kingchenc
677ea37402
Stacked on #315 (the native Binance REST fetcher). Retarget to `main` once #315 merges. Migrates the runnable examples off third-party data-I/O packages onto Wickra's native data layer (`CandleReader`, `Resampler`, `BinanceFeed`, `fetch_*klines`). ## Third-party packages removed (the zero-dep selling point) - **Node**: `ws` (live feed → BinanceFeed) — dropped from package.json + lockfile - **Go**: `github.com/coder/websocket` — dropped from go.mod / go.sum (`go mod tidy`) - **Java**: `jackson-databind` (live feed + REST fetch) — dropped from pom.xml - **R**: `jsonlite` + `websocket` + `later` — dropped from the README notes Each language's CSV loading now goes through `CandleReader`, manual resampling through `Resampler`, the live feed through `BinanceFeed`, and (Java/R) the REST download through the native fetcher. ## Verification Ran the offline examples per language against the bundled data — backtest and multi_timeframe produce identical output across Python / Node / Go / Java / R (e.g. ATR(14) last 345.1010; 1h→5m resamples to 240 bars, →15m to 80 bars). C# / C / WASM (stdlib-only, no third-party deps to remove) follow in this branch. Note: the streaming `strategy_*` examples have pre-existing candle-indicator runtime bugs (CI only syntax-smokes them); the CSV migration preserves their shape and leaves those bugs for a separate fix.
49 lines
1.4 KiB
Go
49 lines
1.4 KiB
Go
// Resample a 1-minute series into higher timeframes and run an indicator per timeframe.
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package main
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import (
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"fmt"
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wickra "github.com/wickra-lib/wickra/bindings/go"
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"github.com/wickra-lib/wickra/examples/go/internal/market"
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)
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func main() {
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oneMinute := market.SyntheticCandlesStep(1200, 0, 60_000)
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fmt.Println("EMA(20) of close across timeframes (resampled from 1-minute bars):")
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for _, factor := range []int{1, 5, 15} {
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bars := resample(oneMinute, factor)
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ema, _ := wickra.NewEma(20)
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var last float64
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for _, b := range bars {
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last = ema.Update(b.Close)
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}
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ema.Close()
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fmt.Printf(" %2dm: %5d bars EMA(20) last = %.4f\n", factor, len(bars), last)
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}
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}
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func resample(source []market.Bar, factor int) []market.Bar {
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if factor <= 1 {
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return source
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}
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// Native Resampler: bucket by an absolute timeframe (the synthetic bars step
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// 60_000 ms, so factor minutes == factor*60_000 ms). No hand-written bucketing.
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r, _ := wickra.NewResampler(int64(factor) * 60_000)
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defer r.Close()
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var out []market.Bar
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emit := func(c wickra.Candle) {
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out = append(out, market.Bar{Open: c.Open, High: c.High, Low: c.Low, Close: c.Close, Volume: c.Volume, Timestamp: c.Timestamp})
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}
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for _, b := range source {
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if c, ok := r.Update(b.Open, b.High, b.Low, b.Close, b.Volume, b.Timestamp); ok {
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emit(c)
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}
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}
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if c, ok := r.Flush(); ok {
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emit(c)
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}
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return out
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}
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