def test_load_tickerdata_file(testdatadir) -> None:
# 7 does not exist in either format.
assert not load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '7m')
# 1 exists only as a .json
tickerdata = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m')
assert _BTC_UNITTEST_LENGTH == len(tickerdata)
# 8 .json is empty and will fail if it's loaded. .json.gz is a copy of 1.json
tickerdata = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '8m')
assert _BTC_UNITTEST_LENGTH == len(tickerdata)
def test_buy_strategy_generator(hyperopt, testdatadir) -> None:
tick = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
fill_missing=True)}
dataframes = hyperopt.backtesting.strategy.tickerdata_to_dataframe(tickerlist)
dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
{'pair': 'UNITTEST/BTC'})
populate_buy_trend = hyperopt.custom_hyperopt.buy_strategy_generator(
{
'adx-value': 20,
'fastd-value': 20,
'mfi-value': 20,
'rsi-value': 20,
'adx-enabled': True,
'fastd-enabled': True,
'mfi-enabled': True,
'rsi-enabled': True,
'trigger': 'bb_lower'
}
)
result = populate_buy_trend(dataframe, {'pair': 'UNITTEST/BTC'})
# Check if some indicators are generated. We will not test all of them
assert 'buy' in result
assert 1 in result['buy']
def test_tickerdata_to_dataframe(default_conf) -> None:
strategy = DefaultStrategy(default_conf)
timerange = TimeRange(None, 'line', 0, -100)
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', True)}
data = strategy.tickerdata_to_dataframe(tickerlist)
assert len(data['UNITTEST/BTC']) == 102 # partial candle was removed
def test_tickerdata_to_dataframe(default_conf, testdatadir) -> None:
strategy = DefaultStrategy(default_conf)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
tick = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
fill_missing=True)}
data = strategy.tickerdata_to_dataframe(tickerlist)
assert len(data['UNITTEST/BTC']) == 102 # partial candle was removed
def test_common_datearray(default_conf) -> None:
strategy = DefaultStrategy(default_conf)
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick)}
dataframes = strategy.tickerdata_to_dataframe(tickerlist)
dates = common_datearray(dataframes)
assert dates.size == dataframes['UNITTEST/BTC']['date'].size
assert dates[0] == dataframes['UNITTEST/BTC']['date'][0]
assert dates[-1] == dataframes['UNITTEST/BTC']['date'][-1]
def test_populate_indicators(hyperopt) -> None:
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick)}
dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
dataframe = hyperopt.custom_hyperopt.populate_indicators(
dataframes['UNITTEST/BTC'], {'pair': 'UNITTEST/BTC'})
# Check if some indicators are generated. We will not test all of them
assert 'adx' in dataframe
assert 'mfi' in dataframe
assert 'rsi' in dataframe
def mocked_load_data(datadir,
pairs=[],
ticker_interval='0m',
refresh_pairs=False,
timerange=None,
exchange=None):
tickerdata = history.load_tickerdata_file(datadir,
'UNITTEST/BTC',
'1m',
timerange=timerange)
pairdata = {'UNITTEST/BTC': parse_ticker_dataframe(tickerdata)}
return pairdata
def test_populate_indicators(hyperopt, testdatadir) -> None:
tick = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m')
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
fill_missing=True)}
dataframes = hyperopt.backtesting.strategy.tickerdata_to_dataframe(tickerlist)
dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
{'pair': 'UNITTEST/BTC'})
# Check if some indicators are generated. We will not test all of them
assert 'adx' in dataframe
assert 'mfi' in dataframe
assert 'rsi' in dataframe
def load_data_test(what):
timerange = TimeRange(None, 'line', 0, -101)
pair = history.load_tickerdata_file(None,
ticker_interval='1m',
pair='UNITTEST/BTC',
timerange=timerange)
datalen = len(pair)
base = 0.001
if what == 'raise':
data = [
[
pair[x][0], # Keep old dates
x * base, # But replace O,H,L,C
x * base + 0.0001,
x * base - 0.0001,
x * base,
pair[x][5], # Keep old volume
] for x in range(0, datalen)
]
if what == 'lower':
data = [
[
pair[x][0], # Keep old dates
1 - x * base, # But replace O,H,L,C
1 - x * base + 0.0001,
1 - x * base - 0.0001,
1 - x * base,
pair[x][5] # Keep old volume
] for x in range(0, datalen)
]
if what == 'sine':
hz = 0.1 # frequency
data = [
[
pair[x][0], # Keep old dates
math.sin(x * hz) / 1000 + base, # But replace O,H,L,C
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
pair[x][5] # Keep old volume
] for x in range(0, datalen)
]
return {
'UNITTEST/BTC':
parse_ticker_dataframe(data,
'1m',
pair="UNITTEST/BTC",
fill_missing=True)
}
def test_tickerdata_to_dataframe_bt(default_conf, mocker) -> None:
patch_exchange(mocker)
timerange = TimeRange(None, 'line', 0, -100)
tick = history.load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', fill_missing=True)}
backtesting = Backtesting(default_conf)
data = backtesting.strategy.tickerdata_to_dataframe(tickerlist)
assert len(data['UNITTEST/BTC']) == 102
# Load strategy to compare the result between Backtesting function and strategy are the same
strategy = DefaultStrategy(default_conf)
data2 = strategy.tickerdata_to_dataframe(tickerlist)
assert data['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])
def mocked_load_data(datadir,
pairs=[],
timeframe='0m',
timerange=None,
*args,
**kwargs):
tickerdata = history.load_tickerdata_file(datadir,
'UNITTEST/BTC',
'1m',
timerange=timerange)
pairdata = {
'UNITTEST/BTC':
parse_ticker_dataframe(tickerdata,
'1m',
pair="UNITTEST/BTC",
fill_missing=True)
}
return pairdata
def _load_pair_as_ticks(pair, tickfreq):
ticks = history.load_tickerdata_file(None,
ticker_interval=tickfreq,
pair=pair)
ticks = ticks[-201:]
return ticks
