Wickra.Gym 0.1.6

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Wickra Gym — C#

Part of the Wickra ecosystem — for C#. dotnet add package Wickra.Gym — prebuilt native library, no system dependencies.

.NET bindings for wickra-gym over the C ABI hub, via source-generated P/Invoke. Build an Env from a spec JSON, drive it with command JSON and read back observations and rewards — the same protocol the CLI and every other binding speak, returning the same bytes.

Install

dotnet add package Wickra.Gym

The native library ships prebuilt per platform under runtimes/<rid>/native/, selected automatically. There is nothing to compile. Targets .NET 8 and later.

Requires .NET 8+. The native library (wickra_gym) must be resolvable on the loader path — PATH on Windows, LD_LIBRARY_PATH on Linux, DYLD_LIBRARY_PATH on macOS — or beside the assembly, where the bundled resolver finds it.

Quick start

using Wickra.Gym;

const string spec = """
{"dataset_ref":"demo","symbol":"BTCUSDT",
 "observation":{"features":[{"kind":"indicator","name":"Rsi","params":[14]},
                            {"kind":"price","field":"close"}]},
 "action_space":{"type":"discrete","n":3},
 "reward":"pnl","episode":{"max_steps":256,"warmup":14}}
""";

using var env = new Env(spec);
env.Command("""{"cmd":"load","candles":[ … ]}""");
string reset = env.Command("""{"cmd":"reset","seed":7}""");
string step = env.Command("""{"cmd":"step","action":2.0}""");

The dataset is precomputed once into a fixed feature tensor, so every step is a pure array index and a (seed, policy) pair fully determines the trajectory — in this binding exactly as in the other nine.

episode.warmup must be at least the longest lookback the observation's indicators declare: below it a column is 0.0 because nothing has been produced yet, which an agent cannot tell from a market reading of zero. A spec below the floor is refused rather than run. An indicator that reads an order book or a funding print needs bars that carry them, and is likewise refused rather than answered with a column of constant zeros.

Benchmark

Every binding forwards to the same data-driven Rust core, so what this one adds is the call overhead of [LibraryImport] P/Invoke over the C ABI, not a different result. The core's throughput is measured by the repository's benchmark suite and the nightly bench.yml run; the numbers, the machine and how to reproduce them are in the repository BENCHMARKS.md.

Documentation

The full guide, the spec reference and the API documentation live in the main repository and the documentation site:

• Repository: https://github.com/wickra-lib/wickra-gym
• Docs (guides, spec reference, cookbook): https://gym.wickra.org
• Runnable example: examples/csharp/

Wickra Gym 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 forwarding to the same data-driven, unsafe-forbidden Rust core.

Security

Found a security issue? Please don't open a public issue. Report it privately via the 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-gym/blob/main/SECURITY.md.

Disclaimer

wickra-gym is research and engineering tooling, not financial advice. A trained agent's backtested performance says nothing about future returns; markets carry risk and you are responsible for your own decisions. wickra-gym is free software you run yourself: no hosted service, no data collection, no warranty.

License

Licensed under either of Apache-2.0 or MIT at your option.