Add the Go binding over the C ABI hub (#228)
Adds a Go binding (`bindings/go`) over the C ABI hub — the second language stecker after C#. ## What's here - **`bindings/go`** — a cgo binding exposing all 514 indicators as idiomatic Go types with `New<Indicator>` constructors and `Update`/`Batch`/`Reset`/`Close` methods. The wrappers in `indicators_gen.go` are generated from `bindings/c/include/wickra.h` (same archetype taxonomy as the C# generator: scalar/batch, multi-output, bars, profile, profile-values, array-input). Opaque handles are freed by `Close()` with a `runtime.SetFinalizer` backstop; pointer arguments are caller-owned, panics never cross the boundary. - **`examples/go`** — the full example suite mirroring C/C#: streaming, backtest, multi_timeframe, parallel_assets (goroutine fan-out), three strategies, and `fetch_btcusdt`/`live_binance`. - **CI** — a `go` job builds the C ABI library, stages it, and runs `gofmt`/`go vet`/`go test` plus the offline examples on Linux, macOS and Windows. - **Docs** — Go added to the README languages table, project layout, building/testing, CONTRIBUTING binding table + regenerate note, ARCHITECTURE, examples index, issue/PR templates, the About-description template, and the other binding READMEs. ## Linking / distribution The binding links the prebuilt C ABI library via cgo (`libwickra.so`/`.dylib`/`wickra.dll` staged under `bindings/go/lib`, gitignored). The native libraries are already shipped per target triple by the existing `c-abi-build` release job; distribution is via the subdirectory module tag `bindings/go/vX.Y.Z` (gated), so `release.yml` needs no new publish job. No Rust crate or `Cargo.toml` change — the Go module is standalone and additive. Not for merge yet (gated, per request).
This commit is contained in:
kingchenc
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// Package market provides deterministic synthetic market data, a small OHLCV
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// CSV loader, and an equity-curve summary shared by the offline Go examples so
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// they run without network access. It mirrors the helpers used by the Python,
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// C, and C# example suites.
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package market
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import (
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"bufio"
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"fmt"
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"math"
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"os"
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"strconv"
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"strings"
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)
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// Bar is one OHLCV bar with a millisecond timestamp.
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type Bar struct {
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Open float64
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High float64
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Low float64
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Close float64
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Volume float64
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Timestamp int64
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}
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// SyntheticPrices returns a reproducible price path (trend + two cycles), with
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// no randomness, starting at 100.
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func SyntheticPrices(count int) []float64 {
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return SyntheticPricesFrom(count, 100.0)
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}
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// SyntheticPricesFrom is SyntheticPrices with an explicit starting level.
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func SyntheticPricesFrom(count int, start float64) []float64 {
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prices := make([]float64, count)
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for i := range prices {
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fi := float64(i)
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prices[i] = start + 12.0*math.Sin(fi*0.05) + 5.0*math.Sin(fi*0.013) + fi*0.01
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}
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return prices
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}
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// SyntheticCandles returns a reproducible OHLCV series derived from
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// SyntheticPrices, one bar per hour.
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func SyntheticCandles(count int) []Bar {
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return SyntheticCandlesStep(count, 0, 3_600_000)
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}
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// SyntheticCandlesStep is SyntheticCandles with an explicit start timestamp and
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// per-bar step in milliseconds.
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func SyntheticCandlesStep(count int, startTimestamp, stepMs int64) []Bar {
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prices := SyntheticPrices(count + 1)
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bars := make([]Bar, count)
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for i := 0; i < count; i++ {
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fi := float64(i)
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op := prices[i]
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cl := prices[i+1]
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high := math.Max(op, cl) + 0.5 + math.Abs(math.Sin(fi*0.7))
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low := math.Min(op, cl) - 0.5 - math.Abs(math.Cos(fi*0.7))
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volume := 1000.0 + 500.0*(1.0+math.Sin(fi*0.1))
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bars[i] = Bar{op, high, low, cl, volume, startTimestamp + int64(i)*stepMs}
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}
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return bars
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}
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// LoadOhlcvCsv loads an OHLCV CSV. It accepts rows of
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// timestamp,open,high,low,close,volume or open,high,low,close,volume; a
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// non-numeric first row is treated as a header and skipped.
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func LoadOhlcvCsv(path string) ([]Bar, error) {
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file, err := os.Open(path)
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if err != nil {
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return nil, err
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}
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defer file.Close()
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var bars []Bar
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scanner := bufio.NewScanner(file)
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for scanner.Scan() {
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line := strings.TrimSpace(scanner.Text())
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if line == "" {
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continue
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}
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cols := strings.Split(line, ",")
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if _, err := strconv.ParseFloat(cols[0], 64); err != nil {
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continue // header row
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}
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f := func(i int) float64 {
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v, _ := strconv.ParseFloat(strings.TrimSpace(cols[i]), 64)
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return v
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}
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if len(cols) >= 6 {
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ts, _ := strconv.ParseInt(strings.TrimSpace(cols[0]), 10, 64)
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bars = append(bars, Bar{f(1), f(2), f(3), f(4), f(5), ts})
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} else {
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bars = append(bars, Bar{f(0), f(1), f(2), f(3), f(4), int64(len(bars))})
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}
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}
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return bars, scanner.Err()
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}
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// EquityResult holds summary statistics for a long-only equity curve.
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type EquityResult struct {
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TotalReturnPct float64
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Sharpe float64
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MaxDrawdownPct float64
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Trades int
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FinalEquity float64
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}
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// Summarize turns a stream of per-bar fractional returns (0.01 == +1%) into a
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// PnL / Sharpe / max-drawdown summary, annualised by periodsPerYear.
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func Summarize(periodReturns []float64, trades int, periodsPerYear float64) EquityResult {
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equity, peak, maxDrawdown := 1.0, 1.0, 0.0
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for _, r := range periodReturns {
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equity *= 1.0 + r
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peak = math.Max(peak, equity)
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if peak > 0 {
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maxDrawdown = math.Max(maxDrawdown, (peak-equity)/peak)
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}
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}
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mean := 0.0
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if len(periodReturns) > 0 {
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var sum float64
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for _, r := range periodReturns {
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sum += r
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}
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mean = sum / float64(len(periodReturns))
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}
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variance := 0.0
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if len(periodReturns) > 1 {
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var ss float64
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for _, r := range periodReturns {
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ss += (r - mean) * (r - mean)
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}
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variance = ss / float64(len(periodReturns)-1)
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}
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stdDev := math.Sqrt(variance)
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sharpe := 0.0
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if stdDev > 1e-12 {
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sharpe = mean / stdDev * math.Sqrt(periodsPerYear)
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}
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return EquityResult{
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TotalReturnPct: (equity - 1.0) * 100.0,
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Sharpe: sharpe,
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MaxDrawdownPct: maxDrawdown * 100.0,
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Trades: trades,
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FinalEquity: equity,
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}
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}
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// Print writes a one-line summary of an equity result.
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func Print(name string, r EquityResult) {
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fmt.Printf("%-26s return=%8.2f%% sharpe=%6.2f maxDD=%6.2f%% trades=%d\n",
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name, r.TotalReturnPct, r.Sharpe, r.MaxDrawdownPct, r.Trades)
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}
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