[Autoloop] [Autoloop: perf-comparison] Experiment Log 2026-04

### Iteration 274 — 2026-04-21 07:36 UTC — [Run](https://github.com/githubnext/tsessebe/actions/runs/24710058006)
- **Status**: ✅ Accepted
- **Change**: Rewrote run_benchmarks.sh (parallel tsx, 8 workers, 30s timeout); added bench_numeric_extended_fn and bench_window_extended_fn
- **Metric**: 372 (previous best: 368, delta: +4)
- **Commit**: ebc7df3

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### Iteration 150 — 2026-04-17 10:51 UTC — [Run](https://github.com/githubnext/tsessebe/actions/runs/24561344321)
- **Status**: ✅ Accepted
- **Change**: Added 5 benchmark pairs: replace_series, isnull_notnull, to_numeric_scalar, dataframe_assign_fn, dataframe_isin_fn
- **Metric**: 473 (previous best: 468, delta: +5)
- **Commit**: 114fbab

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🤖 *Autoloop — an iterative optimization agent for this repository.*

| | |
|---|---|
| **Branch** | [`autoloop/perf-comparison`](https://github.com/githubnext/tsessebe/tree/autoloop/perf-comparison) |
| **Pull Request** | #128 |
| **State File** | [`perf-comparison.md`](https://github.com/githubnext/tsessebe/blob/memory/autoloop/perf-comparison.md) |

## Program

**Goal**: Systematically benchmark every tsb function against its pandas equivalent, one function per iteration.
**Target files**: `benchmarks/**`, `playground/benchmarks.html`, `playground/index.html`
**Metric**: benchmarked_functions (higher is better)
**Current best**: 48 (established in iteration 12)

## Iteration History

### Iteration 12 — 2026-04-12 17:15 UTC — [Run](https://github.com/githubnext/tsessebe/actions/runs/24311975652)
- **Status**: ✅ Accepted
- **Change**: Add 10 new benchmark pairs: rank, clip, series_abs, where, isin, duplicated, drop_duplicates, interpolate, rolling_std, unstack. Re-add all 37 prior pairs. Total 48 matched TS+Python pairs.
- **Metric**: 48 (previous best: 38, delta: +10)
- **Commit**: 7b639cc

### Iters 1–11 — 2026-04-12 11:44–17:10 UTC
- Progressively built up benchmark coverage from 1 to 38 pairs across 11 iterations.

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Inizia esaminando PR #128, il branch autoloop/perf-comparison e i target dei benchmark in benchmarks/**, playground/benchmarks.html e playground/index.html. L’obiettivo dichiarato è sottoporre a benchmark ogni funzione tsb rispetto al suo equivalente pandas, ma l’issue è più un registro continuo di un esperimento generato che un’attività circoscritta; completarla significherebbe estendere questa copertura e aggiornare la metrica registrata.

Scritto dal modello di indicizzazione a partire dal testo della issue.