def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
timeframe: str) -> make_subplots:
"""
Add scatter points indicating max drawdown
"""
try:
max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades)
drawdown = go.Scatter(
x=[highdate, lowdate],
y=[
df_comb.loc[timeframe_to_prev_date(timeframe, highdate),
'cum_profit'],
df_comb.loc[timeframe_to_prev_date(timeframe, lowdate),
'cum_profit'],
],
mode='markers',
name=f"Max drawdown {max_drawdown:.2%}",
text=f"Max drawdown {max_drawdown:.2%}",
marker=dict(symbol='square-open',
size=9,
line=dict(width=2),
color='green'))
fig.add_trace(drawdown, row, 1)
except ValueError:
logger.warning("No trades found - not plotting max drawdown.")
return fig
def test_ccxt_fetch_mark_price_history(self, exchange_futures):
exchange, exchangename = exchange_futures
if not exchange:
# exchange_futures only returns values for supported exchanges
return
pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair'])
since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000)
pair_tf = (pair, '1h', CandleType.MARK)
mark_ohlcv = exchange.refresh_latest_ohlcv(
[pair_tf],
since_ms=since,
drop_incomplete=False)
assert isinstance(mark_ohlcv, dict)
expected_tf = '1h'
mark_candles = mark_ohlcv[pair_tf]
this_hour = timeframe_to_prev_date(expected_tf)
prev_hour = timeframe_to_prev_date(expected_tf, this_hour - timedelta(minutes=1))
assert mark_candles[mark_candles['date'] == prev_hour].iloc[0]['open'] != 0.0
assert mark_candles[mark_candles['date'] == this_hour].iloc[0]['open'] != 0.0
def test_fetch_ohlcv(self, exchange):
exchange, exchangename = exchange
pair = EXCHANGES[exchangename]['pair']
timeframe = EXCHANGES[exchangename]['timeframe']
pair_tf = (pair, timeframe)
ohlcv = exchange.refresh_latest_ohlcv([pair_tf])
assert isinstance(ohlcv, dict)
assert len(ohlcv[pair_tf]) == len(exchange.klines(pair_tf))
# assert len(exchange.klines(pair_tf)) > 200
# Assume 90% uptime ...
assert len(exchange.klines(pair_tf)) > exchange.ohlcv_candle_limit(timeframe) * 0.90
# Check if last-timeframe is within the last 2 intervals
now = datetime.now(timezone.utc) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2))
assert exchange.klines(pair_tf).iloc[-1]['date'] >= timeframe_to_prev_date(timeframe, now)
def test_ccxt_fetch_funding_rate_history(self, exchange_futures):
exchange, exchangename = exchange_futures
if not exchange:
# exchange_futures only returns values for supported exchanges
return
pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair'])
since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000)
timeframe_ff = exchange._ft_has.get('funding_fee_timeframe',
exchange._ft_has['mark_ohlcv_timeframe'])
pair_tf = (pair, timeframe_ff, CandleType.FUNDING_RATE)
funding_ohlcv = exchange.refresh_latest_ohlcv(
[pair_tf],
since_ms=since,
drop_incomplete=False)
assert isinstance(funding_ohlcv, dict)
rate = funding_ohlcv[pair_tf]
this_hour = timeframe_to_prev_date(timeframe_ff)
hour1 = timeframe_to_prev_date(timeframe_ff, this_hour - timedelta(minutes=1))
hour2 = timeframe_to_prev_date(timeframe_ff, hour1 - timedelta(minutes=1))
hour3 = timeframe_to_prev_date(timeframe_ff, hour2 - timedelta(minutes=1))
val0 = rate[rate['date'] == this_hour].iloc[0]['open']
val1 = rate[rate['date'] == hour1].iloc[0]['open']
val2 = rate[rate['date'] == hour2].iloc[0]['open']
val3 = rate[rate['date'] == hour3].iloc[0]['open']
# Test For last 4 hours
# Avoids random test-failure when funding-fees are 0 for a few hours.
assert val0 != 0.0 or val1 != 0.0 or val2 != 0.0 or val3 != 0.0
# We expect funding rates to be different from 0.0 - or moving around.
assert (
rate['open'].max() != 0.0 or rate['open'].min() != 0.0 or
(rate['open'].min() != rate['open'].max())
)
