Wickra 0.1.0: streaming-first technical indicators

A multi-language technical analysis library: 25 indicators across trend,
momentum, volatility, and volume families, every one a state machine with
O(1) per-tick updates. Batch evaluation is provided by a blanket extension
trait over the streaming primitive, so live trading bots and historical
backtests run the same code path.

What ships in this initial drop:

  crates/wickra-core   - 25 indicators, Indicator/BatchExt/Chain traits,
                          OHLCV types with validation; 171 unit tests,
                          property tests, Wilder/Bollinger textbook tests.
  crates/wickra        - top-level facade + criterion benches for every
                          indicator at 1K/10K/100K series sizes.
  crates/wickra-data   - streaming CSV reader, tick-to-candle aggregator,
                          multi-timeframe resampler, Binance Spot kline
                          WebSocket adapter behind feature live-binance;
                          11 unit + 1 doctest.
  bindings/python      - PyO3 + maturin, NumPy I/O, type stubs (.pyi),
                          56 pytest tests including streaming==batch
                          equivalence, Wilder reference values, lifecycle.
  bindings/node        - napi-rs native module, TypeScript .d.ts
                          auto-generated, 7 node --test cases.
  bindings/wasm        - wasm-bindgen ES module for browser/bundler/Node;
                          interactive HTML demo at examples/index.html.
  examples/            - Python and Rust scripts: backtest, live trading,
                          parallel multi-asset, multi-timeframe, Binance.
  benchmarks/          - cross-library comparison against TA-Lib,
                          pandas-ta, finta, talipp; Wickra wins every
                          category by 11-1030x (batch) and 17x+ streaming.
  .github/workflows/   - CI matrix (Rust + Python + Node + WASM on
                          Linux/macOS/Windows), release pipeline for
                          PyPI wheels and npm.

Indicators (25):
  Trend       SMA EMA WMA DEMA TEMA HMA KAMA
  Momentum    RSI MACD Stochastic CCI ROC WilliamsR ADX MFI TRIX
              AwesomeOscillator Aroon
  Volatility  BollingerBands ATR Keltner Donchian PSAR
  Volume      OBV VWAP (cumulative + rolling)

cargo clippy --workspace --all-targets -D warnings is clean. License: Apache-2.0.

bindings/node/__tests__/smoke.test.js

@@ -0,0 +1,82 @@
+// Smoke tests for the Wickra Node bindings.
+//
+// Run with:
+//   cd bindings/node && npm install && npm run build && npm test
+
+const test = require('node:test');
+const assert = require('node:assert/strict');
+const wickra = require('..');
+
+test('version is non-empty', () => {
+  assert.ok(typeof wickra.version() === 'string');
+  assert.ok(wickra.version().length > 0);
+});
+
+test('SMA batch matches reference values', () => {
+  const sma = new wickra.SMA(3);
+  const out = sma.batch([2, 4, 6, 8, 10]);
+  assert.ok(Number.isNaN(out[0]));
+  assert.ok(Number.isNaN(out[1]));
+  assert.equal(out[2], 4);
+  assert.equal(out[3], 6);
+  assert.equal(out[4], 8);
+});
+
+test('RSI pure uptrend yields 100', () => {
+  const rsi = new wickra.RSI(14);
+  const prices = Array.from({ length: 20 }, (_, i) => i + 1);
+  const out = rsi.batch(prices);
+  for (let i = 14; i < out.length; i++) {
+    assert.equal(out[i], 100);
+  }
+});
+
+test('streaming and batch agree on EMA', () => {
+  const prices = Array.from({ length: 60 }, (_, i) => 100 + Math.sin(i * 0.3) * 5);
+  const batch = new wickra.EMA(14).batch(prices);
+  const ema = new wickra.EMA(14);
+  const streamed = prices.map((p) => {
+    const v = ema.update(p);
+    return v === null || v === undefined ? NaN : v;
+  });
+  for (let i = 0; i < prices.length; i++) {
+    if (Number.isNaN(batch[i])) {
+      assert.ok(Number.isNaN(streamed[i]));
+    } else {
+      assert.ok(Math.abs(batch[i] - streamed[i]) < 1e-9);
+    }
+  }
+});
+
+test('MACD returns macd/signal/histogram object', () => {
+  const macd = new wickra.MACD(12, 26, 9);
+  let value = null;
+  for (let i = 1; i <= 60; i++) {
+    value = macd.update(i);
+  }
+  assert.ok(value);
+  assert.equal(typeof value.macd, 'number');
+  assert.equal(typeof value.signal, 'number');
+  assert.equal(typeof value.histogram, 'number');
+  assert.ok(Math.abs(value.histogram - (value.macd - value.signal)) < 1e-9);
+});
+
+test('ATR batch shape', () => {
+  const high = Array.from({ length: 30 }, () => 11);
+  const low = Array.from({ length: 30 }, () => 9);
+  const close = Array.from({ length: 30 }, () => 10);
+  const out = new wickra.ATR(14).batch(high, low, close);
+  assert.equal(out.length, 30);
+  // Once seeded, ATR is the constant TR of 2.
+  for (let i = 13; i < 30; i++) {
+    assert.ok(Math.abs(out[i] - 2) < 1e-9);
+  }
+});
+
+test('zero period is clamped to a valid window', () => {
+  // Constructors cannot throw from JS (napi-rs 2.16 limitation), so they
+  // clamp pathological values like period=0 to the smallest valid window.
+  const sma = new wickra.SMA(0);
+  assert.equal(sma.warmupPeriod(), 1);
+  assert.equal(sma.update(42), 42);
+});