def test_backtest(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)
pair = 'UNITTEST/BTC'
timerange = TimeRange('date', None, 1517227800, 0)
data = history.load_data(datadir=testdatadir,
timeframe='5m',
pairs=['UNITTEST/BTC'],
timerange=timerange)
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(data_processed)
results = backtesting.backtest({
'stake_amount': default_conf['stake_amount'],
'processed': data_processed,
'max_open_trades': 10,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
})
assert not results.empty
assert len(results) == 2
expected = pd.DataFrame({
'pair': [pair, pair],
'profit_percent': [0.0, 0.0],
'profit_abs': [0.0, 0.0],
'open_time':
pd.to_datetime([
Arrow(2018, 1, 29, 18, 40, 0).datetime,
Arrow(2018, 1, 30, 3, 30, 0).datetime
],
utc=True),
'close_time':
pd.to_datetime([
Arrow(2018, 1, 29, 22, 35, 0).datetime,
Arrow(2018, 1, 30, 4, 10, 0).datetime
],
utc=True),
'open_index': [78, 184],
'close_index': [125, 192],
'trade_duration': [235, 40],
'open_at_end': [False, False],
'open_rate': [0.104445, 0.10302485],
'close_rate': [0.104969, 0.103541],
'sell_reason': [SellType.ROI, SellType.ROI]
})
pd.testing.assert_frame_equal(results, expected)
data_pair = data_processed[pair]
for _, t in results.iterrows():
ln = data_pair.loc[data_pair["date"] == t["open_time"]]
# Check open trade rate alignes to open rate
assert ln is not None
assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
# check close trade rate alignes to close rate or is between high and low
ln = data_pair.loc[data_pair["date"] == t["close_time"]]
assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6)
or round(ln.iloc[0]["low"], 6) < round(
t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
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_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 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 = load_data(
datadir=config.get("datadir"),
pairs=pairs,
timeframe=config.get('ticker_interval', '5m'),
timerange=timerange,
data_format=config.get('dataformat_ohlcv', 'json'),
)
trades = load_trades(
config['trade_source'],
db_url=config.get('db_url'),
exportfilename=config.get('exportfilename'),
)
trades = trim_dataframe(trades, timerange, 'open_time')
return {
"tickers": tickers,
"trades": trades,
"pairs": pairs,
}
def test_add_indicators(default_conf, caplog):
pair = "UNITTEST/BTC"
timerange = TimeRange(None, 'line', 0, -1000)
data = history.load_pair_history(pair=pair, ticker_interval='1m',
datadir=None, timerange=timerange)
indicators1 = ["ema10"]
indicators2 = ["macd"]
# Generate buy/sell signals and indicators
strat = DefaultStrategy(default_conf)
data = strat.analyze_ticker(data, {'pair': pair})
fig = generage_empty_figure()
# Row 1
fig1 = add_indicators(fig=deepcopy(fig), row=1, indicators=indicators1, data=data)
figure = fig1.layout.figure
ema10 = find_trace_in_fig_data(figure.data, "ema10")
assert isinstance(ema10, go.Scatter)
assert ema10.yaxis == "y"
fig2 = add_indicators(fig=deepcopy(fig), row=3, indicators=indicators2, data=data)
figure = fig2.layout.figure
macd = find_trace_in_fig_data(figure.data, "macd")
assert isinstance(macd, go.Scatter)
assert macd.yaxis == "y3"
# No indicator found
fig3 = add_indicators(fig=deepcopy(fig), row=3, indicators=['no_indicator'], data=data)
assert fig == fig3
assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog)
def test_hdf5datahandler_ohlcv_load_and_resave(testdatadir):
dh = HDF5DataHandler(testdatadir)
ohlcv = dh.ohlcv_load('UNITTEST/BTC', '5m')
assert isinstance(ohlcv, DataFrame)
assert len(ohlcv) > 0
file = testdatadir / 'UNITTEST_NEW-5m.h5'
assert not file.is_file()
dh.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 = dh._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
_clean_test_file(file)
# Try loading inexisting file
ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', '5m')
assert ohlcv.empty
def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, caplog):
row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
MagicMock(side_effect=fig_generating_mock))
trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
MagicMock(side_effect=fig_generating_mock))
pair = "UNITTEST/BTC"
timerange = TimeRange(None, 'line', 0, -1000)
data = history.load_pair_history(pair=pair, ticker_interval='1m',
datadir=None, timerange=timerange)
data['buy'] = 0
data['sell'] = 0
indicators1 = []
indicators2 = []
fig = generate_candlestick_graph(pair=pair, data=data, trades=None,
indicators1=indicators1, indicators2=indicators2)
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == pair
figure = fig.layout.figure
assert len(figure.data) == 2
# Candlesticks are plotted first
candles = find_trace_in_fig_data(figure.data, "Price")
assert isinstance(candles, go.Candlestick)
volume = find_trace_in_fig_data(figure.data, "Volume")
assert isinstance(volume, go.Bar)
assert row_mock.call_count == 2
assert trades_mock.call_count == 1
assert log_has("No buy-signals found.", caplog)
assert log_has("No sell-signals found.", caplog)
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)
assert not log_has('Could not convert NoDatapair to OHLCV.', caplog)
convert_trades_to_ohlcv(['NoDatapair'], timeframes=['1m', '5m'],
datadir=testdatadir, timerange=tr, erase=True)
assert log_has('Could not convert NoDatapair to OHLCV.', caplog)
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.config['exchange']['pair_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_ticker_interval(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.tickerdata_to_dataframe(data)
min_date, max_date = get_timeframe(processed)
results = backtesting.backtest({
'stake_amount': default_conf['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'position_stacking': False,
'start_date': min_date,
'end_date': max_date,
})
assert not results.empty
assert len(results) == 1
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 test_add_areas(default_conf, testdatadir, caplog):
pair = "UNITTEST/BTC"
timerange = TimeRange(None, 'line', 0, -1000)
data = history.load_pair_history(pair=pair,
timeframe='1m',
datadir=testdatadir,
timerange=timerange)
indicators = {
"macd": {
"color": "red",
"fill_color": "black",
"fill_to": "macdhist",
"fill_label": "MACD Fill"
}
}
ind_no_label = {"macd": {"fill_color": "red", "fill_to": "macdhist"}}
ind_plain = {"macd": {"fill_to": "macdhist"}}
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
# Generate buy/sell signals and indicators
data = strategy.analyze_ticker(data, {'pair': pair})
fig = generate_empty_figure()
# indicator mentioned in fill_to does not exist
fig1 = add_areas(fig, 1, data, {'ema10': {'fill_to': 'no_fill_indicator'}})
assert fig == fig1
assert log_has_re(r'fill_to: "no_fill_indicator" ignored\..*', caplog)
# indicator does not exist
fig2 = add_areas(fig, 1, data, {'no_indicator': {'fill_to': 'ema10'}})
assert fig == fig2
assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog)
# everythin given in plot config, row 3
fig3 = add_areas(fig, 3, data, indicators)
figure = fig3.layout.figure
fill_macd = find_trace_in_fig_data(figure.data, "MACD Fill")
assert isinstance(fill_macd, go.Scatter)
assert fill_macd.yaxis == "y3"
assert fill_macd.fillcolor == "black"
# label missing, row 1
fig4 = add_areas(fig, 1, data, ind_no_label)
figure = fig4.layout.figure
fill_macd = find_trace_in_fig_data(figure.data, "macd<>macdhist")
assert isinstance(fill_macd, go.Scatter)
assert fill_macd.yaxis == "y"
assert fill_macd.fillcolor == "red"
# fit_to only
fig5 = add_areas(fig, 1, data, ind_plain)
figure = fig5.layout.figure
fill_macd = find_trace_in_fig_data(figure.data, "macd<>macdhist")
assert isinstance(fill_macd, go.Scatter)
assert fill_macd.yaxis == "y"
def load_pair_history(pair: str,
ticker_interval: str,
datadir: Optional[Path],
timerange: TimeRange = TimeRange(None, None, 0, 0),
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
fill_up_missing: bool = True,
drop_incomplete: bool = True) -> DataFrame:
"""
Loads cached ticker history for the given pair.
:param pair: Pair to load data for
:param ticker_interval: Ticker-interval (e.g. "5m")
:param datadir: Path to the data storage location.
:param timerange: Limit data to be loaded to this timerange
:param refresh_pairs: Refresh pairs from exchange.
(Note: Requires exchange to be passed as well.)
:param exchange: Exchange object (needed when using "refresh_pairs")
:param fill_up_missing: Fill missing values with "No action"-candles
:param drop_incomplete: Drop last candle assuming it may be incomplete.
:return: DataFrame with ohlcv data
"""
# The user forced the refresh of pairs
if refresh_pairs:
download_pair_history(datadir=datadir,
exchange=exchange,
pair=pair,
ticker_interval=ticker_interval,
timerange=timerange)
pairdata = load_tickerdata_file(datadir,
pair,
ticker_interval,
timerange=timerange)
if pairdata:
if timerange.starttype == 'date' and pairdata[0][
0] > timerange.startts * 1000:
logger.warning(
'Missing data at start for pair %s, data starts at %s', pair,
arrow.get(pairdata[0][0] //
1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange.stoptype == 'date' and pairdata[-1][
0] < timerange.stopts * 1000:
logger.warning(
'Missing data at end for pair %s, data ends at %s', pair,
arrow.get(pairdata[-1][0] //
1000).strftime('%Y-%m-%d %H:%M:%S'))
return parse_ticker_dataframe(pairdata,
ticker_interval,
pair=pair,
fill_missing=fill_up_missing,
drop_incomplete=drop_incomplete)
else:
logger.warning(
f'No history data for pair: "{pair}", interval: {ticker_interval}. '
'Use --refresh-pairs-cached option or download_backtest_data.py '
'script to download the data')
return None
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.")
logger.info(f'About to download pairs: {config["pairs"]}, '
f'intervals: {config["timeframes"]} to {config["datadir"]}')
pairs_not_available: List[str] = []
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
try:
if config.get('download_trades'):
pairs_not_available = refresh_backtest_trades_data(
exchange, pairs=config["pairs"], datadir=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=config['datadir'], timerange=timerange, erase=config.get("erase"))
else:
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=config["pairs"], timeframes=config["timeframes"],
datadir=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 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_generate_candlestick_graph_no_trades(default_conf, mocker,
testdatadir):
row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
MagicMock(side_effect=fig_generating_mock))
trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
MagicMock(side_effect=fig_generating_mock))
pair = 'UNITTEST/BTC'
timerange = TimeRange(None, 'line', 0, -1000)
data = history.load_pair_history(pair=pair,
timeframe='1m',
datadir=testdatadir,
timerange=timerange)
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
# Generate buy/sell signals and indicators
data = strategy.analyze_ticker(data, {'pair': pair})
indicators1 = []
indicators2 = []
fig = generate_candlestick_graph(pair=pair,
data=data,
trades=None,
indicators1=indicators1,
indicators2=indicators2)
assert isinstance(fig, go.Figure)
assert fig.layout.title.text == pair
figure = fig.layout.figure
assert len(figure.data) == 6
# Candlesticks are plotted first
candles = find_trace_in_fig_data(figure.data, "Price")
assert isinstance(candles, go.Candlestick)
volume = find_trace_in_fig_data(figure.data, "Volume")
assert isinstance(volume, go.Bar)
buy = find_trace_in_fig_data(figure.data, "buy")
assert isinstance(buy, go.Scatter)
# All buy-signals should be plotted
assert int(data.buy.sum()) == len(buy.x)
sell = find_trace_in_fig_data(figure.data, "sell")
assert isinstance(sell, go.Scatter)
# All buy-signals should be plotted
assert int(data.sell.sum()) == len(sell.x)
assert find_trace_in_fig_data(figure.data, "Bollinger Band")
assert row_mock.call_count == 2
assert trades_mock.call_count == 1
def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) -> None:
ltfmock = mocker.patch('freqtrade.data.history.load_tickerdata_file',
MagicMock(return_value=None))
timerange = TimeRange('date', None, 1510639620, 0)
history.load_pair_history(pair='UNITTEST/BTC', timeframe='1m',
datadir=testdatadir, timerange=timerange,
startup_candles=20,
)
assert ltfmock.call_count == 1
assert ltfmock.call_args_list[0][1]['timerange'] != timerange
# startts is 20 minutes earlier
assert ltfmock.call_args_list[0][1]['timerange'].startts == timerange.startts - 20 * 60
def test_load_partial_missing(testdatadir, caplog) -> None:
# Make sure we start fresh - test missing data at start
start = arrow.get('2018-01-01T00:00:00')
end = arrow.get('2018-01-11T00:00:00')
tickerdata = history.load_data(testdatadir,
'5m', ['UNITTEST/BTC'],
startup_candles=20,
timerange=TimeRange('date', 'date',
start.timestamp,
end.timestamp))
assert log_has('Using indicator startup period: 20 ...', caplog)
# timedifference in 5 minutes
td = ((end - start).total_seconds() // 60 // 5) + 1
assert td != len(tickerdata['UNITTEST/BTC'])
start_real = tickerdata['UNITTEST/BTC'].iloc[0, 0]
assert log_has(
f'Missing data at start for pair '
f'UNITTEST/BTC, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
caplog)
# Make sure we start fresh - test missing data at end
caplog.clear()
start = arrow.get('2018-01-10T00:00:00')
end = arrow.get('2018-02-20T00:00:00')
tickerdata = history.load_data(datadir=testdatadir,
timeframe='5m',
pairs=['UNITTEST/BTC'],
timerange=TimeRange('date', 'date',
start.timestamp,
end.timestamp))
# timedifference in 5 minutes
td = ((end - start).total_seconds() // 60 // 5) + 1
assert td != len(tickerdata['UNITTEST/BTC'])
# Shift endtime with +5 - as last candle is dropped (partial candle)
end_real = arrow.get(tickerdata['UNITTEST/BTC'].iloc[-1,
0]).shift(minutes=5)
assert log_has(
f'Missing data at end for pair '
f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
caplog)
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: List[str] = []
try:
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'],
config).exchange
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 {config['exchange']['name']}.")
def test_trim_dataframe(testdatadir) -> None:
data = history.load_data(
datadir=testdatadir,
timeframe='1m',
pairs=['UNITTEST/BTC']
)['UNITTEST/BTC']
min_date = int(data.iloc[0]['date'].timestamp())
max_date = int(data.iloc[-1]['date'].timestamp())
data_modify = data.copy()
# Remove first 30 minutes (1800 s)
tr = TimeRange('date', None, min_date + 1800, 0)
data_modify = history.trim_dataframe(data_modify, tr)
assert not data_modify.equals(data)
assert len(data_modify) < len(data)
assert len(data_modify) == len(data) - 30
assert all(data_modify.iloc[-1] == data.iloc[-1])
assert all(data_modify.iloc[0] == data.iloc[30])
data_modify = data.copy()
# Remove last 30 minutes (1800 s)
tr = TimeRange(None, 'date', 0, max_date - 1800)
data_modify = history.trim_dataframe(data_modify, tr)
assert not data_modify.equals(data)
assert len(data_modify) < len(data)
assert len(data_modify) == len(data) - 30
assert all(data_modify.iloc[0] == data.iloc[0])
assert all(data_modify.iloc[-1] == data.iloc[-31])
data_modify = data.copy()
# Remove first 25 and last 30 minutes (1800 s)
tr = TimeRange('date', 'date', min_date + 1500, max_date - 1800)
data_modify = history.trim_dataframe(data_modify, tr)
assert not data_modify.equals(data)
assert len(data_modify) < len(data)
assert len(data_modify) == len(data) - 55
# first row matches 25th original row
assert all(data_modify.iloc[0] == data.iloc[25])
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_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 __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 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
