## Summary
- Dedicated batch fast paths for **EMA, RSI, Bollinger, MACD and ATR** (used by the Python bindings): one allocation filled in a single pass, warmup encoded as `NaN`, no per-element `Option` or input re-validation. Each is **bit-for-bit equal** to replaying `update` — SMA/Bollinger keep the drift-reseed cadence, the EMA-family keep the seed division and `mul_add` recurrences. Adds the `BatchNanExt` extension trait.
- **Cross-library benchmark refresh**: `compare_libraries.py` reports the median across timing rounds (`--rounds` / `--streaming-rounds`), gains `--skip-batch` / `--skip-streaming`, and runs every peer through the streaming arena (recompute for batch-only libraries). `wickra-bench` drives the batch fast paths against `kand`.
- **README** benchmark section reordered streaming-first (the order-of-magnitude result), with measured TA-Lib/tulipy/pandas-ta numbers in place of the CI-only placeholders.
## Impact
- Python batch ~2× faster on EMA/RSI/MACD/ATR; streaming path unchanged.
- The `batch == streaming` equivalence stays bit-exact.
## Verification
- `cargo fmt` · `cargo clippy --workspace --all-targets --all-features -- -D warnings` (clean)
- `cargo test --workspace --all-features` — 3782 unit + 420 doc tests pass
- Python `pytest` — streaming-vs-batch, known-values, input-validation, smoke pass
## Notes
- Node/WASM bindings keep their existing batch; the fast paths are Python-only for now.
* test(keltner): cover periods accessor + name metadata
Codecov flagged 6 lines (file at 95.23%): periods (68-70) + name (106-108).
* test(linreg): cover period accessor + name metadata
Codecov flagged 6 lines (file at 96.10%): period (92-94) + name (142-144).
* test(linreg_slope): cover period accessor + name metadata
Codecov flagged 6 lines (file at 95.91%): period (80-82) + name (125-127).
* test(macd): cover periods/value accessors + name metadata
Codecov flagged 6 lines (file at 95.45%): periods (81-83) + name (135-137).
* test(super_trend): cover params accessor + name metadata
Codecov flagged 6 lines (file at 96.36%): params (99-101) + name (176-178).
Only two doctests existed in wickra-core; none of the 25 indicator
types carried a runnable rustdoc example.
Add an "# Example" doctest to every public indicator type (all 26,
including RollingVwap): construct the indicator and stream 80 inputs
through update, asserting a value is produced. The candle-input
indicators build valid OHLCV candles inline. cargo test --doc
-p wickra-core now runs 28 doctests, all passing; fmt and clippy clean.
Adds the reset tests the audit named as missing (aroon, awesome
oscillator, donchian, keltner, williams_r, and both VWAP variants),
non-finite-input tests for every scalar indicator that guards is_finite
(WMA, RSI, MACD, Bollinger, KAMA), and naive-reference proptests for EMA,
RSI and ATR. 189 core tests pass.
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.
