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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

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Wickra

Wickra is a streaming-first technical-indicators library. Every indicator is implemented in Rust as an O(1) state machine that consumes one input at a time, and the same engine is exposed through ergonomic bindings for Python, Node.js, WebAssembly, and Rust itself. The same update call you write inside a live trading loop also drives the historical backtest of that same strategy — there is no second code path that drifts behind the streaming one.

The project ships 25 indicators across the four classical families (trend, momentum, volatility, volume) and a small set of supporting types (Candle, Tick, Chain). The Rust core forbids unsafe, so every binding inherits a memory-safe implementation. Install is one command on every supported platform: pip install wickra, cargo add wickra, npm install wickra — no system compilers, no C dependencies, no headers.

Wickra is licensed under the PolyForm Noncommercial 1.0.0 license. Personal projects, research, hobby trading bots, education, non-profits, and government use are all permitted; commercial sale of the software or of services built around it is not. If you want to use Wickra commercially, open an issue on GitHub to discuss a separate license.

Published versions

Registry Package Version
crates.io wickra 0.1.4
crates.io wickra-core 0.1.4
crates.io wickra-data 0.1.4
PyPI wickra 0.1.4
npm wickra 0.1.4
npm wickra-wasm 0.1.4

Release notes and tagged builds: https://github.com/kingchenc/wickra/releases.

Wiki contents

  • Quickstart: Python — pip install wickra, a batch RSI on a NumPy array, a streaming RSI loop, and the multi-column NaN pattern that MACD and friends share.
  • Quickstart: Rust — cargo add wickra, batch and streaming via the Indicator and BatchExt traits, and the Chain combinator.
  • Quickstart: Node — npm install wickra, basic SMA and MACD calls, and the current Windows install caveat (wickra-win32-x64-msvc@0.1.4 is held by the npm spam filter).
  • Quickstart: WASM — npm install wickra-wasm, building with wasm-pack, and running indicators client-side in a browser or bundler.
  • Data Layer — the wickra-data crate: the CSV reader, the tick-to-candle aggregator, the multi-timeframe resampler, and the Binance live feed.
  • Streaming vs Batch — the conceptual difference between Wickra's O(1) update and the recompute-everything loops in batch-only libraries, with the benchmark numbers from the project README.
  • Warmup Periods — a verified table of every indicator's warmup_period(), plus the reasoning behind the off-by-one cases (RSI(14) needs 15 inputs because it needs 14 diffs).
  • Indicator Chaining — Chain::new(first, second) and .then(third), with a worked EMA(14) → RSI(7) example and the rule for stacked warmups.

Indicator reference

Start with Indicators-Overview.md for the cross-cutting taxonomy (trend / momentum / volatility / volume) and the shared Indicator trait surface. The per-indicator pages below cover formulas, parameters, warmup behaviour, edge cases, and verified Rust / Python / Node examples. They are grouped by family, mirroring the indicators/<family>/ directory layout.

Trend — smooth the price series to surface direction.

Momentum — measure the rate of price change rather than the level.

Volatility — envelope width and per-bar dispersion measures.

Volume — price moves weighted or confirmed by traded volume.

See also

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