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Merge branch 'develop' into feat/short

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Matthias
2021-11-06 15:24:52 +01:00
parent c094ac5762 d99eaccb5a
commit ebc38159b8
57 changed files with 1202 additions and 197 deletions
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120
freqtrade/persistence/models.py
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@@ -1080,13 +1080,131 @@ class Trade(_DECL_BASE, LocalTrade):
return [
{
'pair': pair,
'profit': profit,
'profit_ratio': profit,
'profit': round(profit * 100, 2), # Compatibility mode
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for pair, profit, profit_abs, count in pair_rates
]
@staticmethod
def get_buy_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on buy tag performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
buy_tag_perf = Trade.query.with_entities(
Trade.buy_tag,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.buy_tag) \
.order_by(desc('profit_sum_abs')) \
.all()
return [
{
'buy_tag': buy_tag if buy_tag is not None else "Other",
'profit_ratio': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for buy_tag, profit, profit_abs, count in buy_tag_perf
]
@staticmethod
def get_sell_reason_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on sell reason performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
sell_tag_perf = Trade.query.with_entities(
Trade.sell_reason,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.sell_reason) \
.order_by(desc('profit_sum_abs')) \
.all()
return [
{
'sell_reason': sell_reason if sell_reason is not None else "Other",
'profit_ratio': profit,
'profit_pct': round(profit * 100, 2),
'profit_abs': profit_abs,
'count': count
}
for sell_reason, profit, profit_abs, count in sell_tag_perf
]
@staticmethod
def get_mix_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, based on buy_tag + sell_reason performance
Can either be average for all pairs or a specific pair provided
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if(pair is not None):
filters.append(Trade.pair == pair)
mix_tag_perf = Trade.query.with_entities(
Trade.id,
Trade.buy_tag,
Trade.sell_reason,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(*filters)\
.group_by(Trade.id) \
.order_by(desc('profit_sum_abs')) \
.all()
return_list: List[Dict] = []
for id, buy_tag, sell_reason, profit, profit_abs, count in mix_tag_perf:
buy_tag = buy_tag if buy_tag is not None else "Other"
sell_reason = sell_reason if sell_reason is not None else "Other"
if(sell_reason is not None and buy_tag is not None):
mix_tag = buy_tag + " " + sell_reason
i = 0
if not any(item["mix_tag"] == mix_tag for item in return_list):
return_list.append({'mix_tag': mix_tag,
'profit': profit,
'profit_abs': profit_abs,
'count': count})
else:
while i < len(return_list):
if return_list[i]["mix_tag"] == mix_tag:
return_list[i] = {
'mix_tag': mix_tag,
'profit': profit + return_list[i]["profit"],
'profit_abs': profit_abs + return_list[i]["profit_abs"],
'count': 1 + return_list[i]["count"]}
i += 1
[x.update({'profit': round(x['profit'] * 100, 2)}) for x in return_list]
return return_list
@staticmethod
def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
"""