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Adds a Java binding (`bindings/java`) over the C ABI hub — the fourth language stecker after C#, Go and R, reaching the hub through the Java Foreign Function & Memory API (Panama, `java.lang.foreign`, final in Java 22) rather than JNI or jextract. ## What's here - **`bindings/java`** — a Maven module (`org.wickra:wickra`) exposing all 514 indicators as idiomatic `AutoCloseable` classes. The downcall handles (`internal/NativeMethods.java`), the per-indicator wrappers and the output records are generated from `bindings/c/include/wickra.h` (same eight-archetype taxonomy as the C#/Go/R generators: scalar/batch, multi-output, bars, profile, values-profile, array-input). The opaque handle is a `MemorySegment` freed by a registered `java.lang.ref.Cleaner` action; multi-output returns a `record` (`null` at warmup), bars a `record[]`, profiles a record with a trailing `double[]`. The hand-written `WickraNative` resolves the native library (a bundled per-platform copy, or a `target/release` fallback for local development) and validates it against a sentinel symbol. repr(C) struct offsets are computed in the generator so the FFM reads land on the exact bytes. - **`examples/java`** — the full example suite mirroring C/C#/Go/R: streaming, backtest, multi_timeframe, parallel_assets (parallel streams), three strategies, and `FetchBtcusdt`/`LiveBinance`. - **CI** — a `java` job builds the C ABI library, sets up JDK 22 (Temurin, with a CDN-flake retry), runs the archetype test suite and the seven offline examples on Linux, macOS and Windows. - **Release** — a gated `java-publish` job (skipped until the `JAVA_PUBLISH_ENABLED` repository variable is set) stages the native libraries from the `wickra-c-<triple>.tar.gz` assets into the binding's resources and deploys to Maven Central with GPG signing. Independent of the GitHub-release job, like the NuGet job. - **Docs** — Java added to the README languages table, project layout, building/testing and comparison table, CONTRIBUTING, ARCHITECTURE, the examples index, the issue/PR templates, the About-description template, and the other binding READMEs. ## Requirements Java 22+ (the FFM API is final since Java 22). The binding requires `--enable-native-access=ALL-UNNAMED` at runtime; the test and example runners pass it automatically. No Rust crate or `Cargo.toml` change — the Java binding is standalone and additive. The generated `*.java` are committed (like the node `index.js`/`index.d.ts`); the generator stays private.
86 lines
3.6 KiB
Markdown
86 lines
3.6 KiB
Markdown
# Wickra — R
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[](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
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[](https://codecov.io/gh/wickra-lib/wickra)
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[](https://github.com/wickra-lib/wickra#license)
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**Streaming-first technical indicators for R, over the Wickra C ABI hub via `.Call`.**
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Wickra is a multi-language technical-analysis library with a Rust core and
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bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, Java, R
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and any other C-capable language. Every indicator is an O(1) streaming state
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machine, so live trading and historical backtests share the exact same
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implementation. This package is the R binding; it reaches the C ABI hub through
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R's native `.Call` interface and exposes all 514 indicators as constructors that
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return a lightweight `wickra_indicator` object.
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## Install
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The package compiles a thin C glue layer (`.Call`) against the prebuilt Wickra
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C ABI library, so a C toolchain (Rtools on Windows) is required, plus the C ABI
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header and library. Build the library from the workspace, then install the
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package pointing at it:
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```bash
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cargo build -p wickra-c --release
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WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" \
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WICKRA_LIB_DIR="$PWD/target/release" \
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R CMD INSTALL bindings/r
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```
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On Windows the C ABI DLL is bundled into the package and put on the load path
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automatically; on Linux and macOS the library path is baked in via rpath.
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## Quick start
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```r
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library(wickra)
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# Batch: run an indicator over a whole series (NaN at warmup positions).
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prices <- 100 + (0:999) * 0.1
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sma <- Sma(20)
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values <- batch(sma, prices)
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# Streaming: the same indicator, fed one observation at a time in O(1).
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rsi <- Rsi(14)
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for (price in prices) {
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v <- update(rsi, price) # NaN during warmup
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if (!is.na(v) && v > 70) message("overbought")
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}
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# Multi-output indicators return a named vector (NA while warming up).
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macd <- MacdIndicator(12, 26, 9)
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update(macd, 42) # c(macd = NA, signal = NA, histogram = NA)
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```
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`batch(ind, prices)` and feeding the same prices through `update()` produce
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identical values — the equivalence is enforced by the test suite. Candle-input
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indicators take the OHLCV fields plus a timestamp, e.g.
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`update(atr, open, high, low, close, volume, timestamp)`. The native handle is
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freed automatically when the object is garbage-collected.
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## Documentation
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The full indicator catalogue, guides, quickstarts, and API reference live in the
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main repository and documentation site:
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- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
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- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
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- **Runnable examples:** [`examples/r/`](https://github.com/wickra-lib/wickra/tree/main/examples/r)
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Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
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C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
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all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
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## Disclaimer
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Wickra is an indicator toolkit, not a trading system. The values it computes are
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deterministic transforms of the input data — they are not financial advice and
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do not predict the market. Any use in a live trading context is at your own risk.
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The library is provided **as is**, without warranty of any kind.
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## License
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Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
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or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.
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