[AtomicGlance]

Summary

Fixes #1300.

Backtest(..., spread=...) now accepts either the existing scalar rate or a one-dimensional per-bar array-like value. A pandas Series must use the same index as the OHLC data. Values are validated as finite, numeric, and non-negative, and are applied at the bar where an order is filled. Scalar spreads keep the existing execution path and results.

The spread remains a relative rate, consistent with the current API. Data-source spreads expressed in price units can be converted to rates before passing them to Backtest.

Tests

• scalar and constant Series spreads produce identical trades and equity curves
• variable spreads affect market, limit, and stop fills at the fill bar
• long and short fills use the correct direction
• invalid length, shape, type, index, NaN, infinite, and negative values are rejected
• full backtesting/test/_test.py suite: 83 passed, 1 skipped

[AtomicGlance]

I reran the full backtesting.py test module on this branch (83 passed, 1 skipped). Before I make any further API changes, could you confirm that a spread sequence/Series aligned to the input bars is the preferred interface alongside the existing scalar value? I’ve kept the current spread convention and apply the value from the actual fill bar for market, limit, and stop orders. I’d also appreciate confirmation on whether a Series must have an identical index and how missing values should be handled.

[AtomicGlance]

Hi, following up on the per-bar spread proposal here and the trade-count addition in #1394. Before doing more work, I’d appreciate your view on whether these APIs fit the project’s direction. In particular, is requiring a spread Series to match the data index the interface you’d prefer? If either feature is outside the intended scope, that would also be helpful to know. Thanks!