- 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.
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.