* feat(rvi): add Relative Vigor Index
Dorsey's RVI = SMA(close - open, period) / SMA(high - low, period) over
a rolling window of period candles. Candle input, single parameter
period (default 10). Positive on average-bullish windows, negative on
average-bearish. Holds the previous value if the entire window has
zero range (denominator undefined).
Reference: Donald Dorsey, also pandas-ta rvi.
Touchpoints: rvi.rs + mod.rs + lib.rs re-export, PyRvi + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values reference,
RviNode (4-column OHLC batch) + index.d.ts/index.js + indicators.test
.js factory + reference, WasmRvi + make_candle_ohlc helper, candle-fuzz
target + criterion bench, README + CHANGELOG.
* feat(pgo): add Pretty Good Oscillator
Mark Johnson's PGO = (close - SMA(close, period)) / EMA(TR, period).
Counts roughly how many ATR-equivalents the close sits from its
period-bar mean. Candle input, single parameter period (default 14).
Johnson's heuristic uses +3/-3 crossings as entry signals.
Touchpoints: pgo.rs + mod.rs + lib.rs re-export, PyPgo + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values flat-close
reference, PgoNode (h/l/c) + index.d.ts/index.js + indicators.test.js
factory + reference, WasmPgo, candle-fuzz target + bench, README +
CHANGELOG.
* feat(kst): add Know Sure Thing (Pring)
Pring's long-horizon momentum oscillator: weighted sum of four
SMA-smoothed ROC series with fixed weights 1, 2, 3, 4, plus an SMA
signal line. Nine parameters (four ROC periods, four SMA periods, one
signal period); classic() applies Pring's recommended defaults.
Multi-output indicator emitting KstOutput { kst, signal }.
Touchpoints: kst.rs + mod.rs + lib.rs re-export, PyKst + __init__.py
+ test_new_indicators MULTI + test_known_values flat-input reference,
KstNode + KstValue + index.d.ts/index.js + indicators.test.js multi
factory + reference, WasmKst (manual JsValue object), scalar-fuzz
target (handled outside the f64-output drive helper), README +
CHANGELOG.
* feat(smi): add Stochastic Momentum Index (Blau)
Blau's doubly-EMA-smoothed bounded oscillator: measures the close's
displacement from the centre of the recent high-low range, scaled by
the smoothed range. Candle input, three parameters (period, d_period,
d2_period) with defaults 5 / 3 / 3.
Internally feeds both the displacement-EMA stack and the range-EMA
stack on every candle so they warm up in parallel (gating either
behind the other starves the second by one input).
Touchpoints: smi.rs + mod.rs + lib.rs re-export, PySmi + __init__.py
+ test_new_indicators CANDLE_SCALAR + test_known_values flat-input
reference, SmiNode + index.d.ts/index.js + indicators.test.js factory
+ reference, WasmSmi, candle-fuzz target, README + CHANGELOG.
* feat(laguerre-rsi): add Ehlers Laguerre RSI
Four-stage Laguerre polynomial filter wrapped in an RSI-style up/down
accumulator. Single gamma in [0, 1] (default 0.5) trades lag for
smoothness. State is seeded by setting all four L_i to the first input
so a constant series stays at the neutral 50. Output clamped to
[0, 100] to absorb floating-point rounding.
Reference: Ehlers, Time Warp - Without Space Travel, 2002.
Touchpoints: laguerre_rsi.rs + mod.rs + lib.rs re-export, PyLaguerreRsi
+ __init__.py + test_new_indicators SCALAR + test_known_values neutral
reference, LaguerreRsiNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmLaguerreRsi via scalar macro, scalar-fuzz
target, README + CHANGELOG.
* feat(connors-rsi): add Connors RSI (CRSI)
Larry Connors' 3-component aggregate: RSI(close), RSI(streak), and
PercentRank of the 1-period return over the last period_rank returns.
Each component is bounded in [0, 100] so the aggregate is too.
Three parameters (period_rsi, period_streak, period_rank) with
defaults 3 / 2 / 100. Streak tracks consecutive up/down runs (resets
to 0 on unchanged close).
Touchpoints: connors_rsi.rs + mod.rs + lib.rs re-export, PyConnorsRsi
+ __init__.py + test_new_indicators SCALAR + test_known_values bounded
reference, ConnorsRsiNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmConnorsRsi via scalar macro, scalar-fuzz
target, README + CHANGELOG.
* feat(inertia): add Dorsey Inertia (RVI + LinReg)
Donald Dorsey's Inertia — a LinearRegression smoothing of the RVI
series. Endpoint of an n-bar least-squares fit of RVI is the indicator
reading. Preserves trend direction while damping the ratio. Candle
input, two parameters (rvi_period, linreg_period) with defaults 14 / 20.
Touchpoints: inertia.rs + mod.rs + lib.rs re-export, PyInertia +
__init__.py + test_new_indicators CANDLE_SCALAR + test_known_values
constant reference, InertiaNode (4-column OHLC batch) + index.d.ts /
index.js + indicators.test.js factory + reference, WasmInertia,
candle-fuzz target, README + CHANGELOG.
* test(kst): Move KST out of MULTI dict (it is scalar-input)
KST sits in the MULTI dict (candle-input, multi-output) but its
update() takes a single f64, not a candle tuple. The shared streaming
loop in test_multi_streaming_matches_batch fed the OHLCV tuple in,
which crashed with `TypeError: argument 'value': must be real number,
not tuple` on every Python matrix entry.
Split into a new MULTI_SCALAR_INPUT dict with its own test function
that feeds the close-price stream as floats. KST is currently the
only such indicator; structure is ready for future scalar-input
multi-output additions (e.g. some MACD-shaped indicators).
* test(coverage): Cover SMI zero-range and ConnorsRsi zero-prev cold paths
codecov/patch on PR 40 flagged two uncovered defensive branches:
- SMI returns self.current early when the smoothed range collapses to
zero (`r2 <= 0.0`) so the formula stays defined. Exercised by feeding
bars where high == low.
- ConnorsRsi skips the ROC ring-buffer update when the previous price
is exactly zero so the divide-by-zero in `(input - prev) / prev` is
impossible. Exercised by seeding the first bar at 0.0.
* 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.
* chore(docs): rename benchmark CPU from 7950X3D to 9950X
The "Reproduced on" line in the umbrella + binding READMEs and the
benchmark page on the site listed the wrong AMD CPU. The benchmarks
were actually produced on a Ryzen 9 9950X, not a 7950X3D. Same
column for absolute µs values applies — the speedup ratios in the
tables are unchanged either way because they're relative across
libraries on the same machine.
The performance-regression issue template's CPU example also
updated for consistency (it was a generic placeholder, but matching
the canonical machine makes the example concrete).
* chore(npm): restore Windows ARM64 sub-package + napi matrix entry
npm Support unblocked the `wickra-win32-arm64-msvc` package name and
transferred write access to @kingchenc (placeholder 0.0.1-security
was published from their side; we ship our first real version on
top of that). This re-enables every change 8aa74cb temporarily
backed out for 0.2.1:
- bindings/node/package.json: re-add `aarch64-pc-windows-msvc` to
napi.triples.additional and `wickra-win32-arm64-msvc` to
optionalDependencies.
- bindings/node/npm/win32-arm64-msvc/package.json: restored — name,
cpu = arm64, os = win32, version pinned to the workspace.
- .github/workflows/release.yml: re-enable the
`windows-11-arm / aarch64-pc-windows-msvc` row in the node-build
matrix and drop the "temporarily skipped" comment block.
After the next tag-push this binding will be published alongside
the other five platforms and `npm install wickra` on Windows ARM64
will resolve to a native build instead of failing the loader's
optional-dep lookup.
* release: bump workspace + bindings to 0.2.7
Workspace, every binding (Python, Node, six platform stubs incl. the
restored win32-arm64-msvc), and the CHANGELOG all move together to
0.2.7. wickra-win32-arm64-msvc is now part of the standard publish
matrix and will land on npm alongside the other five binaries.
The 0.2.7 CHANGELOG entry consolidates the two changes this cycle:
- Windows ARM64 binding restored (npm Support unblocked the name).
- Benchmark CPU label corrected (Ryzen 9 9950X, not 7950X3D).
* fix(docs-rs): rename `doc_auto_cfg` to `doc_cfg` after Rust 1.92 merge
`doc_auto_cfg` was removed in Rust 1.92.0 and folded back into
`doc_cfg` (rust-lang/rust#138907). docs.rs builds with the latest
nightly and sets `--cfg docsrs`, so the previous
#![cfg_attr(docsrs, feature(doc_auto_cfg))]
aborts compilation with E0557 on every published 0.2.x. GitHub CI
never tripped this — stable rustc ignores the line because nothing
sets the `docsrs` cfg there.
Switch all three published library crates (`wickra`, `wickra-core`,
`wickra-data`) to the merged-into `doc_cfg` gate. Same intent, same
on-docs.rs output, builds again on nightly.
* docs(readme): float Wickra to the top of the comparison tables
Reorders the "Why Wickra exists" library-comparison table and the two
benchmark headers so Wickra is the first row (with a ★ marker) instead
of the last. The previous order placed Wickra at the bottom, which
buries the only row a reader landing on the README is here to compare
against. Same column data, same ★/winner annotations, just the row
order flipped and a ★ prefix on the Wickra label.
Mirrored across the umbrella README and every binding README so the
crates.io / PyPI / npm landing pages stay in sync.
* release: bump workspace + bindings to 0.2.6
Workspace, every binding (Python, Node, Node platform stubs), the
release.yml comment and the CHANGELOG all move together to 0.2.6 so
the next tagged release lines every artefact up.
0.2.6 carries two changes from the [0.2.6] CHANGELOG entry:
- fix(docs-rs): swap the now-removed `doc_auto_cfg` feature gate for
the merged-into `doc_cfg` so docs.rs nightly builds resume.
- docs(readme): float ★ Wickra to the top of every comparison table
across the umbrella + binding READMEs.
wickra-win32-arm64-msvc stays excluded for this release with the same
npm spam-filter rationale that held for 0.2.5.
Workspace, every binding (Python, Node, Node platform stubs), and the
release.yml comment are all updated together so the next tagged release
on `v0.2.5` lines every artefact up.
Also adds a short README "Disclaimer" section pointing out that Wickra
is an indicator toolkit, not a trading system, and that production
use is at the caller's own risk. The legal terms in LICENSE (PolyForm
Noncommercial 1.0.0, "No Liability") already cover the warranty / as-is
language — the README section just makes the trading-specific framing
visible without burying it in a click-through.
CHANGELOG carries the new 0.2.5 entry with the API addition
(`BinanceConfig` + `connect_with_config`) and the best-effort Pong
write change in `BinanceKlineStream::next_event`. wickra-win32-arm64-msvc
stays excluded for this release with the same npm-spam-filter rationale
that held for 0.2.1.
R15 — `bindings/node/package.json` and all six per-platform subpackage
templates (`npm/{darwin-arm64,darwin-x64,linux-arm64-gnu,linux-x64-gnu,
win32-arm64-msvc,win32-x64-msvc}/package.json`) plus the WASM
`release.yml` enrich step switch the `license` field from the npm
convention `SEE LICENSE IN LICENSE` to the SPDX identifier
`PolyForm-Noncommercial-1.0.0`. npm's license search and downstream
tooling can now surface the actual license.
R18 — every `engines.node` field is bumped from `>= 16` to `>= 18`.
The package's test script (`node --test __tests__/`) uses the built-in
`node --test` runner that landed in Node 18; advertising support for
Node 16 / 17 was a guarantee we never verified (CI tests on Node 18 /
20 only) and would have produced a confusing error on those versions.
R19 — README's benchmark section gains an explicit hardware /
software-version block and reframes the absolute µs values as a
relative-speedup snapshot rather than a universal contract. Also tells
the reader how to reproduce locally (`pip install -e
bindings/python[bench]` + `python -m benchmarks.compare_libraries`) and
where the CI artefact lives.
Side effects:
- R16 / R17 (built wheel under `bindings/python/dist/` and
`examples/node/node_modules/`) — verified that both are already
covered by `.gitignore` (`*.whl`, `dist/`, `**/node_modules/`) and
were never tracked by git. The local directories have been cleared;
no `.gitignore` change needed and no committed file removed.
The README and Streaming-vs-Batch benchmark tables were a stale snapshot
("5 000-bar series", numbers from an older machine). Re-run
`python -m benchmarks.compare_libraries` on the current hardware against
the same peer set (finta + talipp; TA-Lib and pandas-ta stay excluded on
Windows) and replace the tables with the fresh numbers.
The new run uses the script's current defaults: a 20 000-bar batch series
and a 5 000-bar seed + 15 000-bar live streaming workload — both more
representative of real backtests than the previous 5 000 / 2 000-bar
sizes. Wickra still wins every batch row outright (3.5× to 1 244× faster
than the nearest peer) and the streaming RSI is ~13.8× faster than
talipp's incremental implementation.
Finish the per-language `examples/<lang>/` restructure by relocating the
WASM browser demo from bindings/wasm/examples/ to examples/wasm/.
* `examples/wasm/index.html` is the moved file; its WASM module import
becomes `../../bindings/wasm/pkg/wickra_wasm.js` so the demo still loads
the wasm-pack output without copying it.
* bindings/wasm/README.md, Quickstart-WASM.md, examples/README.md and the
root README "Languages" + project-layout block all point at the new
path. The serve command in the docs now says "serve the repository root
and open examples/wasm/index.html".
`bindings/wasm/examples/` is empty after the move; the now-empty
directory is removed.
Continue the per-language `examples/<lang>/` restructure: move the three
Node example files (streaming.js, backtest.js, live_trading.js) out of
bindings/node/examples/ and into a top-level examples/node/ directory.
* `examples/node/package.json` is a `private` package that pulls the
native binding via `file:../../bindings/node` and lists `ws` as a
dev-dependency for the live-trading example. `require('..')` in each
file becomes `require('wickra')` — exactly what a downstream user would
write — and the file-header run instructions are updated to the new
two-step workflow (`npm install` in bindings/node, then in
examples/node).
* `backtest.js`'s default-CSV path becomes the much shorter
`__dirname/../data/btcusdt-1d.csv` from the new location.
* `bindings/node/package.json` drops the now-unused `ws` devDependency.
* `.gitignore` is broadened from `bindings/node/node_modules/` to
`**/node_modules/` so the new `examples/node/node_modules/` directory is
not tracked.
* The README "Languages" table, project-layout block and
`examples/README.md` Node section are updated for the new paths and run
commands.
Verified by running `node backtest.js` (3200 BTCUSDT daily bars, matching
output), `node streaming.js`, and `node --check live_trading.js` from the
new location.
The three Rust examples (backtest, fetch_btcusdt, live_binance) used to
live each in their own crate's examples/ dir, splitting the example set
across crates and burying it inside the source tree. Move them into a new
workspace member crate at `examples/rust/` (package `wickra-examples`,
`publish = false`) so all language examples sit under one top-level
`examples/<lang>/` tree.
* `examples/rust/Cargo.toml` declares the per-binary deps (wickra,
wickra-data with the `live-binance` feature always on, serde_json, tokio
for the macro and current-thread runtime).
* `examples/rust/src/bin/{backtest,fetch_btcusdt,live_binance}.rs` are the
three migrated binaries; their doc-comments and the fetch_btcusdt output
path are updated for the new location and run command
(`cargo run -p wickra-examples --bin <name>`).
* Workspace `Cargo.toml` lists the new member; the now-empty
`[dev-dependencies]` extras (`wickra`, `tokio` in wickra-data and
`serde_json` in wickra) that existed only for these examples are dropped.
* The `[[example]] live_binance` table is removed from wickra-data's
manifest since the file moved out.
* README "Languages" + project-layout, examples/README.md, Quickstart-Rust
and Data-Layer are pointed at the new paths and commands.
`cargo build -p wickra-examples` and `cargo run --release -p wickra-examples
--bin backtest -- examples/data/btcusdt-1d.csv` both succeed; the rest of
the workspace (core, data, wickra) builds, clippies (`--all-targets -D
warnings`) and tests (508 core + 28 data + 1 integration + 74+3+1
doctests) all stay green.
The top-level examples/ directory held only python/, which made the
examples look Python-only even though Rust, Node and WASM all ship their
own. Add examples/README.md: a single index of every runnable example
across Rust, Python, Node and WASM, each with its run command, plus a note
on the bundled BTCUSDT datasets.
Point the README "Languages" table at the Node backtest example and link
the new index from both the table and the project-layout section.
Add seven OHLCV datasets under crates/wickra/examples/data/, one per
timeframe (1m/5m/15m/1h/12h/1d/1month), holding real BTCUSDT spot klines
fetched from the Binance REST API. The new fetch_btcusdt example
regenerates them: it paginates the klines endpoint through the system
curl, parses with serde_json, validates every candle via Candle::new and
keeps only fully closed buckets.
The indicator benchmarks now run against the 1m dataset instead of a
synthetic series, and a new example_data integration test checks that
every file parses and carries evenly spaced, monotonic timestamps.
The monthly file is named btcusdt-1month.csv rather than btcusdt-1M.csv
so it does not collide with btcusdt-1m.csv on case-insensitive
filesystems (Windows, default macOS).
The original taxonomy was four classical families plus a statistics group,
with the F1-F12 expansion slotted in as sub-categories. This regroups the
whole 71-indicator catalogue into eight top-level families, each with at
least five members:
Moving Averages (12), Momentum Oscillators (13), Trend & Directional (9),
Price Oscillators (5), Volatility & Bands (12), Trailing Stops (5),
Volume (9), Price Statistics (7).
- Wiki: docs/wiki/indicators/ reorganised into eight family folders; all 71
indicator pages moved with `git mv`. Every internal cross-link is
normalised to `../<family>/Indicator-X.md`, each page's `Family` field is
set to its new family, and two pre-existing `../Indicator-Chaining.md`
links (should have been `../../`) are corrected. A link check confirms
every relative wiki link resolves.
- Indicators-Overview.md fully rewritten around the eight families;
Home.md indicator reference and the README family table follow suit.
- Warmup-Periods.md gains the eight F13 indicators; CHANGELOG records the
46-indicator expansion (25 -> 71) and the eight-family taxonomy.
- Tests: Node indicators.test.js and Python test_new_indicators.py cover
all eight new indicators (Node 91/91, Python 117/117 green).
cargo fmt + clippy (core/wickra/data/wasm/node) clean; 508 core tests,
25 data tests and 74 doctests green.
Finalises the F1-F12 indicator expansion (25 -> 63 indicators).
- Python `wickra/__init__.py`: import and re-export all 63 indicators,
grouped by family, with a matching `__all__`. The package previously
exposed only the original 25 even though the compiled module and the
`.pyi` stubs already carried the rest.
- Docs: `Home.md` and `README.md` indicator counts and family tables
updated to 63; `Indicators-Overview.md` already restructured per family
in F10-F12; `Warmup-Periods.md` gains all 38 new indicators across the
single- and multi-output tables (and the stale two-arg `Psar::new`
example is corrected to three args); `CHANGELOG.md` `[Unreleased]` lists
every new indicator by family.
- Tests: `bindings/node/__tests__/indicators.test.js` covers all 63
indicators (streaming==batch plus four new reference-value checks),
80/80 green; new `bindings/python/tests/test_new_indicators.py` covers
the 38 additions (streaming==batch, shapes, reference values,
lifecycle), Python suite 105/105 green.
- `bindings/node/index.js` regenerated by `napi build`.
cargo fmt + clippy (core/wickra/data/wasm/node) clean; 454 core tests,
25 data tests, 66 doctests, 80 Node tests and 105 Python tests green;
`cargo check -p wickra-wasm --tests` green.
CI had no coverage measurement, and although .gitignore listed coverage
artefacts nothing produced them.
Add a `coverage` job that runs cargo-llvm-cov over the three pure-Rust
crates (with wickra-data's live-binance feature so the Binance parser
tests count), emits lcov, and uploads to Codecov. The Codecov upload
uses fail_ci_if_error: false so a Codecov outage cannot break CI. Both
new actions (taiki-e/install-action, codecov/codecov-action) are
SHA-pinned. Add a coverage badge to the README.
- "## Indicators in 0.1.0" -> "## Indicators" (the heading drifted from
the actual version; making it version-neutral stops the drift).
- Project layout: there is no top-level benches/ directory — Rust
benches and examples live inside their crate. The tree now shows
crates/wickra/benches, the per-crate examples, and the new
bindings/node and bindings/wasm examples/ directories.
- Node "Example" pointed at a test file; it now points at the real
bindings/node/examples/streaming.js (added in E17).
- "## Test counts" hardcoded numbers (171/11/56/7) that drift on every
added test. Replaced with a version-neutral "## Testing" section that
describes what each suite covers, including the WASM tests.
- Top: CI badge, crates.io / PyPI / npm version badges, license tag.
- Bottom (new section before License): a short contribution guide with
starting points for new indicators, bug fixes, binding work, and style.
- Footer: large "give us a star" call-to-action with GitHub stars, forks,
and issues badges via shields.io.
The previous `[[example]] path = "../../examples/rust/..."` entries
pointed at files outside the crate root. cargo only packages files
inside the crate directory, so the examples would have been silently
dropped on publish. Moving them to crates/wickra/examples/ and
crates/wickra-data/examples/ keeps them as part of the published
package and lets cargo discover them automatically (no [[example]]
override needed). README and project-layout section updated.
On every v* tag push the release workflow now publishes the project to
all three public registries in parallel:
- crates.io: wickra-core then wickra-data then wickra, with a 45-second
sleep between each so the registry index can refresh before the next
publish step asserts the previous version is available.
- PyPI: maturin-action builds wheels for Linux x86_64 + aarch64, macOS
x86_64 + aarch64, and Windows x64, plus an sdist; all artefacts upload
to PyPI via MATURIN_PYPI_TOKEN.
- npm: napi-rs builds a native binary per platform (linux-x64-gnu,
darwin-x64, darwin-arm64, win32-x64-msvc), publishes each as its own
platform package, then publishes the main `wickra` meta-package
that resolves to the right platform at install time.
- WASM: wasm-pack builds the bundler-target package and publishes it as
`wickra-wasm` on npm, with the auto-generated package.json enriched
with the author/repo/license metadata.
Package metadata was unified so all targets point at kingchenc/wickra
on GitHub; the Node binding is now plain `wickra` (the @wickra/ scope
was unnecessary because the bare name was free). README install table
updated to match.
Switches the project from Apache-2.0 to PolyForm Noncommercial 1.0.0.
Use, modification, redistribution, forking and contribution are all
permitted; the only thing the new license withholds is commercial sale
of the software or of services built primarily around it.
Updates: LICENSE file, workspace Cargo license metadata, the Python
pyproject classifier and SPDX field, and the Node package.json. The
README now explains the practical scope in plain English.
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.
wickra-bot