Files
wickra/bindings/java
kingchenc d362ae26a3 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.
2026-06-16 00:10:58 +02:00
..
2026-06-15 06:02:05 +02:00
2026-06-15 06:02:05 +02:00

Wickra — Java

CI codecov Maven Central License: MIT OR Apache-2.0

Streaming-first technical indicators for the JVM, on the Java Foreign Function & Memory API — prebuilt native library, no JNI, no system dependencies.

Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js and WASM, plus a C ABI for C, C++, C#, Go, Java, 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 Java binding; it consumes the C ABI hub through the Panama FFM API (java.lang.foreign) and exposes all 514 streaming-first indicators as idiomatic AutoCloseable classes.

Requirements

  • Java 22 or later (the FFM API is final since Java 22; no preview flag).
  • The FFM API is restricted: pass --enable-native-access=ALL-UNNAMED when you run your application to silence the native-access warning.

Install

Maven:

<dependency>
  <groupId>org.wickra</groupId>
  <artifactId>wickra</artifactId>
  <version>0.9.2</version>
</dependency>

Gradle:

implementation("org.wickra:wickra:0.9.2")

The native library ships prebuilt per platform (Linux, macOS, Windows — x64 and arm64) inside the jar and is extracted automatically on first use. There is nothing to compile.

Quick start

import org.wickra.Ema;
import org.wickra.Rsi;

// Batch: run an indicator over a whole series (NaN at warmup positions).
double[] prices = new double[1000];
for (int i = 0; i < prices.length; i++) {
    prices[i] = 100.0 + i * 0.1;
}
try (Ema ema = new Ema(20)) {
    double[] values = ema.batch(prices);
}

// Streaming: the same indicator, fed tick by tick in O(1).
try (Rsi rsi = new Rsi(14)) {
    for (double price : liveFeed) {
        double value = rsi.update(price); // NaN during warmup, no recomputation
        if (Double.isFinite(value) && value > 70) {
            System.out.println("overbought");
        }
    }
}

batch(prices) and feeding the same prices through update() produce identical values — the equivalence is enforced by the test suite. Multi-output indicators (MACD, Bollinger, ADX, …) return a record, null while warming up. Each indicator owns a native handle freed by a Cleaner; close() releases it eagerly (use try-with-resources).

Benchmark

benchmarks/ reports streaming and batch updates-per-second for SMA, ATR and MACD. It measures this binding's FFI overhead, not a cross-library ratio (the same Rust core runs under every binding) — see the repository BENCHMARKS.md §3.

cargo build -p wickra-c --release
mvn -q install -DskipTests
mvn -q -f benchmarks exec:exec -Dexec.mainClass=org.wickra.benchmarks.Throughput

Documentation

The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:

Wickra ships native bindings for Python, Node.js, WASM and Rust, plus a C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against — all exposing the same indicators from the shared, unsafe-forbidden Rust core.

Security

Found a security issue? Please don't open a public issue. Report it privately via the affected repository's Security tab ("Report a vulnerability") or email support@wickra.org with a subject line starting [wickra security]. Full policy: https://github.com/wickra-lib/wickra/blob/main/SECURITY.md.

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.