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Enhancement #1300: Allow spread to be a dynamic sequence per candle #1408

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Enhancement #1300: Allow spread to be a dynamic sequence per candle #1408

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10 changes: 7 additions & 3 deletions backtesting/backtesting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -840,7 +840,8 @@ def _adjusted_price(self, size=None, price=None) -> float:
Long/short `price`, adjusted for spread.
In long positions, the adjusted price is a fraction higher, and vice versa.
"""
return (price or self.last_price) * (1 + copysign(self._spread, size))
spread = self._spread[self._i] if isinstance(self._spread, np.ndarray) else self._spread
return (price or self.last_price) * (1 + copysign(spread, size))

@property
def equity(self) -> float:
Expand Down Expand Up @@ -1210,8 +1211,11 @@ def __init__(self,
if not isinstance(data, pd.DataFrame):
raise TypeError("`data` must be a pandas.DataFrame with columns")
if not isinstance(spread, Number):
raise TypeError('`spread` must be a float value, percent of '
'entry order price')
if hasattr(spread, '__len__') and len(spread) == len(data):
spread = np.asarray(spread, dtype=float)
else:
raise TypeError('`spread` must be a float value (percent of '
'entry order price) or a sequence of the same length as data')
if not isinstance(commission, (Number, tuple)) and not callable(commission):
raise TypeError('`commission` must be a float percent of order value, '
'a tuple of `(fixed, relative)` commission, '
Expand Down