Files
wickra/.github/workflows/release.yml
T
kingchenc 3be267cb03 Wickra 0.1.0: streaming-first technical indicators
A multi-language technical analysis library: 25 indicators across trend,
momentum, volatility, and volume families, every one a state machine with
O(1) per-tick updates. Batch evaluation is provided by a blanket extension
trait over the streaming primitive, so live trading bots and historical
backtests run the same code path.

What ships in this initial drop:

  crates/wickra-core   - 25 indicators, Indicator/BatchExt/Chain traits,
                          OHLCV types with validation; 171 unit tests,
                          property tests, Wilder/Bollinger textbook tests.
  crates/wickra        - top-level facade + criterion benches for every
                          indicator at 1K/10K/100K series sizes.
  crates/wickra-data   - streaming CSV reader, tick-to-candle aggregator,
                          multi-timeframe resampler, Binance Spot kline
                          WebSocket adapter behind feature live-binance;
                          11 unit + 1 doctest.
  bindings/python      - PyO3 + maturin, NumPy I/O, type stubs (.pyi),
                          56 pytest tests including streaming==batch
                          equivalence, Wilder reference values, lifecycle.
  bindings/node        - napi-rs native module, TypeScript .d.ts
                          auto-generated, 7 node --test cases.
  bindings/wasm        - wasm-bindgen ES module for browser/bundler/Node;
                          interactive HTML demo at examples/index.html.
  examples/            - Python and Rust scripts: backtest, live trading,
                          parallel multi-asset, multi-timeframe, Binance.
  benchmarks/          - cross-library comparison against TA-Lib,
                          pandas-ta, finta, talipp; Wickra wins every
                          category by 11-1030x (batch) and 17x+ streaming.
  .github/workflows/   - CI matrix (Rust + Python + Node + WASM on
                          Linux/macOS/Windows), release pipeline for
                          PyPI wheels and npm.

Indicators (25):
  Trend       SMA EMA WMA DEMA TEMA HMA KAMA
  Momentum    RSI MACD Stochastic CCI ROC WilliamsR ADX MFI TRIX
              AwesomeOscillator Aroon
  Volatility  BollingerBands ATR Keltner Donchian PSAR
  Volume      OBV VWAP (cumulative + rolling)

cargo clippy --workspace --all-targets -D warnings is clean. License: Apache-2.0.
2026-05-21 17:50:45 +02:00

85 lines
1.9 KiB
YAML

name: Release
on:
push:
tags:
- "v*"
workflow_dispatch:
jobs:
build-wheels:
name: Wheels ${{ matrix.os }} ${{ matrix.target }}
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
include:
- os: ubuntu-latest
target: x86_64
- os: ubuntu-latest
target: aarch64
- os: macos-latest
target: x86_64
- os: macos-latest
target: aarch64
- os: windows-latest
target: x64
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Build wheels
uses: PyO3/maturin-action@v1
with:
working-directory: bindings/python
target: ${{ matrix.target }}
args: --release --strip --out dist
sccache: "true"
manylinux: auto
- name: Upload wheels
uses: actions/upload-artifact@v4
with:
name: wheels-${{ matrix.os }}-${{ matrix.target }}
path: bindings/python/dist/
sdist:
name: Source distribution
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build sdist
uses: PyO3/maturin-action@v1
with:
working-directory: bindings/python
command: sdist
args: --out dist
- uses: actions/upload-artifact@v4
with:
name: sdist
path: bindings/python/dist/
publish:
name: Publish to PyPI
needs: [build-wheels, sdist]
runs-on: ubuntu-latest
if: startsWith(github.ref, 'refs/tags/v')
permissions:
id-token: write
steps:
- uses: actions/download-artifact@v4
with:
path: dist
merge-multiple: true
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: dist/