3be267cb03
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.
63 lines
1.7 KiB
TOML
63 lines
1.7 KiB
TOML
[build-system]
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requires = ["maturin>=1.7,<2.0"]
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build-backend = "maturin"
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[project]
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name = "wickra"
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version = "0.1.0"
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description = "Streaming-first technical indicators: incremental, fast, install-free."
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readme = "../../README.md"
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license = { text = "Apache-2.0" }
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requires-python = ">=3.9"
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keywords = ["finance", "trading", "indicators", "technical-analysis", "ta-lib"]
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classifiers = [
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"Development Status :: 4 - Beta",
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"Intended Audience :: Financial and Insurance Industry",
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"License :: OSI Approved :: Apache Software License",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3 :: Only",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Rust",
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"Topic :: Office/Business :: Financial :: Investment",
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"Topic :: Scientific/Engineering :: Mathematics",
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]
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dependencies = [
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"numpy>=1.22",
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]
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[project.optional-dependencies]
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test = [
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"pytest>=7",
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"numpy>=1.22",
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"hypothesis>=6",
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]
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bench = [
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"pytest-benchmark>=4",
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"TA-Lib; platform_system != 'Windows'",
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"pandas-ta>=0.3.14b",
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"talipp>=2",
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"finta>=1.3",
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"pandas>=2",
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"numpy>=1.22",
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]
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[project.urls]
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Homepage = "https://github.com/wickra/wickra"
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Repository = "https://github.com/wickra/wickra"
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Issues = "https://github.com/wickra/wickra/issues"
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[tool.maturin]
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manifest-path = "Cargo.toml"
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python-source = "python"
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module-name = "wickra._wickra"
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features = ["pyo3/extension-module"]
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strip = true
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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addopts = "-ra -q"
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filterwarnings = ["error"]
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