Live demo

Every line below is computed by wickra-wasm running inside your browser via WebAssembly — no server, no API call, no install. The same Rust kernel that powers pip install wickra and cargo add wickra is producing every indicator value you see.

What's happening

1. A pseudo-random price walk seeds a synthetic asset (start = 100, small drift + per-tick volatility).
2. The wickra-wasm bundle is fetched once (~80 KB gzipped) and the indicator class you pick is instantiated.
3. Every tick is fed into the indicator's update(price) method — a single O(1) state-machine step. Output is plotted live.
4. Hitting ▶ Stream advances the walk in real time at ~12 fps so you can watch the indicator settle in.

Try this

• Drop the period to 5 and switch to RSI — watch the oscillator pin against the 0 / 100 rails on a sharp move.
• Set period to 80 on HMA vs EMA — the Hull moving average hugs the price noticeably tighter.
• Bump Historical ticks to 5 000 — the initial pass throughput number jumps because the JS-to-WASM boundary is amortised across more updates.

Wiring this into your own project

The chart on this page is ~250 lines of Vue + lightweight-charts; the indicator math is one constructor call and update() per tick.

import init, { RSI } from 'wickra-wasm'

await init()                    // fetches the .wasm bundle
const rsi = new RSI(14)

for (const price of liveFeed) {
  const v = rsi.update(price)   // O(1) — returns null during warmup
  if (v !== null && v > 70) console.log('overbought', v)
}

The same shape works in Node and Python — see the API pages for each binding's idiomatic snippet.