* feat(alma): add Arnaud Legoux Moving Average
Gaussian-weighted moving average with configurable centre (offset in
[0, 1]) and kernel width (sigma > 0). Pre-computes normalised weights
at construction so each update is a single rolling window dot product.
Reference: Arnaud Legoux and Dimitrios Kouzis-Loukas, 2009.
Touchpoints:
- crates/wickra-core: alma.rs + mod.rs + lib.rs re-export
- bindings/python: PyAlma + __init__.py + test_new_indicators +
test_known_values reference
- bindings/node: AlmaNode + index.d.ts/index.js + indicators.test.js
factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers ALMA(9, 0.85, 6.0)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry
* feat(mcginley): add McGinley Dynamic moving average
John McGinley's self-adjusting moving average with the recurrence
MD + (price - MD) / (0.6 * period * (price / MD)^4). Speeds up when
price falls below the indicator and damps when price runs above the
indicator. Seeded with the simple average of the first period inputs.
Reference: McGinley, Technical Analysis of Stocks & Commodities, 1990.
Touchpoints:
- crates/wickra-core: mcginley_dynamic.rs + mod.rs + lib.rs re-export
- bindings/python: PyMcGinleyDynamic + __init__.py + test_new_indicators
+ test_known_values reference
- bindings/node: McGinleyDynamicNode (scalar macro) + index.d.ts/index.js
+ indicators.test.js factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers McGinleyDynamic(10)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry
* feat(frama): add Fractal Adaptive Moving Average
Ehlers' FRAMA adapts its smoothing constant to the fractal dimension of
the recent window: tight tracking in trends, heavy smoothing in chop.
Uses the close-only variant where max/min over each window half drive
the dimension estimate. Period must be even (default 16).
Reference: Ehlers, Fractal Adaptive Moving Average, 2005.
Touchpoints:
- crates/wickra-core: frama.rs + mod.rs + lib.rs re-export
- bindings/python: PyFrama + __init__.py + test_new_indicators +
test_known_values reference (constant series + uptrend tracking)
- bindings/node: FramaNode (scalar macro) + index.d.ts/index.js +
indicators.test.js factory + reference value
- bindings/wasm: wasm_scalar_indicator! macro
- fuzz: indicator_update target covers Frama(16)
- crates/wickra/benches: bench_scalar entry
- README + CHANGELOG: Moving Averages row + Unreleased entry
* feat(vidya): add Variable Index Dynamic Average
Chande's VIDYA — an EMA whose alpha scales with |CMO(cmo_period)| / 100.
Strong directional momentum lifts the smoothing constant toward the
EMA-of-period rate; flat or choppy windows shrink it toward zero so
VIDYA coasts on its previous value. Two parameters: period (14) and
cmo_period (9). Reuses the existing wickra-core Cmo internally.
Reference: Chande, Stocks & Commodities, 1992.
Also fixes a silent gap from d37fbd1 (feat(frama)): the PyFrama Python
class wrapper and its add_class registration were dropped because the
two edits hit "File has not been read yet" errors that scrolled past
in a batch. Adds them here alongside VIDYA's bindings.
Touchpoints (VIDYA): vidya.rs + mod.rs + lib.rs re-export, PyVidya +
__init__.py + test_new_indicators + test_known_values reference,
VidyaNode (manual two-param binding) + index.d.ts/index.js +
indicators.test.js factory + reference, wasm_scalar_indicator! macro,
fuzz target, bench, README + CHANGELOG.
* feat(jma): add Jurik Moving Average
Three-stage filter reconstruction of Mark Jurik's adaptive MA (the
algorithm is proprietary; this is the form used by most open-source
ports since the 1999 TASC article). Parameters: period (14), phase in
[-100, 100] (0), power in 1..=4 (2). State is seeded by setting
e0 = JMA = first input so a constant input stream is reproduced exactly.
Touchpoints: jma.rs + mod.rs + lib.rs re-export, PyJma + __init__.py +
test_new_indicators + test_known_values reference, JmaNode (manual
three-param binding) + index.d.ts/index.js + indicators.test.js factory
+ reference, wasm_scalar_indicator! macro, fuzz target, bench, README +
CHANGELOG.
* feat(alligator): add Bill Williams Alligator
Three SMMA lines (Jaw / Teeth / Lips) over the median price
(high + low) / 2 with default periods 13 / 8 / 5. Multi-output
indicator returning AlligatorOutput { jaw, teeth, lips }. The
original chart variant shifts each line forward for display; we
publish the unshifted SMMA values and leave the visual shift to
the consumer.
Reference: Bill Williams, Trading Chaos, 1995.
Touchpoints: alligator.rs + mod.rs + lib.rs re-export, PyAlligator
(Candle input, returns 3-tuple, ndarray (n, 3) batch) + __init__.py
+ test_new_indicators + test_known_values reference, AlligatorNode +
AlligatorValue + index.d.ts/index.js + indicators.test.js multi
factory + reference, WasmAlligator (manual JsValue object) +
candle-fuzz target + README + CHANGELOG.
* feat(evwma): add Elastic Volume-Weighted Moving Average
Christian P. Fries' elastic recurrence where the smoothing weight is the
bar's volume relative to the running window total:
V_sum_t = sum of volumes over the last period candles
EVWMA_t = ((V_sum_t - v_t) * EVWMA_{t-1} + v_t * close_t) / V_sum_t
A bar whose volume is small barely moves the average; a bar that
dominates the window pulls it strongly toward that bar's close. Seeded
with the close of the first full window; holds its previous value if
the entire window has zero volume.
Reference: Fries, Wilmott Magazine, 2001.
Touchpoints: evwma.rs + mod.rs + lib.rs re-export, PyEvwma (close +
volume batch) + __init__.py + test_new_indicators CANDLE_SCALAR +
test_known_values reference, EvwmaNode + index.d.ts/index.js +
indicators.test.js candleScalar factory + reference, WasmEvwma,
candle-fuzz target + README + CHANGELOG.
* ci: Force local wheel install in Python jobs
Use --no-index --no-deps so the Python matrix installs the freshly
built wheel from dist/ and never falls back to PyPI. Previously pip
sometimes picked the released 0.2.x wheel on macOS / Windows when its
platform tag was a wider match than the local build, which made the
job test the released package and miss any new symbols added in the
PR (e.g. AttributeError: module 'wickra' has no attribute 'ALMA').
numpy is already installed by the preceding pip step, so --no-deps
is safe.
450 lines
25 KiB
Markdown
450 lines
25 KiB
Markdown
# Changelog
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All notable changes to Wickra are documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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### Added
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- **Family 01 — Moving Averages.** `ALMA` (Arnaud Legoux Moving Average):
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Gaussian-weighted moving average with configurable centre (`offset` in
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`[0, 1]`) and kernel width (`sigma > 0`). Community-standard defaults
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`(period = 9, offset = 0.85, sigma = 6.0)` available via `Alma::classic()`.
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Exposed in all four bindings (Rust, Python, Node, WASM).
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- **Family 01 — Moving Averages.** `EVWMA` (Elastic Volume-Weighted
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Moving Average, Fries 2001): an "elastic" recurrence whose smoothing
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weight is the bar's volume relative to the running window-volume.
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Candle input (uses close + volume), single parameter `period`
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(default 20). Holds its previous value if the entire window has zero
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volume. Exposed in all four bindings.
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- **Family 01 — Moving Averages.** `Alligator` (Bill Williams): three
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SMMA lines (Jaw / Teeth / Lips) of the median price `(high + low) / 2`
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with default periods 13 / 8 / 5. Multi-output indicator emitting
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`AlligatorOutput { jaw, teeth, lips }`. Visual chart shift is left to
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the consumer. Exposed in all four bindings.
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- **Family 01 — Moving Averages.** `JMA` (Jurik Moving Average):
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three-stage filter reconstruction of Mark Jurik's adaptive MA.
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Three parameters: `period` (14), `phase` in `[-100, 100]` (0), `power`
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in `1..=4` (2). State is seeded to the first input so a constant series
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is reproduced exactly. Exposed in all four bindings.
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- **Family 01 — Moving Averages.** `VIDYA` (Variable Index Dynamic
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Average, Chande 1992): EMA whose smoothing factor is scaled by the
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absolute Chande Momentum Oscillator. Two parameters `period` and
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`cmo_period` (defaults 14 / 9). Exposed in all four bindings.
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- **Family 01 — Moving Averages.** `FRAMA` (Fractal Adaptive Moving
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Average, Ehlers 2005): adapts its smoothing constant to the fractal
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dimension of the recent window — fast in trends, slow in chop. Single
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parameter `period` (must be even, default 16). Exposed in all four
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bindings.
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- **Family 01 — Moving Averages.** `McGinleyDynamic`: John McGinley's
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self-adjusting MA. Single parameter `period`; the recurrence
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`MD + (price - MD) / (0.6 * period * (price / MD)^4)` speeds up when price
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falls below the indicator and damps when price runs above. Seeded with the
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simple average of the first `period` inputs. Exposed in all four bindings.
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## [0.2.7] - 2026-05-24
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### Added
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- **Windows ARM64 is back.** npm Support unblocked the
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`wickra-win32-arm64-msvc` sub-package name (same path
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`wickra-win32-x64-msvc` took through 0.1.4) and transferred write
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access to @kingchenc. 0.2.7 ships the binding for
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`aarch64-pc-windows-msvc` alongside the existing five platforms:
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the `napi.triples.additional` entry, the `optionalDependencies`
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pin, the `bindings/node/npm/win32-arm64-msvc/` sub-package and the
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`windows-11-arm` row of the release.yml node-build matrix are all
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restored from 8aa74cb. `npm install wickra` on Windows ARM64 now
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resolves to a native build instead of failing the loader's
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optional-dep lookup. PyPI's `win_arm64` wheel was unaffected and
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carries through as before.
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### Changed
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- **Benchmark CPU renamed.** The "Reproduced on" line in every
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README listed an AMD Ryzen 9 7950X3D; the canonical machine is
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actually a Ryzen 9 9950X. Speedup ratios in the tables are
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unchanged (they're relative across libraries on the same machine),
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only the labelling is corrected. The performance-regression issue
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template's CPU example was updated for consistency.
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## [0.2.6] - 2026-05-24
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### Fixed
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- **docs.rs build.** Rust 1.92 removed the `doc_auto_cfg` feature gate
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and folded it back into `doc_cfg` (rust-lang/rust#138907). docs.rs
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builds against the latest nightly and sets `--cfg docsrs`, so every
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published 0.2.x failed with E0557 on the
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`#![cfg_attr(docsrs, feature(doc_auto_cfg))]` line at the top of
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`wickra`, `wickra-core`, and `wickra-data`. GitHub CI didn't see
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this — stable rustc never enables the `docsrs` cfg. The three
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library crates now gate on `doc_cfg` (same intent, same rendered
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output on docs.rs, builds again on nightly).
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### Changed
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- **README — Wickra is now the top row of every comparison table.**
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The "Why Wickra exists" library matrix and the per-indicator
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benchmark tables previously placed Wickra at the bottom; a reader
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landing on the README is here to compare *against* Wickra, so the
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pivot row belongs at the top with a ★ marker. Same column data,
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same winner annotations — only row order changed. Mirrored across
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the umbrella README and every binding README so crates.io / PyPI /
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npm landing pages stay in sync.
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## [0.2.5] - 2026-05-24
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### Added
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- `BinanceConfig` plus `BinanceKlineStream::connect_with_config(symbols, interval, config)`
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in `wickra-data`'s `live::binance` module. `connect()` keeps its previous
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signature and now forwards to the new entry-point with the defaults, so the
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public API is backwards-compatible. The config lets callers point the
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stream at Binance Testnet (`wss://testnet.binance.vision`) or tune the
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read timeout, reconnect attempt count, initial / capped backoff and frame
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size limits without rewriting the connector.
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- README **Disclaimer** section clarifying that Wickra is an indicator
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toolkit (not a trading system) and that any production-trading use is at
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the caller's own risk. The legal terms in [LICENSE](LICENSE) are
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unchanged.
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### Changed
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- `BinanceKlineStream::next_event` now writes the Pong reply to a server
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`Ping` on a best-effort basis. A failed write means the connection is
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already dead, so the existing timeout / read-error reconnect arm one
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loop iteration later picks it up — the previous explicit reconnect on
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Pong-write failure is gone. Observable behaviour is unchanged for every
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healthy connection.
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## [0.2.1] - 2026-05-23
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### Changed
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- **MSRV bumped.** Workspace minimum supported Rust version is now **1.86**
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(was 1.75) and the Node binding (`wickra-node`) is now **1.88** (was 1.77).
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The bumps are driven by transitive-dependency floors that were lifted in
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recent updates: `criterion 0.8.2` (the bench dev-dep) requires Rust 1.86,
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and `napi-build >= 2.3.2` requires Rust 1.88. Pinning those deps to the
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older versions would have frozen us out of future security fixes from
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those upstreams, so lifting the MSRV is the cleaner path for a young 0.x
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library. Downstream consumers on older Rust toolchains can stay on
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Wickra 0.2.0.
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- Bumped the bench dev-dep `criterion` from 0.5 to 0.8 and migrated
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`bindings/wickra/benches/indicators.rs` from the deprecated
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`criterion::black_box` re-export to the stable `std::hint::black_box`.
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- Bumped `tokio-tungstenite` from 0.24 to 0.29. `WebSocketConfig` became
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`#[non_exhaustive]` upstream, so the struct-literal construction in
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`crates/wickra-data/src/live/binance.rs` is rewritten to the
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builder-style `WebSocketConfig::default().max_message_size(..).max_frame_size(..)`.
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Same caps, same semantics, same default carry-over.
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- Bumped every committed CI/release GitHub Action to its latest pinned
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SHA: `actions/checkout` 4 → 6, `actions/setup-node` 4 → 6,
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`actions/setup-python` 5 → 6, `actions/upload-artifact` 4 → 7,
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`actions/download-artifact` 4 → 8, `softprops/action-gh-release` 2 → 3,
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`codecov/codecov-action` 5 → 6, `taiki-e/install-action` patch.
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### Fixed
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- `tick_aggregator` gap-fill no longer allocates an unbounded number of
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placeholder candles. The new `MAX_GAP_FILL_CANDLES = 1_000_000` cap
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surfaces an adversarial timestamp jump (e.g. a clock-glitch tick years
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in the future) as `Error::Malformed` instead of an OOM panic. Found by
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the new `tick_aggregator` fuzz target.
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- `HistoricalVolatility::geometric_series_yields_zero` now uses an `1e-6`
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tolerance instead of `1e-9`. The mathematical result on a perfectly
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geometric price series is exactly zero, but the underlying
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`1.01_f64.powi(i)` + log-return + std-dev cascade accumulates
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platform-sensitive FP drift on the order of 1e-7 on x86_64 Linux and
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macOS. The widened tolerance stays four decimal places below any
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realistic annualised volatility value while absorbing the drift across
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every supported platform.
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- Replaced every `(high + low) / 2.0` test-helper and three real call
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sites (`Ohlcv::median_price`, `Donchian.middle`, `EaseOfMovement.mid`,
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`SuperTrend.hl2`) with `f64::midpoint(high, low)`. The change satisfies
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clippy 1.95's new `manual_midpoint` lint without affecting values
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(`f64::midpoint` matches the naive average to better than 1 ULP for the
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inputs used here).
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- Replaced `i.is_multiple_of(2)` (unstable on Rust 1.85) with `i % 2 == 0`
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in the SMA / Bollinger long-stream-drift tests so the workspace MSRV
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job builds cleanly on Rust 1.86.
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- The `Compile examples` CI step now invokes
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`cargo build -p wickra-examples --bins` instead of the now-deleted
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`cargo build -p wickra --example backtest` / `-p wickra-data --example
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live_binance` (the Z5 reorganisation moved every runnable example into
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the dedicated `wickra-examples` crate, but the CI step had not been
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updated).
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- The `Fuzz (smoke)` CI job installs `cargo-fuzz` from a prebuilt binary
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via `taiki-e/install-action` instead of `cargo install cargo-fuzz`.
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The source install resolved against `rustix 0.36.5`, which uses
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internal `#[rustc_*]` attributes the current nightly compiler rejects.
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- The fuzz targets now build with an explicit
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`--target x86_64-unknown-linux-gnu`; cargo-fuzz was defaulting to
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`x86_64-unknown-linux-musl`, which is not installed on the standard
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GitHub-hosted Ubuntu runner.
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### Removed
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- **`wickra-win32-arm64-msvc` is temporarily omitted from this release.**
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The npm spam-detection filter blocks the first publish of this brand-new
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package name (same situation that affected `wickra-win32-x64-msvc`
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through 0.1.4 until npm Support unblocked it). A support ticket is open;
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once the new name is unblocked the
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`aarch64-pc-windows-msvc` triple will be restored in
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`bindings/node/package.json` (`napi.triples.additional` +
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`optionalDependencies`), in the `release.yml` `node-build` matrix, and
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as a fresh `bindings/node/npm/win32-arm64-msvc/` template. Until then,
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`npm install wickra@0.2.1` on Windows ARM64 will surface the loader's
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standard `Cannot find module 'wickra-win32-arm64-msvc'` error; every
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other platform (Linux x64 / Linux ARM64 / macOS x64 / macOS ARM64 /
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Windows x64) ships normally. The PyPI wheel for Windows ARM64 is
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unaffected and still published.
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## [0.2.0] - 2026-05-23
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### Fixed
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- `HistoricalVolatility::update` no longer substitutes a `0.0` log-return on
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non-positive prices (audit finding R13). Negative or zero prices are
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semantically invalid for a log-return calculation; silently treating them as
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"no movement" underreported realised volatility. They are now skipped — the
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previous valid value is returned and the indicator's state (`prev_price`,
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window, sums) is left untouched — matching how every other indicator handles
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invalid inputs.
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- `Tick::new` now returns the new `Error::InvalidTick` variant for negative
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volume instead of `Error::InvalidCandle` (audit finding R14). A tick is not
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a candle, and downstream tick-stream pipelines should be able to match on a
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semantically-correct error. The Python binding's `map_err` was extended to
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forward the new variant as a `ValueError`; the Node and WASM bindings format
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via `Error::to_string()` and pick the new variant up automatically.
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- `Psar::is_ready` now matches the convention shared by every other indicator:
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`is_ready() == true` iff a real value has been produced (audit finding R6).
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The previous implementation returned `self.initialised`, which flipped to
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`true` after the seed candle even though the seed candle itself returns
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`None`. A streaming consumer that wrote
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`if ind.is_ready() { use(ind.update(c)?) }` would hit an unexpected `None`
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on the first post-seed update. The fix introduces a `has_emitted` gate set
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when the first `Some` value is returned.
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- `Psar::reset` now restores the compute fields (`prev_high`, `prev_low`,
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`sar`, `ep`) to `f64::NAN` sentinels instead of `0.0` (audit Opus-Bonus 1).
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The fields are gated by `initialised` today, so the `0.0` sentinel never
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leaked into output — but a future refactor that read them pre-init would
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have silently treated `0.0` as a real price. A `debug_assert!` at the read
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site makes the invariant explicit.
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### Changed
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- `Sma` and `BollingerBands` now reseed their incremental `sum` (and `sum_sq`
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for Bollinger) from the live window every `16 · period` finite updates,
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capping floating-point drift on long-running streams (audit findings R7 and
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L2-Rust). Previously the incremental single-subtract `sum -= old` could
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accumulate catastrophic-cancellation error on streams with alternating
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large/small magnitudes; the misleading `sma.rs` comment that claimed the
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drift was already bounded "by recomputing the sum after each pop" is
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replaced with an accurate description of the new reseed strategy. Amortised
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cost stays at O(1) (`O(period)` work amortised over `O(period)` updates),
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values are bit-identical on inputs that did not drift to begin with, and
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two new `long_stream_drift_stays_bounded` tests stress the recompute by
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alternating `1e9` / `1.0` (SMA) and `1e6` / `1.0` (Bollinger) for several
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recompute cycles and verify the reported values track a fresh from-scratch
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computation over the live window.
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- `LinearRegression`, `LinRegSlope` and `LinRegAngle` (via composition over
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`LinRegSlope`) now run their rolling ordinary-least-squares fit
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**incrementally** in O(1) per update (audit finding R2). Previously every
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tick refit the line from scratch in O(period). The OLS denominators (`Σx`
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and `Σxx`) depend only on `period`, so they were already precomputed; this
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release adds running `Σy` and `Σxy` accumulators and slides them in closed
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form via the identity
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`new_Σxy = old_Σxy − old_Σy + popped_y₀` (then `Σxy += (n − 1) · new_value`
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and `Σy += new_value`). New per-bar equivalence tests compare the O(1)
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output against a fresh O(n) refit on noisy ramps, step functions, and
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constants — values agree to within 1e-9.
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- Fuzz suite expanded from 2 indicators to the full catalogue (audit finding
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R9). The existing `indicator_update` target now exercises every scalar-input
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indicator (~33 classes including MACD and Bollinger Bands); a new
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`indicator_update_candle` target exercises every candle-input indicator (~37
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classes, including ATR, ADX, Stochastic, PSAR, Keltner, SuperTrend,
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ChandelierExit, AwesomeOscillator, OBV, MFI, VWAP, RollingVWAP, and the rest
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of the volume / volatility / trailing-stop / price-statistics families). Each
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iteration sweeps every indicator through both the streaming `update` loop
|
||
and a full `batch` call so any state-mutation bug surfaces on either path.
|
||
CI gains a `fuzz-smoke` job that runs each of the five targets for 30 s on
|
||
every push and pull-request.
|
||
- `UlcerIndex::update` now tracks the trailing maximum with a monotonically-
|
||
decreasing deque of `(index, price)` pairs instead of scanning the whole
|
||
trailing window on every tick. The indicator now honours the `Indicator`
|
||
trait's O(1)-per-tick contract; values and warmup semantics are unchanged
|
||
(verified by a new adversarial-input test that compares the deque output
|
||
bar-by-bar against a naive O(n) trailing-max scan on strictly increasing,
|
||
strictly decreasing, constant, and sawtooth inputs). The doc comment on
|
||
`warmup_period()` is also corrected: the two windows overlap by one bar, so
|
||
the formula is `2 * period - 1`.
|
||
|
||
### Added
|
||
- `RollingVWAP` is now exposed in Python, Node and WASM under that name
|
||
(previously the rolling-window VWAP existed only in the Rust core, even
|
||
though the README's volume-family table already advertised
|
||
`VWAP (cumulative + rolling)`). All four bindings now ship the same
|
||
cumulative `VWAP` plus the finite-window `RollingVWAP(period)`. The wiki page
|
||
`Indicator-Vwap.md` adds Python, Node and WASM examples and drops the
|
||
"Rust-only" caveat.
|
||
- WASM binding now exposes the streaming `update()` method on every candle-input
|
||
indicator: `Adx`, `WilliamsR`, `Cci`, `Mfi`, `Psar`, `Keltner`, `Donchian`,
|
||
`Vwap`, `AwesomeOscillator`, `Aroon`, `Stochastic`, and `Obv`. Multi-output
|
||
indicators (`Adx`, `Keltner`, `Donchian`, `Aroon`, `Stochastic`) return a
|
||
named JS object (`{ plusDi, minusDi, adx }`, `{ upper, middle, lower }`,
|
||
`{ up, down }`, `{ k, d }`) once warm, or `null` during warmup — matching the
|
||
existing `SuperTrend` convention. Each class also gains `reset()`, `isReady()`
|
||
and `warmupPeriod()`, bringing the WASM surface to full parity with Python
|
||
and Node so browser-side streaming code no longer has to replay `batch()`
|
||
on every tick. `WasmKama` gains the previously missing `warmupPeriod()`.
|
||
- New `wasm-bindgen` integration test exercises `update == batch` plus the full
|
||
lifecycle (`reset` / `isReady` / `warmupPeriod`) for all twelve newly wired
|
||
classes against a deterministic 40-bar synthetic OHLCV stream.
|
||
|
||
### Security
|
||
- Upgrade `pyo3` (0.22 → 0.28) and `numpy` (0.22 → 0.28) in the Python binding.
|
||
Fixes [RUSTSEC-2025-0020](https://rustsec.org/advisories/RUSTSEC-2025-0020) —
|
||
a buffer overflow in `PyString::from_object` that affected the published
|
||
Python wheels. The `cargo-deny` ignore entry that previously suppressed the
|
||
advisory has been removed; `cargo deny check` is now clean without
|
||
suppression. Migrated `into_pyarray_bound` to `into_pyarray`,
|
||
`downcast::<PyDict>` to `cast::<PyDict>`, and opted every `#[pyclass]` out of
|
||
the deprecated automatic `FromPyObject` derive via `skip_from_py_object`.
|
||
|
||
### Added
|
||
- 46 new technical indicators, taking the library from 25 to 71 and
|
||
reorganising the catalogue into **eight families**, each with at least five
|
||
members. Every indicator is implemented once in the Rust core and wired
|
||
through the Python, Node and WASM bindings, with reference-value tests and a
|
||
dedicated wiki page:
|
||
- Moving Averages: `Smma`, `Trima`, `Zlema`, `T3`, `Vwma`.
|
||
- Momentum Oscillators: `Mom`, `Cmo`, `Tsi`, `Pmo`, `StochRsi`,
|
||
`UltimateOscillator`.
|
||
- Trend & Directional: `AroonOscillator`, `Vortex`, `MassIndex`,
|
||
`ChoppinessIndex`, `VerticalHorizontalFilter`.
|
||
- Price Oscillators: `Ppo`, `Dpo`, `Coppock`, `AcceleratorOscillator`,
|
||
`BalanceOfPower`.
|
||
- Volatility & Bands: `Natr`, `StdDev`, `UlcerIndex`,
|
||
`HistoricalVolatility`, `BollingerBandwidth`, `PercentB`, `TrueRange`,
|
||
`ChaikinVolatility`.
|
||
- Trailing Stops: `SuperTrend`, `ChandelierExit`, `ChandeKrollStop`,
|
||
`AtrTrailingStop`.
|
||
- Volume: `Adl`, `VolumePriceTrend`, `ChaikinMoneyFlow`,
|
||
`ChaikinOscillator`, `ForceIndex`, `EaseOfMovement`.
|
||
- Price Statistics: `TypicalPrice`, `MedianPrice`, `WeightedClose`,
|
||
`LinearRegression`, `LinRegSlope`, `ZScore`, `LinRegAngle`.
|
||
- `TickAggregator::with_gap_fill` — opt-in mode that emits a flat placeholder
|
||
candle for every empty bucket between two ticks, keeping the candle series
|
||
evenly spaced for downstream indicators.
|
||
- CSV reader: a leading UTF-8 byte-order mark is stripped, fields are trimmed,
|
||
and the header is validated against the required OHLCV columns.
|
||
- CI: an `msrv` job that builds and tests the workspace on Rust 1.75 and the
|
||
node binding on Rust 1.77.
|
||
- Community health files: `CONTRIBUTING.md`, `SECURITY.md`,
|
||
`CODE_OF_CONDUCT.md`, issue / pull-request templates, `CODEOWNERS`, and a
|
||
Dependabot configuration.
|
||
- Seven example OHLCV datasets under `examples/data/`, one per timeframe
|
||
(1m / 5m / 15m / 1h / 12h / 1d / 1month), holding real BTCUSDT spot klines,
|
||
alongside the `fetch_btcusdt` example that regenerates them from the
|
||
Binance REST API.
|
||
- `Timeframe::minutes`, `Timeframe::hours` and `Timeframe::days` convenience
|
||
constructors, each building on seconds with a checked-multiplication
|
||
overflow guard.
|
||
|
||
### Changed
|
||
- The indicator wiki is reorganised into eight family folders under
|
||
`docs/wiki/indicators/` (`moving-averages/`, `momentum-oscillators/`,
|
||
`trend-directional/`, `price-oscillators/`, `volatility-bands/`,
|
||
`trailing-stops/`, `volume/`, `price-statistics/`); `Indicators-Overview.md`,
|
||
`Home.md` and the README indicator table follow the same eight families.
|
||
- `TickAggregator::push` returns `Result<Vec<Candle>>` (was
|
||
`Result<Option<Candle>>`) so a single tick can yield a closed bar plus gap
|
||
fillers.
|
||
- `Resampler::push` returns `Result<Option<Candle>>`: a candle in a bucket
|
||
earlier than the open bar is now rejected as out of order.
|
||
- Aggregated candles are finalised through the validating `Candle::new`, so a
|
||
volume that overflows to a non-finite value is surfaced as an error instead
|
||
of producing a poisoned candle.
|
||
- All GitHub Actions are pinned to commit SHAs; the four publish jobs run in a
|
||
protected `release` environment.
|
||
- The indicator benchmarks (`crates/wickra/benches/indicators.rs`) now run
|
||
against the checked-in real BTCUSDT 1-minute dataset instead of a synthetic
|
||
price series.
|
||
- Every language's examples now live under a uniform `examples/<lang>/`
|
||
tree: Rust moved into a new `examples/rust/` workspace member crate
|
||
(`wickra-examples`, run via `cargo run -p wickra-examples --bin <name>`),
|
||
Node into `examples/node/` with its own `package.json` linking `wickra` via
|
||
`file:../../bindings/node`, and the WASM browser demos into
|
||
`examples/wasm/`. The bundled BTCUSDT datasets move alongside them at
|
||
`examples/data/`. Six new examples close the cross-language parity matrix:
|
||
streaming demos for Python and Rust; multi-timeframe and parallel-assets
|
||
demos for both Rust and Node.
|
||
- Cross-language data-generator parity: `examples/python/fetch_btcusdt.py`
|
||
(stdlib only: `urllib` + `json` + `csv`) and `examples/node/fetch_btcusdt.js`
|
||
(Node 18+ built-in `fetch`) mirror the Rust `fetch_btcusdt` binary —
|
||
byte-for-byte identical CSV output on the same Binance snapshot.
|
||
- Four additional WebAssembly browser demos under `examples/wasm/`
|
||
alongside the original `index.html`: `backtest.html` (fetch + basket of
|
||
indicators), `live_trading.html` (browser-native `WebSocket` to
|
||
Binance), `multi_timeframe.html` (in-page resample) and
|
||
`parallel_assets.html` + `parallel_worker.js` (module-Worker pool with
|
||
serial-vs-parallel speedup). The cross-language matrix is now closed
|
||
for every cell where the pattern makes sense.
|
||
- Three new wiki pages: `TA-Lib-Migration.md` (full mapping table from
|
||
`talib.X(...)` calls to Wickra), `Cookbook.md` (seven concrete
|
||
strategy recipes — RSI mean reversion, MACD crossover, Bollinger
|
||
breakout, ADX-gated trend, multi-timeframe confirmation, SuperTrend,
|
||
chained indicators) and `FAQ.md`. All three linked from `Home.md`.
|
||
|
||
### Fixed
|
||
- `Timeframe::floor` no longer overflows for timestamps near `i64::MIN`.
|
||
- The aggregator rejects same-bucket ticks that arrive out of order instead of
|
||
silently overwriting the bar's close with a stale price.
|
||
- The Binance live stream reconnects with exponential backoff, skips non-kline
|
||
frames, applies a read timeout and message-size limits, and tracks a closed
|
||
flag.
|
||
- Example scripts: `live_trading.py` skips non-kline frames and validates the
|
||
symbol/interval; `backtest.py` and `multi_timeframe.py` report clear errors
|
||
for malformed CSV input.
|
||
|
||
## [0.1.4] - 2026-05-21
|
||
|
||
### Added
|
||
- GitHub Release runs now attach every built artefact (wheels, sdist, native
|
||
Node binaries, npm-pack tarballs, cargo `.crate` files) to the tag's
|
||
release page.
|
||
|
||
## [0.1.3] - 2026-05-21
|
||
|
||
### Fixed
|
||
- npm package ships the napi-generated loader and is built with `--platform`
|
||
so the per-platform binary is resolved correctly.
|
||
|
||
## [0.1.2] - 2026-05-21
|
||
|
||
### Fixed
|
||
- Release pipeline: per-platform idempotent npm publishing with a spam-filter
|
||
retry, and committed `npm/<platform>/` package templates.
|
||
|
||
## [0.1.1] - 2026-05-21
|
||
|
||
### Fixed
|
||
- Node publish step and coordinated version bump across all bindings.
|
||
|
||
## [0.1.0] - 2026-05-21
|
||
|
||
### Added
|
||
- Initial release: a streaming-first technical-analysis library with 25
|
||
indicators (SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, RSI, MACD, ROC, Stochastic,
|
||
CCI, Williams %R, ADX, MFI, TRIX, Aroon, Awesome Oscillator, Bollinger Bands,
|
||
ATR, Keltner Channels, Donchian Channels, Parabolic SAR, OBV, VWAP).
|
||
- Rust core (`wickra-core`), umbrella crate (`wickra`), and a data layer
|
||
(`wickra-data`) with a CSV reader, tick aggregator, resampler, and an
|
||
optional Binance live feed.
|
||
- Bindings for Python, Node.js, and WebAssembly.
|
||
|
||
[Unreleased]: https://github.com/kingchenc/wickra/compare/v0.2.7...HEAD
|
||
[0.2.7]: https://github.com/kingchenc/wickra/compare/v0.2.6...v0.2.7
|
||
[0.2.6]: https://github.com/kingchenc/wickra/compare/v0.2.5...v0.2.6
|
||
[0.2.5]: https://github.com/kingchenc/wickra/compare/v0.2.1...v0.2.5
|
||
[0.2.1]: https://github.com/kingchenc/wickra/compare/v0.2.0...v0.2.1
|
||
[0.2.0]: https://github.com/kingchenc/wickra/compare/v0.1.4...v0.2.0
|
||
[0.1.4]: https://github.com/kingchenc/wickra/compare/v0.1.3...v0.1.4
|
||
[0.1.3]: https://github.com/kingchenc/wickra/compare/v0.1.2...v0.1.3
|
||
[0.1.2]: https://github.com/kingchenc/wickra/compare/v0.1.1...v0.1.2
|
||
[0.1.1]: https://github.com/kingchenc/wickra/compare/v0.1.0...v0.1.1
|
||
[0.1.0]: https://github.com/kingchenc/wickra/releases/tag/v0.1.0
|