About Wickra

Wickra is a multi-language technical-analysis library with a Rust core and first-class bindings for Python, Node.js, and WASM. Every indicator is a state machine that updates in O(1) per new data point, so live trading bots and historical backtests share the exact same implementation — no separate "streaming" and "batch" code paths to drift apart.

What makes it different

Plenty of TA libraries are fast. Wickra's edge is breadth with reach: 514 indicators that all update in O(1) per tick and ship natively to four language targets from a single engine. See the indicators overview for the full catalogue.

• Streaming-first. Each update advances internal state in constant time — no recomputation over history, the same call whether you feed a 50,000-bar backtest or one live tick.
• One engine, ten languages. The Rust core ships as a crate, Python wheels, a Node native addon and a WASM bundle, plus a C ABI that C, C++, C#, Go, Java and R link against. Identical numbers everywhere — every one of the 514 indicators is replayed through all 10 languages and checked bit-for-bit against the Rust reference in CI.
• Install-free. pip install wickra, npm install wickra, cargo add wickra — no system dependencies, no C toolchain, no build step.
• Safe by construction. Every update validates its input, runs a real warmup before it emits a value, and returns an Option/None/NaN during warmup so a single bad tick can't silently poison the state.

On speed — and the deliberate trade-off

Wickra is not the fastest TA crate, and that is a choice rather than a ceiling. The leaner Rust crates win several micro-benchmarks, and those losses are shown rather than hidden. The gap exists because Wickra keeps its guarantees — input validation, a real warmup contract, NaN-safety — instead of handing back a bare f64 from the first tick. What no other library matches is the combination: catalogue size, native O(1) streaming, NaN-safety, and four first-class language targets at once.

Why it exists

Wickra started as a personal itch. The existing TA libraries never quite fit the projects being built on them, so the decision was to build one from the ground up — partly to learn, partly for the genuine enjoyment of taking something that already exists and trying to do it differently, and ideally better. It is open source because the useful version of that itch is the one other people can build on too.

Open source

Wickra is dual-licensed under MIT OR Apache-2.0 — use it, fork it, modify it, redistribute it, commercially or not. Issues and pull requests are welcome.

• Source: github.com/wickra-lib/wickra
• Documentation: docs.wickra.org
• Packages: crates.io · PyPI · npm

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 they do not predict the market. Any use of this library in a production trading context is at your own risk. The library is provided as is, without warranty of any kind; see the license for the full terms.