kingchenc
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Adds an R binding (`bindings/r`) over the C ABI hub — the third language stecker after C# and Go, reaching the hub through R's native `.Call` interface (not extendr). ## What's here - **`bindings/r`** — an R package exposing all 514 indicators as constructors that return a `wickra_indicator` object with generic `update`/`batch`/`reset` methods. The C glue (`src/wickra.c`) and R wrappers (`R/indicators.R`) are generated from `bindings/c/include/wickra.h` (same archetype taxonomy as the C#/Go generators: scalar/batch, multi-output, bars, profile, profile-values, array-input). The opaque handle is an R external pointer freed by a registered finalizer; multi-output returns a named vector (`NA` at warmup), bars a matrix, profiles a list. - **`examples/r`** — the full example suite mirroring C/C#/Go: streaming, backtest, multi_timeframe, parallel_assets (`mclapply`), three strategies, and `fetch_btcusdt`/`live_binance`. - **CI** — an `r` job builds the C ABI library, installs the package, runs the `testthat` suite and the offline examples on Linux, macOS and Windows (`R CMD check` is clean: 0 warnings, 0 notes). - **Docs** — R 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 package compiles a thin `.Call` glue layer against the prebuilt C ABI library (header via `WICKRA_INCLUDE_DIR`, library via `WICKRA_LIB_DIR`). On Windows the package's own `wickra.dll` would collide with the C ABI's `wickra.dll`, so `configure.win` stages a renamed copy (`wickra_abi.dll`) and builds an import library referencing it; `install.libs.R` bundles the DLL and `.onLoad` puts it on the load path. On Linux/macOS the rpath locates the shared library. No `release.yml` change — R is distributed via r-universe / source install (gated). No Rust crate or `Cargo.toml` change — the R package is standalone and additive.
Wickra — Node.js
Streaming-first technical indicators for Node.js. npm install wickra —
prebuilt native binary, no system dependencies.
Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R and any other C-capable language. Every indicator is an O(1) streaming state machine, so live trading bots and historical backtests share the exact same implementation. This package is the Node.js binding (napi-rs); it exposes 200+ streaming-first indicators across sixteen families.
Install
npm install wickra
The native addon ships as a prebuilt binary per platform (Linux, macOS, Windows — x64 and arm64), selected automatically through optional dependencies. There is nothing to compile.
Quick start
const wickra = require('wickra');
// Batch: run an indicator over a whole array.
const prices = Array.from({ length: 1000 }, (_, i) => 100 + i * 0.1);
const values = new wickra.RSI(14).batch(prices); // null during warmup
// Streaming: the same indicator, fed tick by tick in O(1).
const rsi = new wickra.RSI(14);
for (const price of liveFeed) {
const value = rsi.update(price); // no recomputation over history
if (value !== null && value > 70) {
console.log('overbought');
}
}
batch(prices) and feeding the same prices through update() produce
identical values — the equivalence is enforced by the test suite.
Documentation
The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:
- Repository & full indicator list: https://github.com/wickra-lib/wickra
- Docs (quickstarts, cookbook, TA-Lib migration): https://docs.wickra.org
- Runnable examples:
examples/node/
Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against —
all exposing the same indicators from the shared, unsafe-forbidden Rust core.
Disclaimer
Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.
License
Licensed under either of Apache-2.0 or MIT at your option.