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.

crates/wickra-core/src/indicators/aroon.rs

@@ -0,0 +1,156 @@
+//! Aroon Up / Down indicator.
+
+use std::collections::VecDeque;
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Aroon output: up and down strengths in [0, 100].
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub struct AroonOutput {
+    /// Time since the highest high, expressed as a percentage of the window.
+    pub up: f64,
+    /// Time since the lowest low, same convention.
+    pub down: f64,
+}
+
+/// Aroon indicator: tracks how many bars since the highest high and lowest low
+/// inside a `period + 1`-bar window. Returned as a percentage.
+#[derive(Debug, Clone)]
+pub struct Aroon {
+    period: usize,
+    candles: VecDeque<Candle>,
+}
+
+impl Aroon {
+    /// # Errors
+    /// Returns [`Error::PeriodZero`] if `period == 0`.
+    pub fn new(period: usize) -> Result<Self> {
+        if period == 0 {
+            return Err(Error::PeriodZero);
+        }
+        Ok(Self {
+            period,
+            candles: VecDeque::with_capacity(period + 1),
+        })
+    }
+
+    /// Configured period.
+    pub const fn period(&self) -> usize {
+        self.period
+    }
+}
+
+impl Indicator for Aroon {
+    type Input = Candle;
+    type Output = AroonOutput;
+
+    fn update(&mut self, candle: Candle) -> Option<AroonOutput> {
+        if self.candles.len() == self.period + 1 {
+            self.candles.pop_front();
+        }
+        self.candles.push_back(candle);
+        if self.candles.len() < self.period + 1 {
+            return None;
+        }
+        // Find the index (0 = oldest) of the highest high and lowest low.
+        let (mut hh_idx, mut ll_idx) = (0_usize, 0_usize);
+        let (mut hh, mut ll) = (f64::NEG_INFINITY, f64::INFINITY);
+        for (i, c) in self.candles.iter().enumerate() {
+            if c.high >= hh {
+                hh = c.high;
+                hh_idx = i;
+            }
+            if c.low <= ll {
+                ll = c.low;
+                ll_idx = i;
+            }
+        }
+        let n = self.period as f64;
+        let up = 100.0 * hh_idx as f64 / n;
+        let down = 100.0 * ll_idx as f64 / n;
+        Some(AroonOutput { up, down })
+    }
+
+    fn reset(&mut self) {
+        self.candles.clear();
+    }
+
+    fn warmup_period(&self) -> usize {
+        self.period + 1
+    }
+
+    fn is_ready(&self) -> bool {
+        self.candles.len() == self.period + 1
+    }
+
+    fn name(&self) -> &'static str {
+        "Aroon"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+    use approx::assert_relative_eq;
+
+    fn c(h: f64, l: f64, cl: f64) -> Candle {
+        Candle::new(cl, h, l, cl, 1.0, 0).unwrap()
+    }
+
+    #[test]
+    fn pure_uptrend_aroon_up_100() {
+        let candles: Vec<Candle> = (1..=15)
+            .map(|i| c(f64::from(i) + 1.0, f64::from(i) - 1.0, f64::from(i)))
+            .collect();
+        let mut a = Aroon::new(14).unwrap();
+        let last = a.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last.up, 100.0, epsilon = 1e-9);
+        // The lowest low is at the oldest position (index 0).
+        assert_relative_eq!(last.down, 0.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn pure_downtrend_aroon_down_100() {
+        let candles: Vec<Candle> = (1..=15)
+            .rev()
+            .map(|i| c(f64::from(i) + 1.0, f64::from(i) - 1.0, f64::from(i)))
+            .collect();
+        let mut a = Aroon::new(14).unwrap();
+        let last = a.batch(&candles).into_iter().flatten().last().unwrap();
+        assert_relative_eq!(last.down, 100.0, epsilon = 1e-9);
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let m = 50.0 + (f64::from(i) * 0.3).sin() * 5.0;
+                c(m + 1.0, m - 1.0, m)
+            })
+            .collect();
+        let mut a = Aroon::new(14).unwrap();
+        let mut b = Aroon::new(14).unwrap();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn outputs_in_range() {
+        let candles: Vec<Candle> = (0..200)
+            .map(|i| {
+                let m = 50.0 + (f64::from(i) * 0.2).sin() * 5.0;
+                c(m + 1.0, m - 1.0, m)
+            })
+            .collect();
+        let mut a = Aroon::new(14).unwrap();
+        for o in a.batch(&candles).into_iter().flatten() {
+            assert!((0.0..=100.0).contains(&o.up));
+            assert!((0.0..=100.0).contains(&o.down));
+        }
+    }
+}