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Wickra

Streaming-first technical indicators — Rust core with Python, Node.js and WebAssembly bindings. 71 indicators, install-free.

Wickra

Streaming-first technical indicators. Rust core with bindings for Python, Node.js, and WebAssembly. Every indicator is a state machine that updates in O(1) per new data point — same code for backtest and live tick.

import wickra as ta

rsi = ta.RSI(14)
for price in live_feed:
    value = rsi.update(price)   # O(1) — no recomputation over history
    if value is not None and value > 70:
        print("overbought")

Install

Language Install
Python pip install wickra
Rust cargo add wickra
Node.js npm install wickra
Browser / WASM npm install wickra-wasm

No C compiler, no headers, no Rust toolchain required on the install side — pre-built native packages on every supported platform.

Highlights

  • 75 indicators across eight families (moving averages, momentum oscillators, trend & directional, price oscillators, volatility & bands, trailing stops, volume, price statistics)
  • batch == streaming equivalence — every indicator passes a bit-for-bit test that streaming results match batch results
  • Rust core forbids unsafe — every binding inherits a memory-safe implementation
  • Verified against reference values from TA-Lib and Wilder's original tables

Repositories

  • wickra — main library (Rust core + Python / Node / WASM bindings)
  • wickra.wiki — 84 pages of deep-dive docs (per-indicator formulas, parameters, warmup)

License

PolyForm Noncommercial 1.0.0 — personal projects, research, hobby trading bots, education, non-profits and government use are all permitted. For commercial use, open an issue.

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