feat(data): expose CandleReader (CSV) natively in all 10 languages (#311)

Add the data-layer CSV candle reader to every binding so loading OHLCV
candles from a CSV no longer needs a per-language CSV/dataframe dependency.

- C ABI: wickra_candle_reader_new(bytes, len) / _count / _read / _free over
  an opaque CandleReader handle (parse the whole buffer up front, then drain).
- Native: Node/WASM CandleReader.read() -> Candle[], Python read() -> list[tuple].
- C-ABI languages: Go Read() []Candle, C# Candle[] Read(), Java Candle[] read(),
  R read() S3 generic (n x 6 matrix); C / C++ call the C ABI directly.
- Cross-language golden testdata/golden/data_csv*.csv pins the parsed candles
  bit-for-bit across every binding.

Verified locally across Rust (test+clippy+fmt), Node, WASM, Python, C#, Go,
Java, R, and the C/C++ cmake parity suite.

bindings/go/data_layer_test.go

@@ -2,6 +2,7 @@ package wickra
 
 import (
 	"math"
+	"os"
 	"strconv"
 	"testing"
 )
@@ -51,6 +52,35 @@ func TestResamplerGolden(t *testing.T) {
 	}
 }
 
+func TestCandleReaderGolden(t *testing.T) {
+	csv, err := os.ReadFile("../../testdata/golden/data_csv.csv")
+	if err != nil {
+		t.Fatalf("read data_csv.csv: %v", err)
+	}
+	r, err := NewCandleReader(string(csv))
+	if err != nil {
+		t.Fatalf("new: %v", err)
+	}
+	defer r.Close()
+	candles := r.Read()
+	got := make([][6]float64, len(candles))
+	for i, c := range candles {
+		got[i] = [6]float64{c.Open, c.High, c.Low, c.Close, c.Volume, float64(c.Timestamp)}
+	}
+	want := readGolden(t, "data_csv_candles")
+	if len(got) != len(want) {
+		t.Fatalf("candle reader: %d candles vs %d", len(got), len(want))
+	}
+	for i := range got {
+		for j := 0; j < 6; j++ {
+			w := dataParseF(t, want[i][j])
+			if math.Abs(got[i][j]-w) > 1e-9*math.Max(1, math.Abs(w)) {
+				t.Errorf("candle reader row %d col %d: %v vs %v", i, j, got[i][j], w)
+			}
+		}
+	}
+}
+
 func TestTickAggregatorGolden(t *testing.T) {
 	ticks := readGolden(t, "data_ticks")
 	cases := []struct {