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).
This commit is contained in:
kingchenc
2026-06-15 21:24:33 +02:00
committed by GitHub
parent fd9f4c8bc6
commit 8a103ef920
48 changed files with 1368 additions and 29 deletions
+72
View File
@@ -21865,3 +21865,75 @@ impl VolumeWeightedMacdNode {
self.inner.warmup_period() as u32
}
}
// ===== Data layer: tick-to-candle aggregation =====
/// Convert a `wickra-data` error into a JS error.
fn map_data_err(e: wickra_data::Error) -> NapiError {
NapiError::new(Status::InvalidArg, e.to_string())
}
/// One aggregated OHLCV candle emitted by [`TickAggregatorNode`].
#[napi(object)]
pub struct CandleValue {
pub open: f64,
pub high: f64,
pub low: f64,
pub close: f64,
pub volume: f64,
pub timestamp: f64,
}
/// Roll trade ticks up into fixed-timeframe OHLCV candles.
#[napi(js_name = "TickAggregator")]
pub struct TickAggregatorNode {
inner: wickra_data::aggregator::TickAggregator,
}
#[napi]
impl TickAggregatorNode {
/// Construct an aggregator with the given bucket size (in the same unit as
/// the tick timestamps). Pass `gapFill = true` to emit a flat placeholder
/// candle for every skipped bucket.
#[napi(constructor)]
pub fn new(bucket: f64, gap_fill: Option<bool>) -> napi::Result<Self> {
let timeframe =
wickra_data::aggregator::Timeframe::new(bucket as i64).map_err(map_data_err)?;
let mut inner = wickra_data::aggregator::TickAggregator::new(timeframe);
if gap_fill.unwrap_or(false) {
inner = inner.with_gap_fill(true);
}
Ok(Self { inner })
}
/// Push one trade tick; returns every candle that closed as a result (none
/// while the open bar keeps growing, one on a bucket boundary, plus one flat
/// candle per skipped bucket when gap filling is enabled).
#[napi]
pub fn push(
&mut self,
price: f64,
size: f64,
timestamp: f64,
) -> napi::Result<Vec<CandleValue>> {
let tick = wc::Tick::new(price, size, timestamp as i64).map_err(map_err)?;
let candles = self.inner.push(tick).map_err(map_data_err)?;
Ok(candles
.into_iter()
.map(|c| CandleValue {
open: c.open,
high: c.high,
low: c.low,
close: c.close,
volume: c.volume,
timestamp: c.timestamp as f64,
})
.collect())
}
/// Whether gap filling is enabled.
#[napi(js_name = "fillsGaps")]
pub fn fills_gaps(&self) -> bool {
self.inner.fills_gaps()
}
}