Files
wickra/bindings/python
kingchenc 0b11a523a0 F10: add Chaikin Money Flow, Chaikin Oscillator, Force Index and Ease of Movement
- Rust core: cmf.rs (Chaikin Money Flow — summed money-flow volume over
  summed volume, bounded to [-1, +1]), chaikin_oscillator.rs (Chaikin
  Oscillator — the MACD of the ADL, EMA(ADL, fast) - EMA(ADL, slow)),
  force_index.rs (Elder's Force Index — EMA of price change scaled by
  volume), ease_of_movement.rs (Arms' Ease of Movement — SMA of distance
  travelled per unit of volume). Each with a full Indicator impl,
  runnable doctest and reference / property / warmup / reset /
  batch==streaming tests.
- Python: PyChaikinMoneyFlow / PyChaikinOscillator / PyForceIndex /
  PyEaseOfMovement PyO3 classes + module registration + .pyi stubs.
- Node: explicit ChaikinMoneyFlowNode / ChaikinOscillatorNode /
  ForceIndexNode / EaseOfMovementNode; index.d.ts and index.js updated.
- WASM: WasmChaikinMoneyFlow / WasmChaikinOscillator / WasmForceIndex /
  WasmEaseOfMovement.
- Wiki: Indicator-ChaikinMoneyFlow/ChaikinOscillator/ForceIndex/
  EaseOfMovement.md plus a new "Oscillators" sub-table in
  Indicators-Overview.md and entries in Home.md.

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 402 core tests,
25 data tests and 57 doctests green.
2026-05-22 19:25:32 +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.