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kingchenc 896b71fc62 release(0.1.5): bump versions, finalize CHANGELOG, fail loud on missing platform binaries (R20, Z2) 
Versions bumped to 0.1.5 in every authoritative location:

- workspace `Cargo.toml` (`[workspace.package].version`, the
  `wickra-core` path dependency pin).
- `bindings/python/pyproject.toml`.
- `bindings/node/package.json` (main + all six `optionalDependencies`
  pins).
- All six per-platform `bindings/node/npm/<target>/package.json`
  templates.

CHANGELOG: the accumulated `[Unreleased]` block is promoted to
`[0.1.5] - TBD` (date left for the user to set at tag time); the new
`[Unreleased]` header sits empty above it; the compare link table is
extended with `[0.1.5]: …compare/v0.1.4...v0.1.5` and the
`[Unreleased]` link is repointed to `…compare/v0.1.5...HEAD`.

Wiki refresh for 0.1.5 (R20 + Z2):

- `Home.md` version pin table updated; the Quickstart-Node hint replaces
  the "spam filter holding back Windows" caveat with "0.1.5 is the
  first release in which `npm install wickra` works end-to-end on
  Windows" (npm Support released the name on 2026-05-22).
- `Quickstart-Node.md`'s Windows caveat is rewritten to explain the
  history (`0.1.1`–`0.1.4` of `wickra-win32-x64-msvc` are burned) and
  the resolution (0.1.5+ installs cleanly).
- `Quickstart-Rust.md` version mention bumped.
- `Warmup-Periods.md` note bumped + corrected: every Node and WASM
  class — single- and multi-output — now exposes `warmupPeriod()` after
  R3 (this branch), not only the single-output ones.

`release.yml` `publish_dir` no longer silently swallows a
second-attempt platform-package publish failure with a `::warning::`
and `return 0`. A real failure (after the existing 30s retry) now
emits an `::error::` and fails the job. The original mask is exactly
what allowed the `wickra-win32-x64-msvc@0.1.1–0.1.4` spam-filter
rejections to land four times in a row without anyone noticing (audit
finding R20). Failing loud means the next regression of this shape is
caught at the release run, not by a Windows user trying to
`require('wickra')`.

This commit does NOT push, tag, or trigger a release — the user
publishes the 0.1.5 tag themselves once the manual npm-republish
smoke test confirms `wickra-win32-x64-msvc@0.1.5` accepts publish on
the freshly-released name.
2026-05-23 10:58:08 +02:00

10 KiB
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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 71 indicators across eight families — moving averages, momentum oscillators, trend & directional, price oscillators, volatility & bands, trailing stops, volume, and price statistics — plus 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 0.1.5
crates.io wickra-core 0.1.5
crates.io wickra-data 0.1.5
PyPI wickra 0.1.5
npm wickra 0.1.5
npm wickra-wasm 0.1.5

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 install surface. Windows x64 was previously blocked by an npm spam filter on wickra-win32-x64-msvc; that was resolved with npm Support, and 0.1.5 is the first release in which npm install wickra works end-to-end on Windows.
  • 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.
  • Cookbook — copy-paste strategy recipes built on streaming indicators (RSI mean reversion, MACD crossover, Bollinger breakout, ADX-gated trend, multi-timeframe, SuperTrend trailing stop).
  • TA-Lib Migration — function-by-function mapping table from TA-Lib's talib.X(...) calls to the equivalent Wickra expressions.
  • FAQ — quick answers to the most common questions about warmup, NaN handling, thread safety, and the streaming-vs-batch contract.

Indicator reference

Start with Indicators-Overview.md for the full eight-family taxonomy 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.

Moving Averages — smooth the price series to surface direction.

Momentum Oscillators — measure the rate of price change.

Trend & Directional — is there a trend, and which way?

Price Oscillators — difference-of-averages momentum around zero.

Volatility & Bands — dispersion measures and price envelopes.

Trailing Stops — ATR-driven stop-loss trackers.

Volume — price moves weighted or confirmed by traded volume.

Price Statistics — per-bar transforms and rolling regressions.

See also

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