Files
wickra/bindings/node
kingchenc 8a103ef920 feat(data-layer): TickAggregator (tick-to-candle) in all 10 languages (#309)
* feat(data-layer): TickAggregator in Node, WASM, Python + C ABI hub

First data-layer feature (F2): roll trade ticks up into fixed-timeframe OHLCV
candles, exposed natively and over the C ABI.

- wickra-data wired as a binding dependency (workspace dep; its wickra-core dep
  is default-features=false so it never forces rayon into the rayon-free WASM
  build — native bindings re-enable parallel through their own dependency).
- Node `TickAggregator(bucket, gapFill?)` -> `push(price, size, ts): Candle[]`;
  WASM the same (array of objects); Python `push(...) -> list[tuple]`.
- C ABI: `WickraCandle` struct + `wickra_tick_aggregator_new/push/free` (push
  writes candles into a caller buffer and returns the count), generated via the
  capi generator's new DATA_LAYER section; cbindgen now parses wickra-data so
  `TickAggregator` is a forward-declared opaque; header vendored to bindings/go.

Verified bit-identical across Node/WASM/Python/C/C++ (o=100 h=101 l=100 c=101
v=3 ts=0 for the shared 3-tick probe). WIP: Go/C#/Java/R generated bindings and
the cross-language golden are still pending.

* feat(data-layer): TickAggregator in Go, C#, Java, R (lossless push/drain)

Complete F2 across all 10 languages: the C-ABI tick aggregator now uses a
two-step push/drain so gap-fill candles are never lost, and the four generated
bindings expose it idiomatically.

- C ABI redesigned: opaque TickAggregator handle (inner aggregator + pending
  buffer); push consumes a tick and returns the closed-candle count, drain copies
  them into a count-sized caller buffer.
- Go: NewTickAggregator + Push(price,size,ts) []Candle; C#: TickAggregator +
  Candle[] Push(...); Java: TickAggregator + Candle[] push(...); R: TickAggregator
  constructor + push() S3 generic returning an (n x 6) numeric matrix.
- Candle output record generated per language from WickraCandle.

Verified bit-identical to the native bindings (o=100 h=101 l=100 c=101 v=3 ts=0)
in Go, C#, Java, and R at runtime; R passes R CMD check (pre-existing doc
warnings only). WIP: cross-language data-layer golden + CHANGELOG still pending.

* test(data-layer): cross-language golden for the tick aggregator + CHANGELOG

gen_golden emits a deterministic tick stream (testdata/golden/data_ticks.csv) and
the reference candle streams with and without gap filling (data_candles.csv,
data_candles_gap.csv). Every binding replays the shared ticks through its
TickAggregator and checks the candles bit-for-bit (fp tolerance) against the Rust
reference:

- Node / WASM / Python / Go / C# / Java / R: a dedicated parity test each.
- C / C++: data_layer_test.c (compiled as both, run as ctest).

The gap-fill fixture closes several candles from a single push, exercising the
lossless push/drain path. Records the feature under CHANGELOG [Unreleased].

* fix(examples): rename the CSV-loader candle to WickraBar

The example CSV helper (wickra_csv.h) defined its own struct WickraCandle, which
now collides with the public C ABI WickraCandle (the tick aggregator output) in
any example that includes both headers (backtest, multi_timeframe, the strategy
examples). The public type owns the name; rename the example loader's bar to
WickraBar. The generated golden_test.c is untouched (its only match was the
unrelated WickraCandleVolumeOutput).
2026-06-15 21:24:33 +02:00
..
2026-06-15 06:02:05 +02:00

Wickra — Node.js

CI codecov npm License: MIT OR Apache-2.0

Streaming-first technical indicators for Node.js. npm install wickra — prebuilt native binary, no system dependencies.

Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js and WASM, plus a C ABI for C, C++, C#, Go, Java, R and any other C-capable language. Every indicator is an O(1) streaming state machine, so live trading bots and historical backtests share the exact same implementation. This package is the Node.js binding (napi-rs); it exposes all 514 streaming-first indicators across twenty-four families.

Install

npm install wickra

The native addon ships as a prebuilt binary per platform (Linux, macOS, Windows — x64 and arm64), selected automatically through optional dependencies. There is nothing to compile.

Quick start

const wickra = require('wickra');

// Batch: run an indicator over a whole array.
const prices = Array.from({ length: 1000 }, (_, i) => 100 + i * 0.1);
const values = new wickra.RSI(14).batch(prices); // null during warmup

// Streaming: the same indicator, fed tick by tick in O(1).
const rsi = new wickra.RSI(14);
for (const price of liveFeed) {
  const value = rsi.update(price); // no recomputation over history
  if (value !== null && value > 70) {
    console.log('overbought');
  }
}

batch(prices) and feeding the same prices through update() produce identical values — the equivalence is enforced by the test suite.

Benchmark

benchmarks/throughput.js reports streaming and batch updates-per-second for SMA, ATR and MACD. It measures this binding's FFI overhead, not a cross-library ratio (the same Rust core runs under every binding) — see the repository BENCHMARKS.md §3.

npx napi build --platform --release
node benchmarks/throughput.js

Documentation

The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:

Wickra ships native bindings for Python, Node.js, WASM and Rust, plus a C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against — all exposing the same indicators from the shared, unsafe-forbidden Rust core.

Security

Found a security issue? Please don't open a public issue. Report it privately via the affected repository's Security tab ("Report a vulnerability") or email support@wickra.org with a subject line starting [wickra security]. Full policy: https://github.com/wickra-lib/wickra/blob/main/SECURITY.md.

Disclaimer

Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.

License

Licensed under either of Apache-2.0 or MIT at your option.