* feat(core): add 3 trade-flow microstructure indicators
SignedVolume (per-trade size signed by aggressor), CumulativeVolumeDelta
(running signed-volume total), and TradeImbalance (rolling buy/sell volume
imbalance over a trade window). All consume the Trade type, with full unit
coverage. Extends the Microstructure family.
* feat(bindings): expose trade-flow microstructure indicators
Python, Node and WASM bindings for SignedVolume, CumulativeVolumeDelta and
TradeImbalance. Each takes a trade via update(price, size, is_buy); Python and
Node expose a batch over three parallel arrays, WASM exposes per-trade update.
Regenerates node index.d.ts/.js.
* test(bindings,fuzz,bench): cover trade-flow microstructure indicators
Python and Node: reference values, streaming-vs-batch, lifecycle/repr and input
validation (zero window, negative size, non-positive price, mismatched batch
lengths). New indicator_update_trade fuzz target. Synthetic trade-tape benches
(signed_volume cheapest, trade_imbalance windowed/expensive).
* docs: add trade-flow indicators + bump counter to 227
README Microstructure family row gains signed volume / CVD / trade imbalance and
the counter goes 224 -> 227; CHANGELOG records the trade-flow indicators.
* feat(core): add microstructure input types (OrderBook, Trade, TradeQuote)
New non-OHLCV value types for the order-book / trade-flow indicator family:
Level, OrderBook (sorted, uncrossed depth snapshot), Side, Trade (with
aggressor side), and TradeQuote (trade paired with prevailing mid). Each has a
validating constructor plus a new_unchecked hot-path constructor, with full
unit coverage. Adds InvalidOrderBook / InvalidTrade error variants.
* feat(core): add 5 order-book microstructure indicators
OrderBookImbalanceTop1/TopN/Full (signed depth imbalance), Microprice
(size-weighted fair value), and QuotedSpread (top-of-book spread in bps). All
consume the OrderBook snapshot type, emit f64, are stateless and ready after
the first snapshot, with full unit coverage. Registers a new Microstructure
family in the taxonomy.
* feat(bindings): expose order-book microstructure indicators
Python, Node, and WASM bindings for OrderBookImbalanceTop1/TopN/Full,
Microprice and QuotedSpread. Each takes a depth snapshot via four equal-length
(bid_px, bid_sz, ask_px, ask_sz) arrays. Python and Node expose a batch over a
list of snapshots; WASM exposes per-snapshot update (the streaming model that
fits a browser book feed). Regenerates node index.d.ts/.js and registers the
new InvalidOrderBook/InvalidTrade arms in the Python error mapping.
* test(bindings,fuzz): cover order-book microstructure indicators
Python: smoke, reference values, streaming-vs-batch, lifecycle/repr and input
validation (mismatched lengths, crossed book, misordered levels, zero levels)
for all five order-book indicators. Node: reference values, streaming-vs-batch,
and rejection cases. Adds an indicator_update_orderbook fuzz target driving
every order-book indicator over arbitrary (incl. degenerate) snapshots.
* bench(microstructure): synthetic order-book benchmarks
Add a bench_orderbook_input harness and synthesise a five-level book around
each candle close (no order-book dataset ships with the repo). Benches the
cheapest (top-of-book imbalance) and most-expensive (full-depth imbalance) plus
microprice, matching the curated cheapest/expensive-per-family approach.
* docs: add Microstructure family + bump indicator counter to 224
README gains the Microstructure family row (order-book imbalance, microprice,
quoted spread) and the indicator counter goes 219 -> 224 across seventeen
families; CHANGELOG records the new order-book indicators and value types.
* feat(family-16): add ValueArea + InitialBalance + OpeningRange
Opens family #16 (Market Profile) with the three OHLCV-compatible scalar /
multi-output indicators:
- ValueArea(period, bin_count, value_area_pct) -> {poc, vah, val}.
Rolling bin-approximation volume profile over the last `period`
candles. Each candle's volume is spread uniformly across [low, high];
POC is the bin with highest cumulative volume; the value area expands
symmetrically from POC and always absorbs the higher-volume neighbour
next, until `value_area_pct` (default 0.70) of total volume is
enclosed. Defaults (20, 50, 0.70).
- InitialBalance(period) -> {high, low}. Tracks session-opening high
and low over the first `period` bars, then locks. Default period = 12
(one-hour IB on 5-minute bars for US equities). Callers MUST invoke
reset() at every session boundary, otherwise IB stays fixed for the
lifetime of the instance.
- OpeningRange(period) -> {high, low, breakout_distance}. Same
lock-after-N-bars semantics as IB with a shorter default period
(6 = 30 min on 5-minute bars) and a third output that tracks
close - or_mid (positive above the range mid, negative below).
Histogram-output Market Profile variants (Volume Profile, VPVR,
Composite Profile) are deferred because they need a new histogram
output API layer rather than fixed-arity scalars. Tick-data-only
variants (TPO Profile, Single Print, Order Flow Delta, Cumulative
Delta, Volume-Weighted Open) are out of scope because `wickra-data`
does not currently expose tick / L2 data.
All four bindings (Rust core, Python, Node, WASM) ship the new
indicators with parity tests; benches added; fuzz target extended.
Counter 71 -> 74 across 8 -> 9 families. cargo check --workspace
--all-features green.
* fix(family-16): cover cold paths in InitialBalance + ValueArea
InitialBalance::value() public getter had no test covering the post-update
Some(...) branch — extended accessors_and_metadata to call value() after one
update. ValueArea single-print bar path (c.high == c.low) was unreachable in
existing tests since the only single-print test used a uniform 100-price
window which exits early via the span == 0 guard; added a mixed-window test
that triggers the c.high <= c.low branch directly. The (None, None) arm of
the expansion match was by-construction unreachable (the loop condition
already requires at least one neighbour) and has been folded into an
if/else.
Implements Family 10 (Ehlers / Cycle) end-to-end across Rust core,
Python / Node / WASM bindings, fuzz, tests, benches and docs. This
is an entirely new family covering John Ehlers' digital-signal-
processing school of cycle analytics — a strong differentiator
versus TA-Lib and pandas-ta, which ship only fragments.
Indicators:
- MAMA (Mesa Adaptive MA) — multi-output { mama, fama }
- FAMA (Following Adaptive MA) — scalar wrapper around MAMA's slow line
- Fisher Transform — Gaussian-normalising price transform
- Inverse Fisher Transform — bounded oscillator (tanh-based)
- SuperSmoother — 2-pole Butterworth lowpass
- Roofing Filter — high-pass + SuperSmoother bandpass
- Decycler — price minus 2-pole high-pass (lag-free trend)
- Decycler Oscillator — fast / slow Decycler difference (MACD-like)
- Hilbert Dominant Cycle — phase-derived period estimator [6, 50]
- Sine Wave Indicator — sin(phase) with 45° lead companion
- Adaptive Cycle Indicator — half-period driver for adaptive oscillators
- Center of Gravity Oscillator — weighted-mass momentum
- Cybernetic Cycle Component — EasyLanguage classic
- Empirical Mode Decomposition — bandpass + envelope mean
- Ehlers Stochastic — Stochastic on Roofing Filter input, [-1, +1]
- Instantaneous Trendline — Ehlers 2-pole lag-free trend
Indicator count rises 71 -> 87 across nine families (was eight).
All sixteen pass batch == streaming equivalence, expose the standard
Indicator surface (update / batch / reset / is_ready / warmup_period
/ name), are fuzz-tested, benchmarked against the checked-in BTCUSDT
1-minute dataset and reach across all four bindings.
Wiki deep-dive drafts for every indicator + Sidebar / Overview /
Home / Warmup updates are staged under indicator-ideas/families/
wiki/family-10-ehlers-cycle/ in the main repo (ghost-ignored) for
the maintainer to publish to the wiki repo manually.
The rolling-window VWAP indicator (`wickra_core::RollingVwap`) was only
available in the Rust crate, even though the README's Volume-family
table already advertised "VWAP (cumulative + rolling)" as a cross-
language feature. Users on Python, Node or in the browser had to fall
back to the cumulative `VWAP` or re-implement the rolling variant
themselves.
This commit closes the gap end-to-end:
- Python: `wickra.RollingVWAP(period)` — same constructor / `update` /
`batch` / `reset` / `is_ready` / `warmup_period` surface as `VWAP`,
plus a `period` property and a typed `__repr__`. The `__init__.py`
re-exports it and `__all__` lists it; the `.pyi` stub matches.
- Node: `RollingVWAP(period)` — napi class with the same lifecycle,
exported from `index.js` and declared in `index.d.ts`.
- WASM: `RollingVWAP(period)` — wasm-bindgen class with the same
`Float64Array` I/O as `VWAP`.
Tests added:
- Python: `test_rolling_vwap_streaming_matches_batch` — exercises
`update == batch` plus the full lifecycle on the shared OHLC fixture.
- Node: `RollingVWAP` row in the `candleScalar` parity table — covered
by the generic streaming-vs-batch + lifecycle harness.
- WASM: dedicated `wasm-bindgen-test` mirrors the Python test.
The wiki page `Indicator-Vwap.md` drops the "Rust-only" caveat and
gains Python / Node / WASM examples.
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.
kingchenc