Files
wickra/docs/wiki/Home.md
T
kingchenc 81962485af F9: add Accumulation/Distribution Line and Volume-Price Trend
Completes the F9 family (Cumulative volume) end to end:

- Rust core: adl.rs (Accumulation/Distribution Line — cumulative
  range-weighted volume) and vpt.rs (Volume-Price Trend — cumulative
  volume scaled by percentage price change). Each with a full Indicator
  impl, runnable doctest and reference / cumulative-property / warmup /
  reset / batch==streaming tests.
- Python: PyAdl / PyVolumePriceTrend PyO3 classes + module registration
  + .pyi stubs (no parameters, like OBV/VWAP).
- Node: explicit AdlNode and VolumePriceTrendNode; index.d.ts and
  index.js updated.
- WASM: WasmAdl and WasmVolumePriceTrend.
- Wiki: Indicator-Adl.md and Indicator-VolumePriceTrend.md plus rows in
  Indicators-Overview.md and entries in Home.md.

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 373 core tests,
25 data tests and 53 doctests green.
2026-05-22 18:38:21 +02:00

7.2 KiB

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: Pythonpip 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: Rustcargo add wickra, batch and streaming via the Indicator and BatchExt traits, and the Chain combinator.
  • Quickstart: Nodenpm 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: WASMnpm 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 ChainingChain::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