* 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).
96 lines
3.1 KiB
C
96 lines
3.1 KiB
C
/* Strategy example: RSI mean-reversion on hourly BTCUSDT data (Wickra C ABI).
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*
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* Goes long when RSI(14) crosses below 30 (oversold), exits when RSI crosses
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* above 70 (overbought). Position is binary (full-in / full-out), fees are 0.1%
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* per trade (Binance maker tier), no stop-loss. The C counterpart of
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* `examples/rust/src/bin/strategy_rsi_mean_reversion.rs`.
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*
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* Educational example. NOT a recommended trading strategy — the point is to
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* show how a Wickra streaming indicator wires into a signal -> fill -> PnL ->
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* equity loop. Uses the checked-in `examples/data/btcusdt-1h.csv` dataset.
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*
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* Build (after `cargo build -p wickra-c --release`):
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* cc examples/c/strategy_rsi_mean_reversion.c -I bindings/c/include -L target/release -lwickra -lm -o strat_rsi
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*/
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#define WICKRA_CSV_IMPL
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#define WICKRA_STRATEGY_IMPL
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#include "wickra.h"
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#include "wickra_csv.h"
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#include "wickra_strategy.h"
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#include <math.h>
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#include <stdio.h>
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#include <stdlib.h>
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#ifndef WICKRA_DATA_DIR
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#define WICKRA_DATA_DIR "../data"
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#endif
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#define FEE 0.001
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#define RSI_PERIOD 14
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#define OVERSOLD 30.0
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#define OVERBOUGHT 70.0
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int main(int argc, char **argv) {
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const char *path = (argc > 1) ? argv[1] : WICKRA_DATA_DIR "/btcusdt-1h.csv";
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WickraBar *candles = NULL;
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size_t n = wickra_load_csv(path, &candles);
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if (n < RSI_PERIOD * 4) {
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fprintf(stderr, "dataset too small: %llu\n", (unsigned long long)n);
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free(candles);
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return 1;
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}
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struct Rsi *rsi = wickra_rsi_new(RSI_PERIOD);
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double *trades = (double *)malloc(n * sizeof(*trades));
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double *equity_curve = (double *)malloc(n * sizeof(*equity_curve));
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if (rsi == NULL || trades == NULL || equity_curve == NULL) {
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fprintf(stderr, "allocation failed\n");
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return 1;
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}
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int in_position = 0;
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double entry_price = 0.0;
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size_t n_trades = 0;
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double equity = 1.0;
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for (size_t i = 0; i < n; ++i) {
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double price = candles[i].close;
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double r = wickra_rsi_update(rsi, price);
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/* Mark-to-market so the equity curve moves bar-by-bar between trades. */
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equity_curve[i] = in_position ? equity * (price / entry_price) : equity;
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if (!isfinite(r)) {
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continue;
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}
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if (!in_position && r < OVERSOLD) {
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entry_price = price;
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equity *= 1.0 - FEE;
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in_position = 1;
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} else if (in_position && r > OVERBOUGHT) {
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double trade_ret = price / entry_price - 1.0;
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trades[n_trades++] = trade_ret;
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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in_position = 0;
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}
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}
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/* Close any still-open trade at the last bar so metrics include it. */
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if (in_position) {
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double trade_ret = candles[n - 1].close / entry_price - 1.0;
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trades[n_trades++] = trade_ret;
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equity *= (1.0 + trade_ret) * (1.0 - FEE);
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}
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wickra_print_summary("RSI Mean-Reversion (1h, BTCUSDT)", candles[0].close,
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candles[n - 1].close, n, trades, n_trades, equity,
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equity_curve, n);
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wickra_rsi_free(rsi);
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free(trades);
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free(equity_curve);
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free(candles);
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return 0;
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}
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