Files
wickra/bindings/csharp
kingchenc a5fe2e71c4 release: bump 0.9.2 -> 0.9.3 (#325)
Release the native data-layer bundle.

`0.9.3` ships everything merged since `0.9.2`:

- **Data layer in all 10 languages** — `CandleReader` (CSV), `TickAggregator`, `Resampler`, live `BinanceFeed` (WebSocket) and the historical `fetch_binance_klines` (REST), each cross-language golden-pinned.
- **`name()` on every indicator** in all 10 languages (514 indicators, golden-pinned).
- **Python is now zero third-party deps** — NumPy is optional (`pip install wickra[numpy]`); `batch` returns a stdlib `array.array` / buffer-protocol `Matrix` (breaking; results numerically identical, batch throughput tradeoff noted in the CHANGELOG).
- **Binance feed: missing `3d` / `1M` intervals** fixed.

Pure version-string bump on top — `bump_version.py` touched 19 files (Cargo + Lock, pyproject, all node package.json/locks + 6 platform stubs, pom + csproj + DESCRIPTION, SECURITY, CHANGELOG `[0.9.3]` + compare URLs). `cargo fmt`/`clippy -D warnings`/`test --workspace --all-features` all green locally (4225+ tests, 0 failed).

The tag/publish is **not** part of this PR — it waits for explicit GO (irreversible publish to crates.io / PyPI / npm / NuGet / Maven / Go / r-universe).
2026-06-17 21:14:22 +02:00
..

Wickra — C#

CI codecov NuGet License: MIT OR Apache-2.0

Streaming-first technical indicators for C#. dotnet add package Wickra — prebuilt native library, 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 C# binding; it consumes the C ABI hub through [LibraryImport] P/Invoke and exposes all 514 streaming-first indicators as idiomatic IDisposable classes.

Install

dotnet add package Wickra

The native library ships prebuilt per platform (Linux, macOS, Windows — x64 and arm64) under runtimes/<rid>/native/, selected automatically. There is nothing to compile. Targets .NET 8 and later.

Quick start

using Wickra;

// Batch: run an indicator over a whole series (NaN at warmup positions).
var prices = Enumerable.Range(0, 1000).Select(i => 100.0 + i * 0.1).ToArray();
using var sma = new Sma(20);
double[] values = sma.Batch(prices);

// Streaming: the same indicator, fed tick by tick in O(1).
using var rsi = new Rsi(14);
foreach (var price in liveFeed)
{
    var value = rsi.Update(price); // NaN during warmup, no recomputation
    if (double.IsFinite(value) && value > 70)
    {
        Console.WriteLine("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 nullable record struct, null while warming up.

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
dotnet run -c Release --project benchmarks

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.