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BUG: Infer units for numeric timestamp indices #1402

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BUG: Infer units for numeric timestamp indices #1402

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9 changes: 7 additions & 2 deletions backtesting/backtesting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1224,10 +1224,15 @@ def __init__(self,
if (not isinstance(data.index, pd.DatetimeIndex) and
not isinstance(data.index, pd.RangeIndex) and
# Numeric index with most large numbers
(data.index.is_numeric() and
(pd.api.types.is_numeric_dtype(data.index.dtype) and
(data.index > pd.Timestamp('1975').timestamp()).mean() > .8)):
index_magnitude = np.nanmedian(np.abs(data.index))
# Infer seconds, milliseconds, microseconds, or nanoseconds by magnitude
unit = next((unit for unit, threshold in (
('s', 1e11), ('ms', 1e14), ('us', 1e17)
) if index_magnitude < threshold), 'ns')
try:
data.index = pd.to_datetime(data.index, infer_datetime_format=True)
data.index = pd.to_datetime(data.index, unit=unit)
except ValueError:
pass

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18 changes: 18 additions & 0 deletions backtesting/test/_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -131,6 +131,24 @@ def test_data_invalid(self):
with self.assertRaises(ValueError):
Backtest(GOOG.iloc[:0], SmaCross).run()

def test_data_numeric_timestamp_index(self):
timestamps = {
's': [1609459200, 1609545600],
'ms': [1609459200000, 1609545600000],
'us': [1609459200000000, 1609545600000000],
'ns': [1609459200000000000, 1609545600000000000],
}
expected = pd.DatetimeIndex(['2021-01-01', '2021-01-02'])

for unit, index in timestamps.items():
with self.subTest(unit=unit):
data = GOOG.iloc[:2].copy()
data.index = index

bt = Backtest(data, SmaCross)

self.assertTrue(bt._data.index.equals(expected))

def test_assertions(self):
class Assertive(Strategy):
def init(self):
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