Spread is Float but spread is typically different per row of the OHLC dataframe

### Enhancement description

so I was looking at the Backtest class and it accepts `spread: float = .0,` which is as far as I know spread is different per row and it's not fixed. I'm looking forward to the spread to be either np array or a required column in `data: pd.DataFrame,`.

### Additional info, images

this is what Mt5 return so as you notice the spread has it's own column because it's dynamically changing depending on time.

```
First 5 rows:
Open High Low Close Volume spread real_volume
time
2025-04-16 22:00:00 1.13864 1.14128 1.13847 1.13865 6294 8 0
2025-04-16 23:00:00 1.13866 1.13992 1.13816 1.13981 2788 8 0
2025-04-17 00:00:00 1.13980 1.13994 1.13939 1.13964 627 21 0
2025-04-17 01:00:00 1.13971 1.13997 1.13943 1.13995 1461 8 0
2025-04-17 02:00:00 1.13995 1.14093 1.13940 1.13955 2776 8 0
2025-04-17 03:00:00 1.13959 1.13969 1.13651 1.13677 6776 8 0
2025-04-17 04:00:00 1.13677 1.13692 1.13553 1.13654 6591 8 0
2025-04-17 05:00:00 1.13655 1.13819 1.13651 1.13782 3625 8 0
2025-04-17 06:00:00 1.13782 1.13808 1.13640 1.13642 3374 8 0
2025-04-17 07:00:00 1.13641 1.13699 1.13603 1.13623 2376 8 0
2025-04-17 08:00:00 1.13623 1.13712 1.13441 1.13522 3616 8 0
2025-04-17 09:00:00 1.13523 1.13711 1.13435 1.13589 6353 8 0
2025-04-17 10:00:00 1.13586 1.13789 1.13529 1.13770 8072 8 0
2025-04-17 11:00:00 1.13767 1.13885 1.13681 1.13785 7003 8 0
2025-04-17 12:00:00 1.13785 1.13808 1.13701 1.13727 5780 8 0
2025-04-17 13:00:00 1.13727 1.13766 1.13575 1.13596 7365 8 0
2025-04-17 14:00:00 1.13596 1.13701 1.13559 1.13564 5638 8 0
2025-04-17 15:00:00 1.13560 1.13680 1.13352 1.13564 12521 8 0
2025-04-17 16:00:00 1.13567 1.13776 1.13509 1.13611 12523 8 0
2025-04-17 17:00:00 1.13615 1.13857 1.13384 1.13496 10400 8 0
2025-04-17 18:00:00 1.13498 1.13766 1.13476 1.13632 7736 8 0
2025-04-17 19:00:00 1.13632 1.13712 1.13398 1.13505 8103 8 0
2025-04-17 20:00:00 1.13505 1.13538 1.13410 1.13510 4468 8 0
2025-04-17 21:00:00 1.13511 1.13752 1.13430 1.13733 5151 8 0
2025-04-17 22:00:00 1.13732 1.13760 1.13685 1.13731 3522 8 0
2025-04-17 23:00:00 1.13732 1.13766 1.13615 1.13619 1848 8 0
2025-04-18 00:00:00 1.13614 1.13688 1.13587 1.13666 334 41 0
2025-04-18 01:00:00 1.13674 1.13709 1.13656 1.13675 3927 8 0
2025-04-18 02:00:00 1.13675 1.13747 1.13657 1.13727 701 8 0
2025-04-18 03:00:00 1.13727 1.13862 1.13611 1.13740 3889 8 0
```

Start at the Backtest entry point and trace how the OHLC pandas DataFrame and scalar spread are consumed during simulation. Check the existing tests around Backtest inputs and transaction costs, if present. Done means variable spread data can be supplied per row while existing fixed-spread usage remains understood and covered.

Written by the indexing model from the issue text.