def historic_ohlcv(self,
pair: str,
timeframe: str = None,
candle_type: str = '') -> DataFrame:
"""
Get stored historical candle (OHLCV) data
:param pair: pair to get the data for
:param timeframe: timeframe to get data for
:param candle_type: '', mark, index, premiumIndex, or funding_rate
"""
_candle_type = CandleType.from_string(
candle_type
) if candle_type != '' else self._config['candle_type_def']
saved_pair = (pair, str(timeframe), _candle_type)
if saved_pair not in self.__cached_pairs_backtesting:
timerange = TimeRange.parse_timerange(None if self._config.get(
'timerange') is None else str(self._config.get('timerange')))
# Move informative start time respecting startup_candle_count
timerange.subtract_start(
timeframe_to_seconds(str(timeframe)) *
self._config.get('startup_candle_count', 0))
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
pair=pair,
timeframe=timeframe or self._config['timeframe'],
datadir=self._config['datadir'],
timerange=timerange,
data_format=self._config.get('dataformat_ohlcv', 'json'),
candle_type=_candle_type,
)
return self.__cached_pairs_backtesting[saved_pair].copy()
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
"""
Loads backtest data and returns the data combined with the timerange
as tuple.
"""
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
data = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=timerange,
startup_candles=self.required_startup,
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
)
min_date, max_date = history.get_timerange(data)
logger.info(
f'Loading data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
# Adjust startts forward if not enough data is available
timerange.adjust_start_if_necessary(
timeframe_to_seconds(self.timeframe), self.required_startup,
min_date)
return data, timerange
def test_hdf5datahandler_ohlcv_load_and_resave(testdatadir, tmpdir):
tmpdir1 = Path(tmpdir)
dh = HDF5DataHandler(testdatadir)
ohlcv = dh.ohlcv_load('UNITTEST/BTC', '5m')
assert isinstance(ohlcv, DataFrame)
assert len(ohlcv) > 0
file = tmpdir1 / 'UNITTEST_NEW-5m.h5'
assert not file.is_file()
dh1 = HDF5DataHandler(tmpdir1)
dh1.ohlcv_store('UNITTEST/NEW', '5m', ohlcv)
assert file.is_file()
assert not ohlcv[ohlcv['date'] < '2018-01-15'].empty
# Data gores from 2018-01-10 - 2018-01-30
timerange = TimeRange.parse_timerange('20180115-20180119')
# Call private function to ensure timerange is filtered in hdf5
ohlcv = dh._ohlcv_load('UNITTEST/BTC', '5m', timerange)
ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', '5m', timerange)
assert len(ohlcv) == len(ohlcv1)
assert ohlcv.equals(ohlcv1)
assert ohlcv[ohlcv['date'] < '2018-01-15'].empty
assert ohlcv[ohlcv['date'] > '2018-01-19'].empty
# Try loading inexisting file
ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', '5m')
assert ohlcv.empty
def load_data_test(what, testdatadir):
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = history.load_pair_history(pair='UNITTEST/BTC', datadir=testdatadir,
timeframe='1m', timerange=timerange,
drop_incomplete=False,
fill_up_missing=False)
base = 0.001
if what == 'raise':
data.loc[:, 'open'] = data.index * base
data.loc[:, 'high'] = data.index * base + 0.0001
data.loc[:, 'low'] = data.index * base - 0.0001
data.loc[:, 'close'] = data.index * base
if what == 'lower':
data.loc[:, 'open'] = 1 - data.index * base
data.loc[:, 'high'] = 1 - data.index * base + 0.0001
data.loc[:, 'low'] = 1 - data.index * base - 0.0001
data.loc[:, 'close'] = 1 - data.index * base
if what == 'sine':
hz = 0.1 # frequency
data.loc[:, 'open'] = np.sin(data.index * hz) / 1000 + base
data.loc[:, 'high'] = np.sin(data.index * hz) / 1000 + base + 0.0001
data.loc[:, 'low'] = np.sin(data.index * hz) / 1000 + base - 0.0001
data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base
return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC',
fill_missing=True)}
def test_backtest_1min_timeframe(default_conf, fee, mocker,
testdatadir) -> None:
default_conf['ask_strategy']['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
# Run a backtesting for an exiting 1min timeframe
timerange = TimeRange.parse_timerange('1510688220-1510700340')
data = history.load_data(datadir=testdatadir,
timeframe='1m',
pairs=['UNITTEST/BTC'],
timerange=timerange)
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)
results = backtesting.backtest(
processed=processed,
stake_amount=default_conf['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=1,
position_stacking=False,
)
assert not results.empty
assert len(results) == 1
def test_generate_profit_graph():
filename = history.make_testdata_path(None) / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["POWR/BTC", "XLM/BTC"]
tickers = history.load_data(datadir=None,
pairs=pairs,
ticker_interval='5m',
timerange=timerange
)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs, tickers, trades)
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Profit plot"
figure = fig.layout.figure
assert len(figure.data) == 4
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scattergl)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scattergl)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scattergl)
def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):
pair = 'XRP/ETH'
file1 = testdatadir / 'XRP_ETH-1m.json'
file5 = testdatadir / 'XRP_ETH-5m.json'
# Compare downloaded dataset with converted dataset
dfbak_1m = load_pair_history(datadir=testdatadir,
timeframe="1m",
pair=pair)
dfbak_5m = load_pair_history(datadir=testdatadir,
timeframe="5m",
pair=pair)
_backup_file(file1, copy_file=True)
_backup_file(file5)
tr = TimeRange.parse_timerange('20191011-20191012')
convert_trades_to_ohlcv([pair],
timeframes=['1m', '5m'],
datadir=testdatadir,
timerange=tr,
erase=True)
assert log_has("Deleting existing data for pair XRP/ETH, interval 1m.",
caplog)
# Load new data
df_1m = load_pair_history(datadir=testdatadir, timeframe="1m", pair=pair)
df_5m = load_pair_history(datadir=testdatadir, timeframe="5m", pair=pair)
assert df_1m.equals(dfbak_1m)
assert df_5m.equals(dfbak_5m)
_clean_test_file(file1)
_clean_test_file(file5)
def test_refresh_backtest_trades_data(mocker, default_conf, markets, caplog,
testdatadir):
dl_mock = mocker.patch(
'freqtrade.data.history.history_utils._download_trades_history',
MagicMock())
mocker.patch('freqtrade.exchange.Exchange.markets',
PropertyMock(return_value=markets))
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
mocker.patch.object(Path, "unlink", MagicMock())
ex = get_patched_exchange(mocker, default_conf)
timerange = TimeRange.parse_timerange("20190101-20190102")
unavailable_pairs = refresh_backtest_trades_data(
exchange=ex,
pairs=["ETH/BTC", "XRP/BTC", "XRP/ETH"],
datadir=testdatadir,
timerange=timerange,
erase=True)
assert dl_mock.call_count == 2
assert dl_mock.call_args[1]['timerange'].starttype == 'date'
assert log_has("Downloading trades for pair ETH/BTC.", caplog)
assert unavailable_pairs == ["XRP/ETH"]
assert log_has("Skipping pair XRP/ETH...", caplog)
def test_create_cum_profit1(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
# Move close-time to "off" the candle, to make sure the logic still works
bt_data.loc[:, 'close_date'] = bt_data.loc[:, 'close_date'] + DateOffset(
seconds=20)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="TRX/BTC",
timeframe='5m',
datadir=testdatadir,
timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
with pytest.raises(ValueError, match='Trade dataframe empty.'):
create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'NOTAPAIR'],
"cum_profits",
timeframe="5m")
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
data = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=timerange,
startup_candles=self.required_startup,
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
)
min_date, max_date = history.get_timerange(data)
logger.info('Loading data from %s up to %s (%s days)..',
min_date.isoformat(), max_date.isoformat(),
(max_date - min_date).days)
# Adjust startts forward if not enough data is available
timerange.adjust_start_if_necessary(
timeframe_to_seconds(self.timeframe), self.required_startup,
min_date)
return data, timerange
def test_backtest_1min_timeframe(default_conf, fee, mocker,
testdatadir) -> None:
default_conf['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount",
return_value=0.00001)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
# Run a backtesting for an exiting 1min timeframe
timerange = TimeRange.parse_timerange('1510688220-1510700340')
data = history.load_data(datadir=testdatadir,
timeframe='1m',
pairs=['UNITTEST/BTC'],
timerange=timerange)
processed = backtesting.strategy.advise_all_indicators(data)
min_date, max_date = get_timerange(processed)
results = backtesting.backtest(
processed=processed,
start_date=min_date,
end_date=max_date,
max_open_trades=1,
position_stacking=False,
)
assert not results['results'].empty
assert len(results['results']) == 1
def init_plotscript(config):
"""
Initialize objects needed for plotting
:return: Dict with tickers, trades and pairs
"""
if "pairs" in config:
pairs = config["pairs"]
else:
pairs = config["exchange"]["pair_whitelist"]
# Set timerange to use
timerange = TimeRange.parse_timerange(config.get("timerange"))
tickers = history.load_data(
datadir=Path(str(config.get("datadir"))),
pairs=pairs,
ticker_interval=config.get('ticker_interval', '5m'),
timerange=timerange,
)
trades = load_trades(
config['trade_source'],
db_url=config.get('db_url'),
exportfilename=config.get('exportfilename'),
)
return {
"tickers": tickers,
"trades": trades,
"pairs": pairs,
}
def test_add_profit(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = history.load_pair_history(pair="TRX/BTC",
ticker_interval='5m',
datadir=testdatadir,
timerange=timerange)
fig = generate_empty_figure()
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
fig1 = add_profit(fig,
row=2,
data=cum_profits,
column='cum_profits',
name='Profits')
figure = fig1.layout.figure
profits = find_trace_in_fig_data(figure.data, "Profits")
assert isinstance(profits, go.Scatter)
assert profits.yaxis == "y2"
def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "ADA/BTC"]
tickers = history.load_data(datadir=testdatadir,
pairs=pairs,
ticker_interval='5m',
timerange=timerange)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs, tickers, trades, timeframe="5m")
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Freqtrade Profit plot"
assert fig.layout.yaxis.title.text == "Price"
assert fig.layout.yaxis2.title.text == "Profit"
assert fig.layout.yaxis3.title.text == "Profit"
figure = fig.layout.figure
assert len(figure.data) == 4
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scatter)
def start_download_data(args: Dict[str, Any]) -> None:
"""
Download data (former download_backtest_data.py script)
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
timerange = TimeRange()
if 'days' in config:
time_since = arrow.utcnow().shift(
days=-config['days']).strftime("%Y%m%d")
timerange = TimeRange.parse_timerange(f'{time_since}-')
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "
"Please check the documentation on how to configure this.")
dl_path = Path(config['datadir'])
logger.info(f'About to download pairs: {config["pairs"]}, '
f'intervals: {config["timeframes"]} to {dl_path}')
pairs_not_available: List[str] = []
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'], config).exchange
try:
if config.get('download_trades'):
pairs_not_available = refresh_backtest_trades_data(
exchange,
pairs=config["pairs"],
datadir=Path(config['datadir']),
timerange=timerange,
erase=config.get("erase"))
# Convert downloaded trade data to different timeframes
convert_trades_to_ohlcv(pairs=config["pairs"],
timeframes=config["timeframes"],
datadir=Path(config['datadir']),
timerange=timerange,
erase=config.get("erase"))
else:
pairs_not_available = refresh_backtest_ohlcv_data(
exchange,
pairs=config["pairs"],
timeframes=config["timeframes"],
dl_path=Path(config['datadir']),
timerange=timerange,
erase=config.get("erase"))
except KeyboardInterrupt:
sys.exit("SIGINT received, aborting ...")
finally:
if pairs_not_available:
logger.info(
f"Pairs [{','.join(pairs_not_available)}] not available "
f"on exchange {exchange.name}.")
def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
processed = strategy.ohlcvdata_to_dataframe(data)
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
def init_plotscript(config, markets: List, startup_candles: int = 0):
"""
Initialize objects needed for plotting
:return: Dict with candle (OHLCV) data, trades and pairs
"""
if "pairs" in config:
pairs = expand_pairlist(config['pairs'], markets)
else:
pairs = expand_pairlist(config['exchange']['pair_whitelist'], markets)
# Set timerange to use
timerange = TimeRange.parse_timerange(config.get('timerange'))
data = load_data(
datadir=config.get('datadir'),
pairs=pairs,
timeframe=config['timeframe'],
timerange=timerange,
startup_candles=startup_candles,
data_format=config.get('dataformat_ohlcv', 'json'),
)
if startup_candles and data:
min_date, max_date = get_timerange(data)
logger.info(f"Loading data from {min_date} to {max_date}")
timerange.adjust_start_if_necessary(
timeframe_to_seconds(config['timeframe']), startup_candles,
min_date)
no_trades = False
filename = config.get('exportfilename')
if config.get('no_trades', False):
no_trades = True
elif config['trade_source'] == 'file':
if not filename.is_dir() and not filename.is_file():
logger.warning("Backtest file is missing skipping trades.")
no_trades = True
try:
trades = load_trades(
config['trade_source'],
db_url=config.get('db_url'),
exportfilename=filename,
no_trades=no_trades,
strategy=config.get('strategy'),
)
except ValueError as e:
raise OperationalException(e) from e
if not trades.empty:
trades = trim_dataframe(trades, timerange, 'open_date')
return {
"ohlcv": data,
"trades": trades,
"pairs": pairs,
"timerange": timerange,
}
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 start_download_data(args: Namespace) -> None:
"""
Download data (former download_backtest_data.py script)
"""
config = setup_utils_configuration(args, RunMode.OTHER)
timerange = TimeRange()
if 'days' in config:
time_since = arrow.utcnow().shift(
days=-config['days']).strftime("%Y%m%d")
timerange = TimeRange.parse_timerange(f'{time_since}-')
dl_path = Path(config['datadir'])
logger.info(f'About to download pairs: {config["pairs"]}, '
f'intervals: {config["timeframes"]} to {dl_path}')
pairs_not_available = []
try:
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'],
config).exchange
for pair in config["pairs"]:
if pair not in exchange.markets:
pairs_not_available.append(pair)
logger.info(f"Skipping pair {pair}...")
continue
for ticker_interval in config["timeframes"]:
pair_print = pair.replace('/', '_')
filename = f'{pair_print}-{ticker_interval}.json'
dl_file = dl_path.joinpath(filename)
if config.get("erase") and dl_file.exists():
logger.info(
f'Deleting existing data for pair {pair}, interval {ticker_interval}.'
)
dl_file.unlink()
logger.info(
f'Downloading pair {pair}, interval {ticker_interval}.')
download_pair_history(datadir=dl_path,
exchange=exchange,
pair=pair,
ticker_interval=str(ticker_interval),
timerange=timerange)
except KeyboardInterrupt:
sys.exit("SIGINT received, aborting ...")
finally:
if pairs_not_available:
logger.info(
f"Pairs [{','.join(pairs_not_available)}] not available "
f"on exchange {config['exchange']['name']}.")
# configuration.resolve_pairs_list()
print(config)
def test_advise_all_indicators(default_conf, testdatadir) -> None:
strategy = StrategyResolver.load_strategy(default_conf)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = load_data(testdatadir,
'1m', ['UNITTEST/BTC'],
timerange=timerange,
fill_up_missing=True)
processed = strategy.advise_all_indicators(data)
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest_results/backtest-result_new.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "XLM/BTC"]
trades = trades[
trades['close_date'] < pd.Timestamp('2018-01-12', tz='UTC')]
data = history.load_data(datadir=testdatadir,
pairs=pairs,
timeframe='5m',
timerange=timerange)
trades = trades[trades['pair'].isin(pairs)]
fig = generate_profit_graph(pairs,
data,
trades,
timeframe="5m",
stake_currency='BTC')
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == "Freqtrade Profit plot"
assert fig.layout.yaxis.title.text == "Price"
assert fig.layout.yaxis2.title.text == "Profit BTC"
assert fig.layout.yaxis3.title.text == "Profit BTC"
figure = fig.layout.figure
assert len(figure.data) == 7
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter)
drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 35.69%")
assert isinstance(drawdown, go.Scatter)
parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
assert isinstance(parallel, go.Scatter)
underwater = find_trace_in_fig_data(figure.data, "Underwater Plot")
assert isinstance(underwater, go.Scatter)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scatter)
with pytest.raises(OperationalException, match=r"No trades found.*"):
# Pair cannot be empty - so it's an empty dataframe.
generate_profit_graph(pairs,
data,
trades.loc[trades['pair'].isnull()],
timeframe="5m",
stake_currency='BTC')
def test_ohlcvdata_to_dataframe_copy(mocker, default_conf, testdatadir) -> None:
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
strategy.ohlcvdata_to_dataframe(data)
assert aimock.call_count == 1
# Ensure that a copy of the dataframe is passed to advice_indicators
assert aimock.call_args_list[0][0][0] is not data
def test_create_cum_profit():
filename = make_testdata_path(None) / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="POWR/BTC", ticker_interval='5m',
datadir=None, timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'POWR/BTC'],
"cum_profits")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
def load_data_test(what, testdatadir):
timerange = TimeRange.parse_timerange('1510694220-1510700340')
pair = history.load_tickerdata_file(testdatadir,
timeframe='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 __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
self.config = config
self.exchange = exchange
self.strategy: IStrategy = strategy
self.edge_config = self.config.get('edge', {})
self._cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
self._final_pairs: list = []
# checking max_open_trades. it should be -1 as with Edge
# the number of trades is determined by position size
if self.config['max_open_trades'] != float('inf'):
logger.critical('max_open_trades should be -1 in config !')
if self.config['stake_amount'] != UNLIMITED_STAKE_AMOUNT:
raise OperationalException(
'Edge works only with unlimited stake amount')
self._capital_ratio: float = self.config['tradable_balance_ratio']
self._allowed_risk: float = self.edge_config.get('allowed_risk')
self._since_number_of_days: int = self.edge_config.get(
'calculate_since_number_of_days', 14)
self._last_updated: int = 0 # Timestamp of pairs last updated time
self._refresh_pairs = True
self._stoploss_range_min = float(
self.edge_config.get('stoploss_range_min', -0.01))
self._stoploss_range_max = float(
self.edge_config.get('stoploss_range_max', -0.05))
self._stoploss_range_step = float(
self.edge_config.get('stoploss_range_step', -0.001))
# calculating stoploss range
self._stoploss_range = np.arange(self._stoploss_range_min,
self._stoploss_range_max,
self._stoploss_range_step)
self._timerange: TimeRange = TimeRange.parse_timerange(
"%s-" % arrow.now().shift(
days=-1 * self._since_number_of_days).format('YYYYMMDD'))
if config.get('fee'):
self.fee = config['fee']
else:
try:
self.fee = self.exchange.get_fee(symbol=expand_pairlist(
self.config['exchange']['pair_whitelist'],
list(self.exchange.markets))[0])
except IndexError:
self.fee = None
def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
patch_exchange(mocker)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
backtesting = Backtesting(default_conf)
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
assert len(processed['UNITTEST/BTC']) == 102
# Load strategy to compare the result between Backtesting function and strategy are the same
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
processed2 = strategy.ohlcvdata_to_dataframe(data)
assert processed['UNITTEST/BTC'].equals(processed2['UNITTEST/BTC'])
def __init__(self, config: Dict[str, Any]) -> None:
self.config = config
# Reset keys for edge
remove_credentials(self.config)
self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.strategy = StrategyResolver.load_strategy(self.config)
validate_config_consistency(self.config)
self.edge = Edge(config, self.exchange, self.strategy)
# Set refresh_pairs to false for edge-cli (it must be true for edge)
self.edge._refresh_pairs = False
self.edge._timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
def test_create_cum_profit(testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
df = load_pair_history(pair="TRX/BTC",
timeframe='5m',
datadir=testdatadir,
timerange=timerange)
cum_profits = create_cum_profit(df.set_index('date'),
bt_data[bt_data["pair"] == 'TRX/BTC'],
"cum_profits",
timeframe="5m")
assert "cum_profits" in cum_profits.columns
assert cum_profits.iloc[0]['cum_profits'] == 0
assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
def init_plotscript(config):
"""
Initialize objects needed for plotting
:return: Dict with candle (OHLCV) data, trades and pairs
"""
if "pairs" in config:
pairs = config['pairs']
else:
pairs = config['exchange']['pair_whitelist']
# Set timerange to use
timerange = TimeRange.parse_timerange(config.get('timerange'))
data = load_data(
datadir=config.get('datadir'),
pairs=pairs,
timeframe=config.get('timeframe', '5m'),
timerange=timerange,
data_format=config.get('dataformat_ohlcv', 'json'),
)
no_trades = False
filename = config.get('exportfilename')
if config.get('no_trades', False):
no_trades = True
elif config['trade_source'] == 'file':
if not filename.is_dir() and not filename.is_file():
logger.warning("Backtest file is missing skipping trades.")
no_trades = True
trades = load_trades(
config['trade_source'],
db_url=config.get('db_url'),
exportfilename=filename,
no_trades=no_trades,
strategy=config.get('strategy'),
)
trades = trim_dataframe(trades, timerange, 'open_date')
return {
"ohlcv": data,
"trades": trades,
"pairs": pairs,
}
def test_download_data_no_markets(mocker, default_conf, caplog, testdatadir):
dl_mock = mocker.patch('freqtrade.data.history.download_pair_history',
MagicMock())
mocker.patch('freqtrade.exchange.Exchange.markets',
PropertyMock(return_value={}))
ex = get_patched_exchange(mocker, default_conf)
timerange = TimeRange.parse_timerange("20190101-20190102")
unav_pairs = refresh_backtest_ohlcv_data(exchange=ex,
pairs=["ETH/BTC", "XRP/BTC"],
timeframes=["1m", "5m"],
dl_path=testdatadir,
timerange=timerange,
erase=False)
assert dl_mock.call_count == 0
assert "ETH/BTC" in unav_pairs
assert "XRP/BTC" in unav_pairs
assert log_has("Skipping pair ETH/BTC...", caplog)