* test: golden-pin the four de-duplicated indicators across all C-ABI bindings Extend gen_golden to emit reference fixtures for AdOscillator (ADOSC), IntradayIntensity, AwesomeOscillatorHistogram and AverageDrawdown, and replay them through the Go / C# / Java / R golden harnesses so their corrected definitions stay bit-identical to the Rust core in every binding. Go suite verified locally (gcc 13 + cgo): all 9 golden tests pass; C#/Java/R use the same fixtures and harness pattern (CI-verified). First step of extending the golden coverage beyond the seven archetype representatives. * test: golden-pin the scalar-output tranche (308 indicators) against Rust Extend gen_golden with a generated emit_scalar that writes reference fixtures for every single-f64-output indicator (scalar / candle / pairwise input) using valid constructor params, and add a manifest-driven generic Python golden replay that reconstructs each by its native name and checks it bit-for-bit against the Rust output. 308 indicators now value-tied to the Rust core in Python (pytest: 308/308). Takes golden coverage from the 7 archetype representatives to 308+ of the catalogue. 22 scalar indicators with non-default constructor constraints are skipped by gen_golden for now (logged), as are non-f64-output ones; multi-output, exotic inputs and the per-indicator arg arities of the C-ABI/Node replays follow. Generated + verified locally with the full toolchain. * test: golden-pin the multi-output tranche (70 indicators) in Python Add a generated emit_multi to gen_golden (per-indicator Output-field access, one CSV column per field) and a manifest-driven generic Python replay that checks every field of each multi-output indicator against the Rust reference. 70 multi-output indicators now value-tied to Rust in Python; combined with the scalar tranche, 378 indicators are golden-pinned. 8 multi with non-default param constraints and 5 with non-f64 Output fields (Option/Vec/i64) are deferred. pytest green. * test(golden): add 30 constraint-tuned indicators to scalar/multi golden suite Emit golden fixtures for 22 scalar-output and 8 multi-output indicators whose constructors need non-default parameters (Alma, Jma, Psar, T3, Mama, DoubleBollinger, ZigZag, ...). All 408 fixtures replay bit-for-bit through the Python binding. * test(golden): cover 36 missed scalar/multi indicators Add 26 single-output (LinearRegression family, HT cycle, Candle volatility estimators, DrawdownDuration) and 10 multi-output (BollingerBands, MACD/MACDEXT/MACDFIX, Camarilla, VWAP bands, ...) indicators to the golden suite. 444 fixtures replay bit-for-bit through the Python binding. * test(golden): cover 50 exotic-input indicators Add deterministic synthetic feeders for the DerivativesTick (17), CrossSection (15), Trade (8), TradeQuote (3) and OrderBook (7) families, derived from the shared OHLCV input series in both gen_golden and a new Python replay harness (test_golden_exotic). All 494 fixtures replay bit-for-bit through the Python binding. * test(golden): complete 514-indicator golden coverage Add the final tranches: 3 mixed multi-output indicators (Ichimoku, WilliamsFractals, LeadLagCrossCorrelation), 6 histogram profiles (time/volume seasonality + TPO/volume price profiles), 10 alt-chart bar builders and the footprint. Every one of the 514 distinct indicators now has a Rust-generated g_<Canonical>.csv fixture and a generic Python replay (scalar/multi/exotic/profile/bars), all passing bit-for-bit. * test(golden): add generic Node replay for all 514 indicators A manifest-driven node:test harness reconstructs every indicator by its native class, feeds the same synthetic stream derived from the shared golden input, and checks output bit-for-bit against the Rust reference fixtures (scalar/multi/exotic/profile/bars). node_manifest.json is generated from index.d.ts plus the Python-side manifests. 514/514 pass. * test(golden): add generated Go replay for all 514 indicators golden_all_test.go (generated by gen_golden_test.py) reconstructs every Go indicator, feeds the shared synthetic stream and checks output bit-for-bit against the Rust reference fixtures. A reflection-based comparator flattens multi-output structs, profiles and bar slices so one path covers all archetypes. This is the first C-ABI binding verified across the full catalogue. 514/514 pass. * test(golden): add generated C# replay for all 514 indicators GoldenAllTests.g.cs (generated by gen_golden_test.py) reconstructs every C# indicator, feeds the shared synthetic stream and checks output bit-for-bit against the Rust reference fixtures via a reflection-based flatten covering scalar/multi/profile/bar archetypes. 514/514 pass. Also add the '#nullable enable' directive the compiler requires to the generated Indicators.g.cs, clearing the four CS8669 warnings on the nullable double[] profile return types. * fix(java): marshal C ABI bool params correctly; add 514 golden replay The Java FFM binding marshalled the cross-section state flags (newHigh, newLow, aboveMa, onBuySignal) as JAVA_DOUBLE arrays, but the C ABI takes them as const bool* (one byte each), so the native side read the low byte of each 8-byte double and saw every flag as false. Add WickraNative. boolSegment and use it across the 15 cross-section indicators. Also pass the MacdExt MaType arguments as byte to match the uint8_t downcall descriptor (was int, throwing WrongMethodTypeException). Add GoldenAllTest.java (generated by gen_golden_test.py): a reflection runner replaying all 514 indicators against the Rust reference fixtures. The bugs above were found by this test; 514/514 now pass. * fix(r): marshal C ABI bool flags correctly; add 514 golden replay The R wrapper passed the cross-section state flags as (bool *)REAL(x), reinterpreting the 8-byte doubles as 1-byte bools so the native side read every flag as false. Add wk_bool_vec to convert each flag vector into a real C bool buffer and use it for all 15 cross-section update wrappers. Add test-golden-all.R + generated golden_specs.R: a reflective runner replaying all 514 indicators against the Rust reference fixtures. The bug above was found by this test; verified 514/514 pass locally. * test(golden): add WASM replay for all 514 indicators A manifest-driven node:test harness loads the nodejs-target wasm-pack build, reconstructs every indicator by its JS class, feeds the shared synthetic stream and checks output bit-for-bit against the Rust reference fixtures. wasm_manifest.json is generated from the wasm .d.ts plus the shared manifests; a recursive flattener covers scalar, multi (Reflect objects), profile and bar shapes. 514/514 pass locally (wasm-pack build --target nodejs, then node --test). * test(golden): add C and C++ replay for all 514 indicators golden_test.c (generated by gen_golden_test.py) drives every indicator through the C ABI (wickra.h) and checks output bit-for-bit against the Rust reference fixtures. golden_test.cpp #includes the same source so the identical runner is compiled and run under both gcc (C) and g++ (C++) via the CMake targets golden_test / golden_test_cpp — proving the extern "C" header is consumable from each language. Both 514/514 (verified via ctest). * test(golden): gofmt the generated Go golden replay * test(golden): make the Node fixture reader CRLF-safe and pin fixtures to LF
Wickra — Go
Streaming-first technical indicators for Go, over the Wickra C ABI hub via cgo.
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 Go binding; it consumes the C ABI hub through cgo and exposes all 514 streaming-first indicators as idiomatic types.
Install
Use the published wickra-go module, which bundles the prebuilt C ABI
library for every platform, so go get + go build works with no extra steps
(a C compiler is still required, as the binding uses cgo):
go get github.com/wickra-lib/wickra-go
import wickra "github.com/wickra-lib/wickra-go"
wickra-go is generated from this directory by the release pipeline: it mirrors
the Go sources, the vendored C ABI header (include/wickra.h) and the prebuilt
libraries under lib/<goos>_<goarch>/. On Linux/macOS the library path is baked
in via rpath; on Windows the DLL must be discoverable at run time (next to the
executable or on PATH).
Building from this repository (contributors)
This bindings/go directory is the development source. To build it directly,
compile the C ABI and stage the library into the per-platform directory cgo
links against:
cargo build -p wickra-c --release
mkdir -p bindings/go/lib/linux_amd64 # match your GOOS_GOARCH
cp target/release/libwickra.so bindings/go/lib/linux_amd64/ # Linux
cp target/release/libwickra.dylib bindings/go/lib/darwin_arm64/ # macOS (arm64)
cp target/release/wickra.dll bindings/go/lib/windows_amd64/ # Windows
Quick start
package main
import (
"fmt"
wickra "github.com/wickra-lib/wickra/bindings/go"
)
func main() {
// Batch: run an indicator over a whole series (NaN at warmup positions).
prices := make([]float64, 1000)
for i := range prices {
prices[i] = 100.0 + float64(i)*0.1
}
sma, _ := wickra.NewSma(20)
defer sma.Close()
values := sma.Batch(prices)
// Streaming: the same indicator, fed tick by tick in O(1).
rsi, _ := wickra.NewRsi(14)
defer rsi.Close()
for _, price := range prices {
value := rsi.Update(price) // NaN during warmup, no recomputation
if value > 70 {
fmt.Println("overbought")
}
}
_ = values
}
Batch(prices) and feeding the same prices through Update() produce identical
values — the equivalence is enforced by the test suite. Multi-output indicators
(MACD, Bollinger, ADX, …) return (Output, bool), with false while warming up.
Every indicator owns a native handle freed by Close(); a finalizer is wired as
a backstop, but call Close() (e.g. with defer) to release memory promptly.
Benchmark
benchmarks/throughput.go 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.
cd benchmarks && go run .
Documentation
The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:
- Repository & full indicator list: https://github.com/wickra-lib/wickra
- Docs (quickstarts, cookbook, TA-Lib migration): https://docs.wickra.org
- Runnable examples:
examples/go/
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.