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kingchenc 2f3b5cc3be F-Abschluss: wire the Python package, refresh docs and extend the test suites

Finalises the F1-F12 indicator expansion (25 -> 63 indicators).

- Python `wickra/__init__.py`: import and re-export all 63 indicators,
  grouped by family, with a matching `__all__`. The package previously
  exposed only the original 25 even though the compiled module and the
  `.pyi` stubs already carried the rest.
- Docs: `Home.md` and `README.md` indicator counts and family tables
  updated to 63; `Indicators-Overview.md` already restructured per family
  in F10-F12; `Warmup-Periods.md` gains all 38 new indicators across the
  single- and multi-output tables (and the stale two-arg `Psar::new`
  example is corrected to three args); `CHANGELOG.md` `[Unreleased]` lists
  every new indicator by family.
- Tests: `bindings/node/__tests__/indicators.test.js` covers all 63
  indicators (streaming==batch plus four new reference-value checks),
  80/80 green; new `bindings/python/tests/test_new_indicators.py` covers
  the 38 additions (streaming==batch, shapes, reference values,
  lifecycle), Python suite 105/105 green.
- `bindings/node/index.js` regenerated by `napi build`.

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 454 core tests,
25 data tests, 66 doctests, 80 Node tests and 105 Python tests green;
`cargo check -p wickra-wasm --tests` green.

2026-05-22 20:04:13 +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 63 indicators across the four classical families (trend, momentum, volatility, volume) plus a statistics group, 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.

Statistics — price transforms and rolling regressions.

8.3 KiB Raw Blame History

Wickra

Published versions

Wiki contents

Indicator reference

See also

8.3 KiB

Raw Blame History