▶ Live demo: all 514 indicators over real Binance market data, computed live in your browser — live.wickra.org · zero backend, powered by
wickra-wasm.
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.
- 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-UNNAMEDwhen you run your application to silence the native-access warning.
Maven:
<dependency>
<groupId>org.wickra</groupId>
<artifactId>wickra</artifactId>
<version>0.9.9</version>
</dependency>Gradle:
implementation("org.wickra:wickra:0.9.9")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.
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).
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.ThroughputThe 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/java/
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.
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.
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.
Licensed under either of Apache-2.0 or MIT at your option.
