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refactor: make performance_query work in a dynamic way

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Matthias
2025-01-26 18:20:28 +01:00
parent 1aac8dfa59
commit 78c71cdf87
1 changed files with 22 additions and 16 deletions
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38
freqtrade/persistence/trade_model.py
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@@ -1914,18 +1914,14 @@ class Trade(ModelBase, LocalTrade):
return total_open_stake_amount or 0
@staticmethod
def get_overall_performance(start_date: datetime | None = None) -> list[dict[str, Any]]:
def _generic_performance_query(columns: list, filters: list, fallback: str = "") -> Select:
"""
Returns List of dicts containing all Trades, including profit and trade count
NOTE: Not supported in Backtesting.
Retrieve a generic select object to calculate performance grouped on `columns`.
"""
filters: list = [Trade.is_open.is_(False)]
if start_date:
filters.append(Trade.close_date >= start_date)
columns_coal = [func.coalesce(c, fallback).label(c.name) for c in columns]
pair_costs = (
select(
Trade.pair,
*columns_coal,
func.sum(
(
func.coalesce(Order.filled, Order.amount)
@@ -1939,34 +1935,44 @@ class Trade(ModelBase, LocalTrade):
*filters,
Order.ft_order_side == case((Trade.is_short.is_(True), "sell"), else_="buy"),
)
# Order.filled.gt > 0
.group_by(Trade.pair)
.group_by(*columns)
.cte("pair_costs")
)
trades_grouped = (
select(
Trade.pair,
*columns_coal,
func.sum(Trade.close_profit_abs).label("profit_sum_abs"),
func.count(Trade.pair).label("count"),
func.count(*columns_coal).label("count"),
)
.filter(*filters)
.group_by(Trade.pair)
.group_by(*columns_coal)
.cte("trades_grouped")
)
q = (
select(
trades_grouped.c.pair,
*[trades_grouped.c[x.name] for x in columns],
(trades_grouped.c.profit_sum_abs / pair_costs.c.cost_per_pair).label(
"profit_ratio"
),
trades_grouped.c.profit_sum_abs,
trades_grouped.c.count,
)
.join(pair_costs, trades_grouped.c.pair == pair_costs.c.pair)
.join(pair_costs, *[trades_grouped.c[x.name] == pair_costs.c[x.name] for x in columns])
.order_by(desc("profit_sum_abs"))
)
pair_rates = Trade.session.execute(q).all()
return q
@staticmethod
def get_overall_performance(start_date: datetime | None = None) -> list[dict[str, Any]]:
"""
Returns List of dicts containing all Trades, including profit and trade count
NOTE: Not supported in Backtesting.
"""
filters: list = [Trade.is_open.is_(False)]
if start_date:
filters.append(Trade.close_date >= start_date)
pair_rates_query = Trade._generic_performance_query([Trade.pair], filters)
pair_rates = Trade.session.execute(pair_rates_query).all()
return [
{
"pair": pair,