kingchenc
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.
54 lines
1.9 KiB
Rust
54 lines
1.9 KiB
Rust
//! `wickra-core`: streaming-first technical indicators.
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//!
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//! The core engine of Wickra. Every indicator is implemented as a state machine
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//! that consumes inputs one at a time via [`Indicator::update`] in constant time.
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//! Batch evaluation is provided as a blanket extension trait so the same code
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//! path serves both online (tick-by-tick) and offline (historical) workloads.
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//!
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//! # Design
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//!
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//! - **Streaming-first.** State is held by the indicator instance, so a new value
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//! only re-computes deltas, not the whole series.
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//! - **Batch is free.** [`BatchExt::batch`] is a blanket implementation that
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//! simply replays `update` over a slice. Writing one implementation gives both
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//! APIs.
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//! - **Composable.** Indicators implement [`Indicator<Input = f64, Output = f64>`]
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//! wherever they conceptually take a price, so they can be chained via
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//! [`Chain`].
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//! - **No `unsafe`.** The crate forbids `unsafe_code` in the workspace lints.
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//!
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//! # Quick start
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//!
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//! ```
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//! use wickra_core::{BatchExt, Indicator, Sma};
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//!
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//! // Streaming:
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//! let mut sma = Sma::new(3).unwrap();
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//! assert_eq!(sma.update(1.0), None);
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//! assert_eq!(sma.update(2.0), None);
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//! assert_eq!(sma.update(3.0), Some(2.0));
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//!
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//! // Batch (replays `update` internally):
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//! let mut sma = Sma::new(3).unwrap();
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//! let out = sma.batch(&[1.0, 2.0, 3.0, 4.0]);
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//! assert_eq!(out, vec![None, None, Some(2.0), Some(3.0)]);
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//! ```
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#![cfg_attr(docsrs, feature(doc_auto_cfg))]
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mod error;
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mod ohlcv;
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mod traits;
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pub mod indicators;
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pub use error::{Error, Result};
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pub use indicators::{
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Adx, AdxOutput, Aroon, AroonOutput, Atr, AwesomeOscillator, BollingerBands, BollingerOutput,
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Cci, Dema, Donchian, DonchianOutput, Ema, Hma, Kama, Keltner, KeltnerOutput, MacdIndicator,
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MacdOutput, Mfi, Obv, Psar, Roc, RollingVwap, Rsi, Sma, Stochastic, StochasticOutput, Tema,
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Trix, Vwap, WilliamsR, Wma,
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};
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pub use ohlcv::{Candle, Tick};
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pub use traits::{BatchExt, Chain, Indicator};
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