dataframe = MagicMock() hyperopt.strategy.tickerdata_to_dataframe = MagicMock()
hyperopt.start() hyperopt.start()
parallel.assert_called_once() parallel.assert_called_once()
@ -242,7 +242,7 @@ def test_has_space(hyperopt):
def test_populate_indicators(hyperopt) -> None: def test_populate_indicators(hyperopt) -> None:
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m') tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': tick} tickerlist = {'UNITTEST/BTC': tick}
dataframes = hyperopt.tickerdata_to_dataframe(tickerlist) dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'}) dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'})
# Check if some indicators are generated. We will not test all of them # Check if some indicators are generated. We will not test all of them
@ -254,7 +254,7 @@ def test_populate_indicators(hyperopt) -> None:
def test_buy_strategy_generator(hyperopt) -> None: def test_buy_strategy_generator(hyperopt) -> None:
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m') tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': tick} tickerlist = {'UNITTEST/BTC': tick}
dataframes = hyperopt.tickerdata_to_dataframe(tickerlist) dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'}) dataframe = hyperopt.populate_indicators(dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'})
populate_buy_trend = hyperopt.buy_strategy_generator( populate_buy_trend = hyperopt.buy_strategy_generator(