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/r/tests/testthat/test-data-layer.R

@@ -51,6 +51,24 @@ test_that("tick aggregator matches the golden candles", {
   }
 })
 
+test_that("candle reader matches the golden candles", {
+  gdir <- find_data_golden_dir()
+  skip_if(is.null(gdir), "golden fixtures not bundled with the package")
+
+  read_mat <- function(name) {
+    lines <- readLines(file.path(gdir, paste0(name, ".csv")))[-1]
+    lines <- lines[nzchar(lines)]
+    do.call(rbind, lapply(lines, function(l) as.numeric(strsplit(l, ",")[[1]])))
+  }
+
+  csv <- paste(readLines(file.path(gdir, "data_csv.csv")), collapse = "\n")
+  reader <- CandleReader(csv)
+  got <- unname(read(reader))
+  want <- unname(read_mat("data_csv_candles"))
+  expect_equal(nrow(got), nrow(want))
+  expect_equal(got, want, tolerance = 1e-9)
+})
+
 test_that("resampler matches the golden candles", {
   gdir <- find_data_golden_dir()
   skip_if(is.null(gdir), "golden fixtures not bundled with the package")