Honest tiered cross-library benchmark + streaming/batch perf (#186)
## Summary An honest, tiered cross-library benchmark — and the optimization pass it triggered. ### Performance (wickra-core, outputs unchanged) Profiling against the other Rust TA crates exposed real inefficiencies. Each benchmarked indicator is now **5–79% faster** in both streaming and batch: - **SMA, Bollinger**: flat `Box<[f64]>` ring buffers replace `VecDeque` (−69…79%). - **RSI**: `100·ag/(ag+al)` collapses three divisions into one; Wilder smoothing hoists `1/period` out of the hot path (−46%). - **ATR**: reciprocal hoisted (−42%). - **EMA/RSI/ATR**: per-tick `Option<f64>` hot state → bare `f64` + ready flag. Net result vs `kand`: Wickra now wins **RSI, Bollinger and ATR** (streaming), and ties `ta-rs` on SMA — up from losing every indicator 1.5–6× before. ### Benchmark harness New `crates/wickra-bench` (publish=false): a Criterion benchmark comparing Wickra against `kand`, `ta-rs` and `yata` on an identical BTCUSDT candle series, in streaming and batch modes. Peer APIs were verified against their source, not guessed. Wired into the nightly `cross-library-bench` workflow as a separate job. ### Honest README The benchmark section is rewritten into three layered tables (Rust core vs Rust crates; Python vs the Python ecosystem) that **show the losses as well as the wins**. The "only library that combines…" claim is gone; the new framing is breadth + multi-language reach + the deliberate safety trade-off that costs raw speed. Added an origin/why-slower rationale and a star CTA. ### Python benchmark Added `tulipy` runners and expanded per-tick streaming coverage to SMA/EMA/RSI/ MACD/Bollinger. `bench.in`/`bench.txt` now lock `TA-Lib` + `tulipy` (hash-pinned); `pandas-ta` stays out (it requires Python ≥ 3.12, the bench runs on 3.11). ### Notes - TA-Lib/tulipy numbers in the README Python table are marked ⧗ — they are produced by the CI Linux job (C extensions don't build cleanly on every desktop), not measured locally. - The matching `wickra-docs` prose update is committed separately and will be pushed with the release, per the docs-don't-lead-the-registries rule. Verified locally: `cargo fmt`, `cargo test --workspace --all-features` (3413 core + bindings), `cargo clippy --workspace --all-targets --all-features -D warnings`, Node build + 498 tests, and pytest all green.
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@@ -1,7 +1,5 @@
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//! Simple Moving Average.
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use std::collections::VecDeque;
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use crate::error::{Error, Result};
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use crate::traits::Indicator;
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@@ -33,7 +31,14 @@ use crate::traits::Indicator;
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#[derive(Debug, Clone)]
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pub struct Sma {
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period: usize,
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window: VecDeque<f64>,
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/// Fixed-capacity ring buffer of the last `period` finite inputs. A flat
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/// `Box<[f64]>` with a manual write cursor beats `VecDeque` on this hot path:
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/// sequential storage, branchless wraparound, no per-call bookkeeping.
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buf: Box<[f64]>,
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/// Index of the next slot to write — also the oldest element once full.
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head: usize,
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/// Number of slots filled, saturating at `period`.
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count: usize,
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sum: f64,
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/// Number of finite updates since the running `sum` was last reseeded from
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/// the live window. Caps accumulated floating-point drift on long streams.
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@@ -60,7 +65,9 @@ impl Sma {
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}
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Ok(Self {
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period,
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window: VecDeque::with_capacity(period),
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buf: vec![0.0; period].into_boxed_slice(),
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head: 0,
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count: 0,
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sum: 0.0,
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updates_since_recompute: 0,
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})
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@@ -73,7 +80,7 @@ impl Sma {
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/// Current value if available.
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pub fn value(&self) -> Option<f64> {
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if self.window.len() == self.period {
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if self.count == self.period {
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Some(self.sum / self.period as f64)
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} else {
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None
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@@ -89,25 +96,40 @@ impl Indicator for Sma {
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if !input.is_finite() {
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return self.value();
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}
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if self.window.len() == self.period {
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// Slide: drop the oldest, then add the new. Each step is a single
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// f64 add/subtract — O(1) but introduces ~1 ULP of rounding noise.
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// The periodic reseed below caps the accumulated drift.
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let old = self.window.pop_front().expect("window non-empty");
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self.sum -= old;
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if self.count == self.period {
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// Window full: overwrite the oldest slot (at `head`). Each step is a
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// single f64 add/subtract — O(1) but introduces ~1 ULP of rounding
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// noise. The periodic reseed below caps the accumulated drift.
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self.sum -= self.buf[self.head];
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self.buf[self.head] = input;
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self.sum += input;
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} else {
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self.buf[self.head] = input;
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self.sum += input;
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self.count += 1;
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}
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// Branchless-ish wraparound, cheaper than `% period`.
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self.head += 1;
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if self.head == self.period {
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self.head = 0;
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}
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self.window.push_back(input);
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self.sum += input;
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self.updates_since_recompute += 1;
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if self.updates_since_recompute >= RECOMPUTE_EVERY * self.period {
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self.sum = self.window.iter().copied().sum();
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// Reseed in chronological order (oldest at `head`) so the running sum
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// tracks a fresh from-scratch mean to the bit on stable inputs.
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self.sum = self.buf[self.head..]
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.iter()
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.chain(&self.buf[..self.head])
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.copied()
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.sum();
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self.updates_since_recompute = 0;
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}
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self.value()
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}
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fn reset(&mut self) {
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self.window.clear();
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self.head = 0;
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self.count = 0;
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self.sum = 0.0;
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self.updates_since_recompute = 0;
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}
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@@ -117,7 +139,7 @@ impl Indicator for Sma {
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}
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fn is_ready(&self) -> bool {
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self.window.len() == self.period
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self.count == self.period
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}
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fn name(&self) -> &'static str {
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@@ -130,6 +152,7 @@ mod tests {
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use super::*;
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use crate::traits::BatchExt;
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use approx::assert_relative_eq;
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use std::collections::VecDeque;
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#[test]
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fn new_rejects_zero_period() {
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