kingchenc
806ae22abe
Version bump `0.8.7` → `0.8.8`. ### Fixed - R binding: declare `Depends: R (>= 2.10)`, clearing the `R CMD check` "package needs dependence on R (>= 2.10)" warning that the bundled, lazy-loaded `sample_ohlcv` dataset triggers on r-universe / CRAN. (#264) Bump touches the manual release touchpoints only; docs/webpage version strings are left to `sync-about.yml` on the tag.
116 lines
4.5 KiB
Markdown
116 lines
4.5 KiB
Markdown
# Wickra — Java
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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://central.sonatype.com/artifact/org.wickra/wickra)
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[](https://github.com/wickra-lib/wickra#license)
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**Streaming-first technical indicators for the JVM, on the Java Foreign Function
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& Memory API — prebuilt native library, no JNI, no system dependencies.**
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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 bots and historical backtests share the exact same
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implementation. This package is the Java binding; it consumes the C ABI hub
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through the Panama FFM API (`java.lang.foreign`) and exposes all 514
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streaming-first indicators as idiomatic `AutoCloseable` classes.
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## Requirements
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- **Java 22 or later** (the FFM API is final since Java 22; no preview flag).
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- The FFM API is *restricted*: pass `--enable-native-access=ALL-UNNAMED` when you
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run your application to silence the native-access warning.
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## Install
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Maven:
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```xml
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<dependency>
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<groupId>org.wickra</groupId>
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<artifactId>wickra</artifactId>
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<version>0.8.8</version>
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</dependency>
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```
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Gradle:
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```kotlin
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implementation("org.wickra:wickra:0.8.8")
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```
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The native library ships prebuilt per platform (Linux, macOS, Windows — x64 and
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arm64) inside the jar and is extracted automatically on first use. There is
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nothing to compile.
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## Quick start
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```java
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import org.wickra.Ema;
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import org.wickra.Rsi;
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// Batch: run an indicator over a whole series (NaN at warmup positions).
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double[] prices = new double[1000];
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for (int i = 0; i < prices.length; i++) {
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prices[i] = 100.0 + i * 0.1;
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}
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try (Ema ema = new Ema(20)) {
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double[] values = ema.batch(prices);
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}
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// Streaming: the same indicator, fed tick by tick in O(1).
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try (Rsi rsi = new Rsi(14)) {
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for (double price : liveFeed) {
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double value = rsi.update(price); // NaN during warmup, no recomputation
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if (Double.isFinite(value) && value > 70) {
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System.out.println("overbought");
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}
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}
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}
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```
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`batch(prices)` and feeding the same prices through `update()` produce identical
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values — the equivalence is enforced by the test suite. Multi-output indicators
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(MACD, Bollinger, ADX, …) return a `record`, `null` while warming up. Each
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indicator owns a native handle freed by a `Cleaner`; `close()` releases it
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eagerly (use try-with-resources).
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## Benchmark
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`benchmarks/` reports streaming and batch updates-per-second for `SMA`, `ATR`
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and `MACD`. It measures this binding's FFI overhead, not a cross-library ratio
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(the same Rust core runs under every binding) — see the repository
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[BENCHMARKS.md](https://github.com/wickra-lib/wickra/blob/main/BENCHMARKS.md) §3.
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```bash
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cargo build -p wickra-c --release
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mvn -q install -DskipTests
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mvn -q -f benchmarks exec:exec -Dexec.mainClass=org.wickra.benchmarks.Throughput
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```
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## Documentation
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The full indicator catalogue, guides, quickstarts, and API reference live in
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the 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/java/`](https://github.com/wickra-lib/wickra/tree/main/examples/java)
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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++, Go, C#, 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
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are deterministic transforms of the input data — they are not financial advice
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and do not predict the market. Any use in a live trading context is at your own
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risk. 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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