Quickstart: R

Verified against the Rust reference. Every one of Wickra's 514 indicators is replayed through all 10 languages and checked bit-for-bit against the Rust core's golden fixtures in CI — the math here is provably identical to every other binding (how).

A five-minute tour of the Wickra R binding — a .Call shim on the C ABI hub. By the end you will have streamed an RSI, run a batch SMA, and read a multi-output MACD, all from idiomatic R.

Install

The package compiles a thin .Call glue layer against the prebuilt Wickra C ABI library, so a C toolchain (Rtools on Windows) is required, plus the C ABI header and library. Build the library from the workspace, then install the package pointing at it:

bash

cargo build -p wickra-c --release
WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" \
WICKRA_LIB_DIR="$PWD/target/release" \
R CMD INSTALL bindings/r

On Windows the C ABI DLL is bundled into the package and put on the load path automatically; on Linux and macOS the library path is baked in via rpath.

The object shape

Every indicator is a constructor returning a wickra_indicator object over an opaque native handle, with the same operations as the C ABI underneath:

library(wickra)

sma <- Sma(14)             # stops with an error on invalid params
w <- warmup_period(sma)    # updates until ready: 14
v <- update(sma, 42)       # NA while warming up
ready <- is_ready(sma)     # FALSE until warmed up
reset(sma)                 # back to a fresh state
# the native handle is freed automatically when `sma` is garbage-collected

The alt-chart bar builders (RenkoBars(), KagiBars(), …) have no warmup_period() / is_ready() — a candle can complete 0..n bars, so they have no warmup.

update() never revisits the history behind the tick. Handles are released by a registered finalizer, so there is nothing to free by hand.

Streaming and batch side by side

library(wickra)

# 1. Streaming: feed Wilder's textbook example into RSI(14).
rsi <- Rsi(14)
prices <- c(
  44.34, 44.09, 44.15, 43.61, 44.33, 44.83, 45.10, 45.42,
  45.84, 46.08, 45.89, 46.03, 45.61, 46.28, 46.28, 46.00
)
for (i in seq_along(prices)) {
  r <- update(rsi, prices[i])
  if (!is.na(r)) {           # NA during the 15-bar warmup
    cat(sprintf("tick %2d  rsi=%.4f\n", i, r))
  }
}

# 2. Batch: one SMA(3) call over five prices writes NA at warmup.
batch(Sma(3), c(1, 2, 3, 4, 5))
# -> NA NA 2 3 4

The first RSI value lands on tick 15. Batch output is bit-for-bit identical to feeding the same inputs through update() one at a time.

The opt-in fast batch

batch_fast() takes the same arguments as batch() and returns the same shape:

fast <- batch_fast(Ema(20), prices)
macd <- batch_fast(MacdIndicator(12, 26, 9), prices)  # n x 3 matrix

The fast batch runs a SIMD kernel where the indicator has one (moving averages, RSI, ATR, MACD and MACDFIX, Bollinger Bands, the Chaikin oscillator, skewness, Pearson correlation and more). The kernel reassociates the arithmetic, so each value agrees with the exact batch to within a few units in the last place rather than bit for bit; NaN placement and length are identical, and the result is the same on every platform. Where an indicator has no kernel, the fast batch is the exact batch. Keep the exact batch wherever you compare against streaming bit for bit; reach for the fast one when throughput is the point. See Streaming vs Batch.

Multi-output indicators

Indicators with several outputs (MACD, Bollinger, ADX, …) return a named numeric vector — NA while warming up, real values once one is ready:

macd <- MacdIndicator(12, 26, 9)
for (price in feed) {
  m <- update(macd, price)
  if (!is.na(m[["macd"]])) {
    cat(sprintf("macd=%.4f signal=%.4f hist=%.4f\n",
                m[["macd"]], m[["signal"]], m[["histogram"]]))
  }
}

Candle-input indicators (ATR, ADX, OBV, …) take the OHLCV fields plus a timestamp, e.g. update(atr, open, high, low, close, volume, timestamp). Bar builders return a matrix of completed bars; profile indicators return a list.

A deeper example

examples/r/backtest.R runs a basket of indicators over an OHLCV series; the examples/r/ directory also has a multi-indicator streaming demo, multi-timeframe resampling, an mclapply fan-out, three strategy examples, and Binance fetch/live examples. Build and install once, then run any of them:

bash

cargo build -p wickra-c --release
WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" WICKRA_LIB_DIR="$PWD/target/release" \
  R CMD INSTALL bindings/r
cd examples/r && Rscript streaming.R

Quickstart: R ​

Install ​

The object shape ​

Streaming and batch side by side ​

The opt-in fast batch ​

Multi-output indicators ​

A deeper example ​

See also ​