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kingchenc de1112ea91 chore(examples): rename live_trading examples to live_binance (#301 )

The examples stream a live Binance feed into the indicators and print signals;
they place no orders, so 'live_trading' overstated them and was inconsistent
with the C/Go/R examples already named live_binance. Rename the Python/Node/WASM
files to live_binance.* and update every reference, run command, header, and the
project-tree listings. Accurate use-case wording ('suitable for live trading
bots') and the risk disclaimers are left unchanged.

2026-06-15 03:41:19 +02:00

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Wickra WASM examples

Browser demos for the wickra-wasm WASM binding. Every demo loads the module the same way (init() then construct indicators) so the patterns transfer one-to-one to your own page.

Build

The WASM module ships as a wasm-pack --target web bundle. Build it once from the repository root:

wasm-pack build bindings/wasm --target web --release --features panic-hook

This drops bindings/wasm/pkg/ with the .wasm binary, the JS loader and TypeScript types. Every demo here imports the loader via ../../bindings/wasm/pkg/wickra_wasm.js.

Serve

ES-module workers and fetch() over CSV both need a real HTTP origin, not file://. Any static server from the repository root works:

# Python:
python -m http.server 8000

# Or Node:
npx http-server -p 8000

Then open the demo you want at http://localhost:8000/examples/wasm/<file>.

Demos

File	What it does
`index.html`	The original showcase: streams a synthetic price series through six indicators and draws a live `<canvas>` chart with `SMA`, `EMA`, `RSI`, `MACD`, `BollingerBands` and `ATR` cards.
`backtest.html`	Backtest: fetches an OHLCV CSV (default the bundled BTCUSDT daily dataset), streams every candle through a basket of eight indicators, prints a summary table. Mirrors `examples/python/backtest.py`.
`live_binance.html`	Browser-native `WebSocket` to Binance kline streams; runs RSI / MACD / Bollinger on the incoming closes and flags BUY/SELL candidates when the three agree. Mirrors `examples/python/live_binance.py`.
`multi_timeframe.html`	Fetches a 1-minute CSV, rolls it up in-page to 5m / 15m / 1h / 4h / 1d buckets and prints RSI / MACD-histogram / ADX per timeframe. Mirrors `examples/python/multi_timeframe.py`.
`parallel_assets.html`	Synthetic `(assets, bars)` panel, serial baseline on the main thread vs. a pool of module Workers each loading its own copy of the WASM module. Mirrors `examples/python/parallel_assets.py`.
`parallel_worker.js`	Module worker used by `parallel_assets.html` (not loaded directly).
`strategy_rsi_mean_reversion.html`	RSI(14) mean-reversion (long < 30, exit > 70), 0.1% fees, summary table. Mirrors `examples/python/strategy_rsi_mean_reversion.py`.
`strategy_macd_adx.html`	MACD(12,26,9) crossover gated by ADX(14) > 20, summary table. Mirrors `examples/python/strategy_macd_adx.py`.
`strategy_bollinger_squeeze.html`	Bollinger-squeeze breakout with a 2×ATR(14) stop, summary table. Mirrors `examples/python/strategy_bollinger_squeeze.py`.

Performance

The in-browser benchmark is parallel_assets.html: it times a serial main-thread baseline against a pool of module Workers and reports the speedup. For raw single-thread throughput numbers see the sibling benchmarks — Rust criterion (crates/wickra/benches/), Python (bindings/python/benchmarks/compare_libraries.py) and Node (bindings/node/benchmarks/throughput.js, npm run bench). The WASM engine is the same Rust core compiled to wasm32, so its relative ordering of indicators tracks those.

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