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
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+//! Parabolic SAR (Wilder).
+
+use crate::error::{Error, Result};
+use crate::ohlcv::Candle;
+use crate::traits::Indicator;
+
+/// Trade direction in the SAR state machine.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+enum Trend {
+    Up,
+    Down,
+}
+
+/// Parabolic Stop And Reverse.
+///
+/// Implementation follows Wilder's original recursion: each step computes a new
+/// SAR from the previous SAR, extreme point (EP) and acceleration factor (AF);
+/// the trend flips when price crosses the SAR.
+#[derive(Debug, Clone)]
+pub struct Psar {
+    af_start: f64,
+    af_step: f64,
+    af_max: f64,
+
+    initialised: bool,
+    prev_high: f64,
+    prev_low: f64,
+    trend: Trend,
+    sar: f64,
+    ep: f64,
+    af: f64,
+}
+
+impl Psar {
+    /// Construct PSAR with explicit acceleration parameters.
+    ///
+    /// # Errors
+    /// Returns [`Error::NonPositiveMultiplier`] / [`Error::InvalidPeriod`] for invalid params.
+    pub fn new(af_start: f64, af_step: f64, af_max: f64) -> Result<Self> {
+        if !af_start.is_finite() || !af_step.is_finite() || !af_max.is_finite() {
+            return Err(Error::NonPositiveMultiplier);
+        }
+        if af_start <= 0.0 || af_step <= 0.0 || af_max <= 0.0 {
+            return Err(Error::NonPositiveMultiplier);
+        }
+        if af_start > af_max {
+            return Err(Error::InvalidPeriod {
+                message: "af_start must be <= af_max",
+            });
+        }
+        Ok(Self {
+            af_start,
+            af_step,
+            af_max,
+            initialised: false,
+            prev_high: 0.0,
+            prev_low: 0.0,
+            trend: Trend::Up,
+            sar: 0.0,
+            ep: 0.0,
+            af: af_start,
+        })
+    }
+
+    /// Wilder's defaults: `(0.02, 0.02, 0.20)`.
+    pub fn classic() -> Self {
+        Self::new(0.02, 0.02, 0.20).expect("classic PSAR params are valid")
+    }
+}
+
+impl Indicator for Psar {
+    type Input = Candle;
+    type Output = f64;
+
+    fn update(&mut self, candle: Candle) -> Option<f64> {
+        if !self.initialised {
+            // Seed: the first emitted SAR comes on the second candle. Initial trend
+            // is chosen by whether the second close is above or below the first.
+            self.prev_high = candle.high;
+            self.prev_low = candle.low;
+            self.sar = candle.low;
+            self.ep = candle.high;
+            self.trend = Trend::Up;
+            self.af = self.af_start;
+            self.initialised = true;
+            return None;
+        }
+
+        // Predicted SAR for this period (before clamping to prior two extremes).
+        let mut new_sar = self.sar + self.af * (self.ep - self.sar);
+
+        // Wilder rule: SAR cannot penetrate today's or yesterday's range.
+        let prev_h = self.prev_high;
+        let prev_l = self.prev_low;
+        new_sar = match self.trend {
+            Trend::Up => new_sar.min(prev_l).min(candle.low),
+            Trend::Down => new_sar.max(prev_h).max(candle.high),
+        };
+
+        let mut output_sar = new_sar;
+
+        // Check for trend reversal.
+        let reversed = match self.trend {
+            Trend::Up => candle.low <= new_sar,
+            Trend::Down => candle.high >= new_sar,
+        };
+
+        if reversed {
+            // Flip trend, reset AF and EP, place SAR at prior EP.
+            output_sar = self.ep;
+            self.trend = match self.trend {
+                Trend::Up => Trend::Down,
+                Trend::Down => Trend::Up,
+            };
+            self.ep = match self.trend {
+                Trend::Up => candle.high,
+                Trend::Down => candle.low,
+            };
+            self.af = self.af_start;
+        } else {
+            // Update EP and AF if a new extreme has been reached.
+            match self.trend {
+                Trend::Up => {
+                    if candle.high > self.ep {
+                        self.ep = candle.high;
+                        self.af = (self.af + self.af_step).min(self.af_max);
+                    }
+                }
+                Trend::Down => {
+                    if candle.low < self.ep {
+                        self.ep = candle.low;
+                        self.af = (self.af + self.af_step).min(self.af_max);
+                    }
+                }
+            }
+        }
+
+        self.sar = output_sar;
+        self.prev_high = candle.high;
+        self.prev_low = candle.low;
+        Some(output_sar)
+    }
+
+    fn reset(&mut self) {
+        self.initialised = false;
+        self.af = self.af_start;
+        self.sar = 0.0;
+        self.ep = 0.0;
+    }
+
+    fn warmup_period(&self) -> usize {
+        2
+    }
+
+    fn is_ready(&self) -> bool {
+        self.initialised
+    }
+
+    fn name(&self) -> &'static str {
+        "PSAR"
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::traits::BatchExt;
+
+    fn c(h: f64, l: f64, cl: f64) -> Candle {
+        Candle::new(cl, h, l, cl, 1.0, 0).unwrap()
+    }
+
+    #[test]
+    fn first_candle_returns_none() {
+        let mut psar = Psar::classic();
+        assert_eq!(psar.update(c(11.0, 9.0, 10.0)), None);
+    }
+
+    #[test]
+    fn pure_uptrend_sar_below_lows() {
+        let candles: Vec<Candle> = (0..40)
+            .map(|i| {
+                let base = 100.0 + f64::from(i);
+                c(base + 0.5, base - 0.5, base)
+            })
+            .collect();
+        let mut psar = Psar::classic();
+        for (i, sar) in psar.batch(&candles).into_iter().enumerate() {
+            if let Some(s) = sar {
+                assert!(
+                    s <= candles[i].low + 1e-9,
+                    "SAR {s} should be <= low {} at i={i}",
+                    candles[i].low
+                );
+            }
+        }
+    }
+
+    #[test]
+    fn pure_downtrend_sar_above_highs() {
+        let candles: Vec<Candle> = (0..40)
+            .rev()
+            .map(|i| {
+                let base = 100.0 + f64::from(i);
+                c(base + 0.5, base - 0.5, base)
+            })
+            .collect();
+        let mut psar = Psar::classic();
+        let outs = psar.batch(&candles);
+        // After the trend establishes downward, SAR should sit above highs.
+        for (i, sar) in outs.into_iter().enumerate().skip(5) {
+            if let Some(s) = sar {
+                assert!(s >= candles[i].high - 1e-9);
+            }
+        }
+    }
+
+    #[test]
+    fn batch_equals_streaming() {
+        let candles: Vec<Candle> = (0..60)
+            .map(|i| {
+                let m = 100.0 + (f64::from(i) * 0.3).sin() * 8.0;
+                c(m + 1.0, m - 1.0, m)
+            })
+            .collect();
+        let mut a = Psar::classic();
+        let mut b = Psar::classic();
+        assert_eq!(
+            a.batch(&candles),
+            candles.iter().map(|x| b.update(*x)).collect::<Vec<_>>()
+        );
+    }
+
+    #[test]
+    fn rejects_invalid_params() {
+        assert!(Psar::new(0.0, 0.02, 0.20).is_err());
+        assert!(Psar::new(0.02, 0.0, 0.20).is_err());
+        assert!(Psar::new(0.30, 0.02, 0.20).is_err());
+        assert!(Psar::new(f64::NAN, 0.02, 0.20).is_err());
+    }
+}