Files
wickra/bindings/python
kingchenc 780a176072 F2: add ZLEMA, T3 and VWMA advanced moving averages
Completes the F2 family (Advanced MAs) end to end:

- Rust core: zlema.rs (Zero-Lag EMA over the de-lagged series
  2·price − price[lag]), t3.rs (Tillson's six-EMA cascade with the
  volume-factor polynomial), vwma.rs (volume-weighted rolling mean with
  a zero-volume fallback to the unweighted mean). Each with a full
  Indicator impl, runnable doctest and reference-value / warmup /
  reset / batch==streaming / non-finite tests.
- Python: PyZlema / PyT3 / PyVwma PyO3 classes + module registration
  + .pyi stubs (T3 defaults v=0.7).
- Node: ZlemaNode via the scalar macro, explicit T3Node and VwmaNode
  classes; index.d.ts and index.js updated.
- WASM: WasmZlema / WasmT3 via the scalar macro, explicit WasmVwma.
- Wiki: Indicator-Zlema.md, Indicator-T3.md, Indicator-Vwma.md plus
  rows in Indicators-Overview.md and entries in Home.md.

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 232 core tests,
25 data tests and 33 doctests green.
2026-05-22 17:45:02 +02:00
..

Wickra — Python bindings

Streaming-first technical indicators powered by a Rust core.

pip install wickra

Quick start

import numpy as np
import wickra as ta

# Batch — TA-Lib-style usage
prices = np.linspace(100, 200, 1000)
rsi = ta.RSI(14).batch(prices)            # NumPy array; NaN during warmup

# Streaming — feed ticks one at a time
rsi = ta.RSI(14)
for price in live_prices:
    v = rsi.update(price)                 # O(1) per tick
    if v is not None and v > 70:
        ...

What's included

25 streaming-first indicators across four families. Every one passes a batch == streaming equivalence test and reference-value tests:

  • Trend — SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA
  • Momentum — RSI (Wilder), MACD, Stochastic, CCI, ROC, WilliamsR, ADX, MFI, TRIX, AwesomeOscillator, Aroon
  • Volatility — BollingerBands, ATR, Keltner, Donchian, PSAR
  • Volume — OBV, VWAP

Why streaming-first matters

Classic TA libraries are batch-only: every live tick triggers a full recomputation over the entire history. Wickra updates indicator state in O(1) per tick. On a 5K-bar history the streaming RSI gap is ~17× over the nearest peer with a streaming API and 100×+ over batch-only libraries.

Full project

See https://github.com/kingchenc/wickra for benchmarks, the Rust core, Node.js and WebAssembly bindings, examples, and CI.

License

Licensed under the PolyForm Noncommercial License 1.0.0. Personal, research, educational, and non-profit use are all permitted. Commercial sale requires a separate license — contact via the GitHub repo.