docs: refresh Python benchmark figures from a fresh measured run (#206)

The published Python benchmark tables (README/BENCHMARKS.md) were a stale, incoherent run. Re-measured locally with the current build (wickra 0.6.5, post batch fast-paths) via `compare_libraries.py` on the same 9950X.

- **Streaming vs talipp:** 11-56x (was 9-58x).
- **Batch:** real per-indicator numbers; MACD and ATR were notably off in the old table.
- **Prose:** Wickra beats TA-Lib on RSI and ATR (no longer MACD, which now trails 130 vs 111 us).

Rust tables unchanged. Numbers are a single coherent run; absolute us still depend on machine state (caveat already in the doc).

BENCHMARKS.md

@@ -26,15 +26,15 @@ was built to expose.
 
 | Indicator        | **★ Wickra** | talipp           | TA-Lib (recompute)    |
 |------------------|------------------:|------------------|-----------------------|
-| SMA(20)          | **0.063 µs ★**    | 0.59 µs (9×)     | 204 µs (3 300×)       |
-| EMA(20)          | **0.060 µs ★**    | 0.72 µs (12×)    | 212 µs (3 500×)       |
-| RSI(14)          | **0.065 µs ★**    | 1.06 µs (16×)    | 230 µs (3 600×)       |
-| MACD(12, 26, 9)  | **0.078 µs ★**    | 4.22 µs (54×)    | 245 µs (3 100×)       |
-| Bollinger(20, 2) | **0.088 µs ★**    | 5.15 µs (58×)    | 229 µs (2 600×)       |
+| SMA(20)          | **0.089 µs ★**    | 0.96 µs (11×)    | 422 µs (4 700×)       |
+| EMA(20)          | **0.111 µs ★**    | 1.19 µs (11×)    | 430 µs (3 900×)       |
+| RSI(14)          | **0.061 µs ★**    | 0.95 µs (16×)    | 298 µs (4 900×)       |
+| MACD(12, 26, 9)  | **0.079 µs ★**    | 3.30 µs (42×)    | 327 µs (4 100×)       |
+| Bollinger(20, 2) | **0.089 µs ★**    | 4.97 µs (56×)    | 296 µs (3 300×)       |
 
-Against the only other incremental Python peer Wickra is **9–58× faster**;
-against the recompute-on-every-tick libraries it is **2 600–14 000× faster**
-(`finta` RSI hits 14 000×). tulipy / pandas-ta land in the same recompute band
+Against the only other incremental Python peer Wickra is **11–56× faster**;
+against the recompute-on-every-tick libraries it is **2 800–19 000× faster**
+(`finta` RSI hits 19 000×). tulipy / pandas-ta land in the same recompute band
 as TA-Lib.
 
 **Rust — per-tick latency** (whole 50 000-bar series, lower = faster):
@@ -63,17 +63,17 @@ field everywhere.
 
 **Python** (20 000-bar pass, µs/op, lower = faster):
 
-| Indicator        | Wickra   | TA-Lib | tulipy | pandas-ta |
-|------------------|---------:|-------:|-------:|----------:|
-| SMA(20)          | 22.7     | **15.4** | 15.9 | 33.7      |
-| EMA(20)          | 30.8     | **30.3** | 31.1 | 48.8      |
-| RSI(14)          | 58.9     | 72.5   | **38.5** | 94.8    |
-| MACD(12, 26, 9)  | 71.7     | 99.1   | **33.5** | 207.6   |
-| Bollinger(20, 2) | 84.9     | 65.7   | **32.3** | 336.4   |
-| ATR(14)          | 52.0     | 79.4   | **31.9** | —        |
+| Indicator        | Wickra   | TA-Lib   | tulipy   | pandas-ta | finta    |
+|------------------|---------:|---------:|---------:|----------:|---------:|
+| SMA(20)          | 22.2     | **15.6** | 15.9     | 32.7      | 290.1    |
+| EMA(20)          | 30.5     | **30.4** | 30.9     | 46.7      | 198.5    |
+| RSI(14)          | 52.3     | 72.0     | **34.2** | 88.8      | 812.3    |
+| MACD(12, 26, 9)  | 129.8    | 111.1    | **38.4** | 286.8     | 716.7    |
+| Bollinger(20, 2) | 87.2     | 74.6     | **37.9** | 474.3     | 1255.5   |
+| ATR(14)          | 74.7     | 87.3     | **35.5** | —         | 3496.4   |
 
-Wickra beats TA-Lib on RSI, MACD and ATR and the whole Python field on every
-row; tulipy's SIMD C stays ahead on the heavier indicators.
+Wickra beats pandas-ta and finta on every row and TA-Lib on RSI and ATR;
+tulipy's SIMD C (and TA-Lib on SMA/EMA) lead the remaining rows.
 
 **Rust** (50 000-bar pass, µs, lower = faster). Only Wickra and `kand` expose a
 batch API; `ta-rs` and `yata` are streaming-only:

README.md

@@ -78,7 +78,7 @@ times to get there.
   runs a real warmup, and returns an `Option` so a single bad tick can't silently
   poison state. `batch == streaming` is **bit-exact, fuzzed and 100 %-line-covered
   for all 479 indicators**.
-- **Orders of magnitude faster where it counts.** In streaming Wickra is **9–58×**
+- **Orders of magnitude faster where it counts.** In streaming Wickra is **11–56×**
   faster than the only other incremental peer and **thousands of times** faster
   than recompute-on-every-tick libraries. On batch it wins several rows outright
   and trades the simple recurrences (SMA, EMA, MACD) for its guarantees — and
@@ -118,7 +118,7 @@ useful version of that itch is the one other people can build on too.
 ## Benchmarks
 
 Wickra updates every indicator in **O(1)** per tick. In **streaming** — the
-workload it is built for — it is **9–58× faster** than the only other incremental
+workload it is built for — it is **11–56× faster** than the only other incremental
 peer and **thousands of times** faster than recompute-on-every-tick libraries.
 **Batch** is competitive: it wins several rows outright and trades a few µs
 elsewhere for `None`-warmup, NaN-safety and bit-exact `batch == streaming`.