Files

T

kingchenc 21bbd521b3 F11: add SuperTrend, Chandelier Exit, Chande Kroll Stop and ATR Trailing Stop

- Rust core: super_trend.rs (SuperTrend — ATR-banded trailing stop with
  flip logic; SuperTrendOutput { value, direction }), chandelier_exit.rs
  (Chandelier Exit — ATR stop hung off the window's highest high / lowest
  low; ChandelierExitOutput { long_stop, short_stop }),
  chande_kroll_stop.rs (Chande Kroll Stop — a two-stage ATR stop;
  ChandeKrollStopOutput { stop_long, stop_short }), atr_trailing_stop.rs
  (ATR Trailing Stop — a single ratcheting close-based stop). Each with a
  full Indicator impl, runnable doctest and reference / property / warmup
  / reset / batch==streaming tests.
- Python: PySuperTrend / PyChandelierExit / PyChandeKrollStop /
  PyAtrTrailingStop PyO3 classes (struct outputs as tuples and (n, 2)
  arrays) + module registration + .pyi stubs.
- Node: explicit SuperTrendNode / ChandelierExitNode / ChandeKrollStopNode
  / AtrTrailingStopNode with SuperTrendValue / ChandelierExitValue /
  ChandeKrollStopValue objects; index.d.ts and index.js updated.
- WASM: WasmSuperTrend / WasmChandelierExit / WasmChandeKrollStop /
  WasmAtrTrailingStop.
- Wiki: Indicator-SuperTrend/ChandelierExit/ChandeKrollStop/
  AtrTrailingStop.md plus rows in the "Trailing stop" table of
  Indicators-Overview.md and entries in Home.md.
- Add clippy.toml with doc-valid-idents for the proper noun "LeBeau".

cargo fmt + clippy (core/wickra/data/wasm/node) clean; 427 core tests,
25 data tests and 61 doctests green.

2026-05-22 19:42:14 +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.

7.8 KiB Raw Blame History

Wickra

Published versions

Wiki contents

Indicator reference

See also

7.8 KiB

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