The v0.4.0-era CI failure was a runner network blip — `napi build` invokes cargo,
whose fetch of index.crates.io hit "Could not resolve host: index.crates.io" and
failed the Node-on-macOS job, forcing a manual re-run. The earlier flake-hardening
(setup-node/setup-python + rust-cache retries) only covered toolchain download and
cache restore, not the registry fetches inside the actual build/publish steps.
Set tool-level network retries as workflow env so every cargo/napi/maturin/
wasm-pack/npm/pip invocation in every job inherits them — including the nested
cargo calls inside napi/maturin/wasm-pack:
- CARGO_NET_RETRY=10 (default 3): cargo classes DNS-resolve / connect / timeout
errors as spurious and retries with backoff; 10 attempts ride out a transient
blip instead of failing the job.
- CARGO_NET_GIT_FETCH_WITH_CLI=true: more robust git-dep fetches.
- npm_config_fetch_retries=5 / maxtimeout=120s: npm ci/install registry retries.
- PIP_RETRIES=5 / PIP_DEFAULT_TIMEOUT=120: pip install resilience.
Applied to ci.yml, release.yml and bench.yml (the workflows that build). No more
manual re-runs for transient registry flakes.
The auto-injected GITHUB_TOKEN defaulted to write-all in ci.yml, bench.yml
and release.yml (no top-level permissions block), and codeql.yml declared
its scopes only at job level. Add a top-level `permissions: contents: read`
to all four so the token starts read-only and only the jobs that genuinely
write through it raise the scope:
- release.yml: github-release keeps contents: write; node-/wasm-publish and
attestations keep their id-token / attestations: write blocks. The
cargo/python/node publish jobs push to crates.io/PyPI/npm via their own
registry secrets, not the GITHUB_TOKEN, so read-only is correct for them.
- codeql.yml: analyze keeps security-events: write (job level).
- ci.yml / bench.yml: no job writes back to the repo (coverage uploads via
CODECOV_TOKEN; bench only uploads an artifact), so no job override is needed.
sync-about.yml already had a top-level block but at contents: write; demote
the top level to read and move contents: write down to the single `sync` job
(the PR-head counter push is the only GITHUB_TOKEN write). The cross-repo
About/docs/webpage/org writes are unaffected — they run through the
fine-grained ABOUT_SYNC_TOKEN, which the permissions key does not govern.
Raises OpenSSF Scorecard Token-Permissions from 0 toward 10.
* examples(node): add RSI mean-reversion strategy
Node counterpart of strategy_rsi_mean_reversion.{py,rs}: RSI(14) < 30 long,
> 70 exit, 0.1% fees, hourly BTCUSDT. Output verified byte-identical to the
Rust reference (37 trades W24/L13, -17.84% return, 46.89% max drawdown).
* examples(node): add MACD + ADX trend-filter strategy
Node counterpart of strategy_macd_adx.{py,rs}: MACD(12,26,9) histogram
crossover entries gated by ADX(14) > 20, hourly BTCUSDT, 0.1% fees. Output
verified byte-identical to the Rust reference (246 trades W90/L156, -47.19%
return, 53.75% max drawdown).
* examples(node): add Bollinger-squeeze breakout strategy
Node counterpart of strategy_bollinger_squeeze.{py,rs}: enter on a fresh
180-bar Bollinger-bandwidth low + close above the upper band, exit on a
2*ATR(14) stop or upper-band collapse, daily BTCUSDT, 0.1% fees. Output
verified byte-identical to the Rust reference (1 trade, -7.82% return,
13.01% max drawdown).
* examples(wasm): add RSI mean-reversion strategy demo
Browser counterpart of strategy_rsi_mean_reversion.{py,js,rs}: RSI(14) < 30
long, > 70 exit, 0.1% fees, summary table. Same signal/fill/PnL/equity loop as
the runtime-verified Node example; loads via the established wickra_wasm.js
init + fetch-CSV pattern. (wasm32 build runs in CI.)
* examples(wasm): add MACD + ADX trend-filter strategy demo
Browser counterpart of strategy_macd_adx.{py,js,rs}: MACD(12,26,9) histogram
crossover gated by ADX(14) > 20, hourly BTCUSDT, 0.1% fees. Logic identical to
the runtime-verified Node example; standard wickra_wasm.js init + fetch-CSV
loader. (wasm32 build runs in CI.)
* examples(wasm): add Bollinger-squeeze breakout strategy demo
Browser counterpart of strategy_bollinger_squeeze.{py,js,rs}: fresh 180-bar
Bollinger-bandwidth low + upper-band breakout, 2*ATR(14) stop, daily BTCUSDT,
0.1% fees. Logic identical to the runtime-verified Node example; standard
wickra_wasm.js init + fetch-CSV loader. (wasm32 build runs in CI.)
* ci: add examples syntax-smoke job (P2.3)
The Rust examples are built by 'cargo build -p wickra-examples --bins'; the
Node, browser-WASM and Python examples had no build gate. New job parse-checks
every examples/{node,wasm}/*.js, extracts and node --checks each WASM .html
module script, and python -m py_compile's every examples/python/*.py — so a
broken example edit fails CI instead of landing silently.
* docs(examples): list the new Node + WASM strategy examples
Add the three Node strategy scripts and three WASM strategy demos to the
examples README tables, bringing Node and WASM to parity with the existing
Rust and Python strategy rows.
* chore(examples): refresh examples/node lockfile for the linked wickra binding
npm install rewrote the file: dependency snapshot of the local wickra binding
that the examples link against (version 0.1.4 -> 0.3.1, license + engines
fields), which had gone stale in the committed lockfile.
* test(node): add input-validation suite
Node counterpart of bindings/python/tests/test_input_validation.py: invalid
constructor parameters (ATR zero period, MACD non-increasing fast/slow,
BollingerBands negative multiplier, PSAR step > max, ValueArea period/pct,
InitialBalance/OpeningRange zero period, Ichimoku non-increasing periods,
Ehlers-family ordering) and unequal-length candle/ValueArea batch inputs all
throw a JS Error. Validated against the built binding.
* test(node): add indicator completeness contract
Introspects every exported indicator class and asserts the full interface
(update / batch / reset / isReady / warmupPeriod) plus the pre-warmup contract
for zero-arg indicators, and guards that the full catalogue (>= 200 classes)
is exported. Catches a new indicator wired without the standard methods, or a
stale/partial native build dropping exports, with no per-indicator boilerplate.
* test(wasm): broaden scalar streaming-vs-batch coverage
Extend the inline wasm-bindgen-test suite with a streaming==batch check across
~70 scalar indicators spanning moving averages, momentum, volatility,
statistics/regression, Ehlers/cycle and risk/performance families (previously
only EMA + the candle-input group were covered per-indicator), plus four more
invalid-constructor assertions. Constructor args mirror the CI-passing Node
factories. Host-compiles (cargo test -p wickra-wasm --no-run); executed in CI
via wasm-pack test --node.
* bench(node): add indicator throughput benchmark
Node counterpart of the Rust criterion benches / Python compare_libraries:
measures streaming (per-tick update) and batch throughput in Mupd/s across a
representative indicator set over a synthetic OHLCV series (--bars, default
200k). Dependency-free; wired as 'npm run bench'.
* docs(wasm): list strategy demos + document the benchmark story
Add the three new strategy demos to the WASM examples table and a Performance
section: parallel_assets.html is the in-browser benchmark, with raw throughput
covered by the Rust criterion / Python / Node benchmarks (the WASM engine is the
same core compiled to wasm32).
* fix(bindings): clear clippy pedantic lints and lint bindings in CI
Resolve the pedantic lints that only surfaced under a full
`cargo clippy --workspace` (the CI clippy job covered only the core
crates, so the Python/Node bindings drifted):
- manual_midpoint: `(a + b) / 2.0` -> `f64::midpoint(a, b)` (node + python)
- new_without_default: add `Default` impls for the six no-arg Node nodes
- type_complexity: factor the pivot/Ichimoku return tuples into
`PivotLevels` / `WoodieLevels` / `IchimokuLines` aliases (python)
- many_single_char_names: allow at crate level — OHLCV batch helpers bind
the conventional o/h/l/c/v column names
Add a dedicated `clippy-bindings` CI job (ubuntu-only, with Python + Node
toolchains) so future binding lints fail CI instead of slipping through.
* ci: lint Python and Node bindings in a dedicated clippy job
The main `rust` job's clippy step only covers wickra-core/wickra/
wickra-data/wickra-wasm, so pedantic lints in the PyO3/napi bindings
slipped through. Add an ubuntu-only `clippy-bindings` job that
provisions Python + Node (needed by the build scripts) and runs
`cargo clippy -p wickra-node -p wickra-python --all-targets -- -D warnings`.
* feat(apo): add Absolute Price Oscillator
EMA(close, fast) - EMA(close, slow). Like MACD without the signal EMA.
Defaults to (fast = 12, slow = 26); fast must be strictly less than
slow.
Touchpoints: apo.rs + mod.rs + lib.rs re-export, PyApo + __init__.py
+ test_new_indicators SCALAR + test_known_values flat reference,
ApoNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmApo via scalar macro, scalar-fuzz target, README + CHANGELOG.
* fix(apo): add PyApo + ApoNode + WasmApo bindings missed from ec269d8
The previous APO commit (ec269d8) only registered APO in the Python
__init__.py / Node index.js / Node index.d.ts / fuzz / tests / docs.
The actual PyApo pyclass, ApoNode napi class, and WasmApo wasm class
edits silently no-op'd because the underlying lib.rs files had been
touched by a branch switch between Read and Edit. The bindings were
therefore advertising APO from the Python module / Node package /
WASM module but not actually exposing it.
Fix: insert PyApo block + add_class call in bindings/python/src/lib.rs,
ApoNode block in bindings/node/src/lib.rs, WasmApo macro line in
bindings/wasm/src/lib.rs. cargo test workspace stays at 615 (no new
tests added; the existing test_known_values + indicators.test.js
references would have failed at import once the bindings rebuilt
without these classes).
* feat(ao-histogram): add Awesome Oscillator Histogram
AO - SMA(AO, sma_period). A configurable variant of the existing
AcceleratorOscillator (which fixes fast=5, slow=34, sma=5).
Three parameters; defaults match Bill Williams' Accelerator.
Touchpoints: awesome_oscillator_histogram.rs + mod.rs + lib.rs
re-export, PyAoHist + __init__.py + test_new_indicators CANDLE_SCALAR
+ test_known_values flat reference, AwesomeOscillatorHistogramNode +
index.d.ts/index.js + indicators.test.js factory + reference,
WasmAoHist, candle-fuzz target, README + CHANGELOG.
* feat(cfo): add Chande Forecast Oscillator
100 * (close - LinReg(close, period)) / close. Positive when close
overshoots the linear forecast, negative when it undershoots. Holds
the previous value if the close is zero (percentage form undefined).
Single param period (default 14).
Touchpoints: cfo.rs + mod.rs + lib.rs re-export, PyCfo + __init__.py
+ test_new_indicators SCALAR + test_known_values linear reference,
CfoNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmCfo via scalar macro, scalar-fuzz target, README + CHANGELOG.
* fix(cfo): add WasmCfo binding missed from 733afd9
* feat(zero-lag-macd): add Zero-Lag MACD
Classic MACD topology with ZLEMA substituted for EMA everywhere:
faster reaction to trend changes at the cost of slightly noisier
readings. Multi-output ZeroLagMacdOutput { macd, signal, histogram }.
Three parameters (fast = 12, slow = 26, signal = 9); fast must be
strictly less than slow.
Touchpoints: zero_lag_macd.rs + mod.rs + lib.rs re-export, PyZeroLagMacd
+ __init__.py + test_new_indicators MULTI + test_known_values flat
reference, ZeroLagMacdNode + ZeroLagMacdValue + index.d.ts/index.js +
indicators.test.js multi factory + reference, WasmZeroLagMacd, scalar
fuzz with hand-rolled drive (multi-output bypasses the f64-only
helper), README + CHANGELOG.
* feat(elder-impulse): add Alexander Elder Impulse System
Tri-state momentum gauge: +1 (green/buy) when EMA trend and MACD
histogram both rise, -1 (red/sell) when both fall, 0 (blue/neutral)
on disagreement. Four parameters (ema_period, macd_fast, macd_slow,
macd_signal); defaults (13, 12, 26, 9) match Elder.
Internally feeds both branches on every input so they warm in parallel;
needs one bar past the slowest branch to seed direction state.
Touchpoints: elder_impulse.rs + mod.rs + lib.rs re-export, PyElderImpulse
+ __init__.py + test_new_indicators SCALAR + test_known_values neutral
reference, ElderImpulseNode + index.d.ts/index.js + indicators.test.js
factory + reference, WasmElderImpulse via scalar macro, scalar-fuzz
target, README + CHANGELOG.
* feat(stc): add Schaff Trend Cycle
Doug Schaff's doubly-Stochastic-smoothed MACD. Bounded [0, 100]
reading that reacts faster than MACD by extracting the percentile of
MACD within a recent window, half-EMA-smoothing it, and re-stochasing
the smoothed series. Four parameters (fast = 23, slow = 50,
schaff_period = 10, factor = 0.5); fast must be strictly less than
slow and factor must lie in (0, 1].
Output clamped to [0, 100] to absorb floating-point rounding. The
stochastic stages clamp to 0 when their rolling range collapses (flat
input or perfectly monotone trend), so a flat series settles
deterministically at 0 after warmup.
Touchpoints: stc.rs + mod.rs + lib.rs re-export, PyStc + __init__.py
+ test_new_indicators SCALAR + test_known_values flat reference,
StcNode + index.d.ts/index.js + indicators.test.js factory + reference,
WasmStc via scalar macro, scalar-fuzz target, README + CHANGELOG.
* fix(stc): rename last_stc -> last_value to satisfy clippy
* ci: Retry setup-node and setup-python on CDN flakes
Setup-node on Windows runners and setup-python across all OSes
occasionally fail with a silent hang or 5xx mid-download ("Attempting
to download 18..." → fail in <1s) — pure upstream CDN flake. The fix
ran on this branch's previous merge commit (24e723f) had to be
re-triggered manually via `gh run rerun --failed`.
Wrap both setup actions with continue-on-error and a follow-up retry
step that waits 30s and re-runs the same setup. The retry only fires
when the first attempt failed (steps.<id>.outcome == 'failure'), so a
green setup costs nothing extra. The retry uses the identical pinned
SHA so we still get supply-chain verification on both attempts.
Applied to ci.yml (Python matrix and Node matrix). release.yml has
the same setup-node / setup-python steps but is rarely re-run, so
the existing manual rerun pattern stays sufficient for now.
* test(zero-lag-macd): Fix MULTI dict shape mismatch + cover warmup_period
ZeroLagMACD was registered in the Python MULTI dict (which asserts a
(n, 2) batch shape) but actually emits (n, 3) — macd, signal,
histogram — like MACD. Moved out into its own standalone test
test_zero_lag_macd_streaming_matches_batch (3-tuple shape), and
included in the lifecycle sweep. Mirrors the existing Alligator
pattern for 3-output candle indicators.
Also adds a unit test for ZeroLagMacd::warmup_period that pins both
the (12, 26, 9) classic case and a small-period config — these four
lines were the codecov/patch miss on PR 41.
* 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.
jetli/wasm-pack-action@v0.4.0 with no version: input installs whatever
wasm-pack the action's bundled installer fetches — currently a ~0.10.x
release whose 'build' subcommand does not yet accept --features. Our
build invocation 'wasm-pack build … --features panic-hook' now fails
with
error: Found argument '--features' which wasn't expected, or isn't
valid in this context
USAGE: wasm-pack build --release --target <target>
even though that exact command worked on past runs where the action
happened to install a newer wasm-pack. (The bundler-target release.yml
job passed for v0.2.1 only because it shared the same cached install
on that runner.)
wasm-pack's --features top-level flag has been stable since 0.12.0, so
the fix is to install a fresh wasm-pack each run. Switch both the ci.yml
'WASM build' step and the release.yml 'wasm-publish' job to the same
taiki-e/install-action prebuilt-binary installer we already use for
cargo-llvm-cov and cargo-fuzz. taiki-e tracks the latest wasm-pack
release and the install is a single binary download — no compile, no
shell installer.
The wasm-pack invocations themselves are unchanged.
criterion 0.8.2 raised its MSRV from 1.85 to 1.86 (rustc 1.85.1 is now
explicitly rejected by its Cargo.toml `rust-version`). One more notch
on the same upward drift that already took us from 1.75 -> 1.80 (rayon)
-> 1.85 (clap_lex/edition2024).
Updated:
- Cargo.toml workspace rust-version 1.85 -> 1.86
- .github/workflows/ci.yml MSRV matrix name + toolchain
- ci.yml comment refreshed to reflect the new driving dep
The first MSRV bump to 1.80 fixed the rayon-core floor but ran into a
second transitive-dep floor on the same CI run:
error: failed to parse manifest at clap_lex-1.1.0/Cargo.toml
Caused by: feature `edition2024` is required
The package requires the Cargo feature called `edition2024`, but
that feature is not stabilized in this version of Cargo (1.80.1).
clap_lex 1.1.0 is pulled in by criterion (dev-dep on the wickra crate)
via clap 4.6 -> clap_builder 4.6 -> clap_lex 1.1. edition2024 was
stabilized in Rust 1.85, so lift the workspace MSRV one more step. The
1.85 floor subsumes the rayon-core 1.80 requirement; bindings/node
stays at 1.88 (napi-build) which already covers everything below it.
Also fix the fuzz job: cargo-fuzz defaulted to building for
x86_64-unknown-linux-musl, which is not installed on the GitHub-hosted
ubuntu runner. Pass --target x86_64-unknown-linux-gnu explicitly on
every cargo fuzz run invocation so it builds for the actual host
target.
The previous MSRV pins were below what current transitive dependencies
need:
- rayon-core 1.13.0 (pulled in by the optional `parallel` feature on
wickra-core via rayon) requires rustc >= 1.80; under the old 1.75
workspace MSRV the CI MSRV job broke with "package `rayon-core
v1.13.0` cannot be built because it requires rustc 1.80 or newer".
- napi-build 2.3.2 (the build-script crate that napi-derive 2.x calls
into) requires rustc >= 1.88; under the old 1.77 node-binding MSRV
the CI MSRV-node job broke with "package `napi-build v2.3.2` cannot
be built because it requires rustc 1.88 or newer".
Pinning the deps backwards would have frozen us out of upstream
security/fix releases for both crates. Lifting the MSRV is the cleaner
path for a young 0.x library — downstream consumers on older toolchains
can stay on the already-published 0.2.0.
Updated:
- Cargo.toml workspace rust-version 1.75 -> 1.80
- bindings/node/Cargo.toml rust-version 1.77 -> 1.88
- .github/workflows/ci.yml MSRV matrix names + toolchain values + comment
- CHANGELOG.md [Unreleased] documents the bump
The previous `cargo install cargo-fuzz --locked` resolved against
cargo-fuzz's own Cargo.lock which pins to rustix 0.36.5. That rustix
version still annotates its source with internal #[rustc_*] attributes,
and the current nightly compiler rejects those attributes from
out-of-tree crates, so cargo-fuzz never finished compiling on CI:
error: attributes starting with `rustc` are reserved for use by the
`rustc` compiler
--> rustix-0.36.5/src/backend/linux_raw/io/errno.rs:28
error: could not compile `rustix` (lib) due to 4 previous errors
error: failed to compile `cargo-fuzz v0.13.1`
Switch the install to taiki-e/install-action, the same prebuilt-binary
provider we already use for cargo-llvm-cov. That skips the full
transitive-dependency compile and lets the fuzz-smoke job actually run.
The Z5 reorganisation moved every runnable example out of the per-crate
examples/ folders and into a dedicated wickra-examples crate at
examples/rust/, with the binaries living under src/bin/<name>.rs. The
old ci.yml Compile-examples step still pointed at the now-deleted
cargo example targets backtest (wickra) and live_binance (wickra-data),
which is why Rust windows-latest failed with 'no example target named
backtest in wickra package' and 'no example target named live_binance
in wickra-data package'.
Replace both calls with a single cargo build -p wickra-examples --bins.
That covers backtest, live_binance, fetch_btcusdt, multi_timeframe,
parallel_assets and streaming in one shot, and the wickra-examples
crate already enables the live-binance feature on its wickra-data dep
so no extra --features flag is needed.
R10 — `cross-library-bench` previously ran on every push and every PR
to `main`, adding 5–10 minutes of build + bench time per CI run with
no automated consumer of the artefact. It moves to a dedicated
workflow (`.github/workflows/bench.yml`) that fires nightly at 03:00
UTC and on-demand via `workflow_dispatch` (with optional `size` /
`iterations` inputs). The job in `ci.yml` is removed and a pointer
comment is left in its place so future readers find the new home.
R11 — `pyproject.toml`'s `requires-python = ">=3.9"` already allowed
Python 3.13 installs, but the classifier list stopped at 3.12 and CI
tested only 3.9 / 3.11 / 3.12. The Python CI matrix gains `"3.13"`
and the matching `Programming Language :: Python :: 3.13` classifier
is added so PyPI listings and version-search tooling reflect the
actually-tested range.
The fuzz suite previously covered only `Rsi(14)` and `Ema(20)` — 2 of
71 indicators, no OHLCV coverage at all. Audit finding R9 asked for
ATR/ADX/Stochastic/PSAR as a minimum; this commit goes further and
brings every indicator under fuzz.
- `indicator_update` (rewritten): drives every scalar-input indicator
through one streaming pass + one batch call per iteration. Covers
SMA, EMA, WMA, RSI, DEMA, TEMA, HMA, ROC, TRIX, SMMA, TRIMA, ZLEMA,
KAMA, T3, MOM, CMO, TSI, PMO, StochRSI, DPO, PPO, Coppock, StdDev,
UlcerIndex, HistoricalVolatility, LinearRegression, LinRegSlope,
LinRegAngle, VHF, ZScore, MACD, BollingerBands. A `drive` helper
marked `#[inline(never)]` keeps each indicator on its own panic
backtrace frame.
- `indicator_update_candle` (new): chunks the fuzz `f64` stream into
`[open, high, low, close, volume]` tuples, builds candles via
`Candle::new` (skipping ones that fail OHLCV validation — that path
is fuzz-tested separately), then drives every candle-input indicator
through streaming + batch. Covers ATR, NATR, TrueRange,
ChaikinVolatility, Keltner, Donchian, PSAR, SuperTrend,
ChandelierExit, ChandeKrollStop, ATRTrailingStop, ADX, Aroon,
AroonOscillator, Vortex, MassIndex, ChoppinessIndex, CCI, WilliamsR,
AwesomeOscillator, AcceleratorOscillator, UltimateOscillator,
BalanceOfPower, OBV, MFI, VWAP, RollingVWAP, VWMA, ADL, VPT, CMF,
ChaikinOscillator, ForceIndex, EaseOfMovement, TypicalPrice,
MedianPrice, WeightedClose, Stochastic.
- `fuzz/Cargo.toml` registers the new target; `fuzz/README.md`
describes both expanded targets.
- A `fuzz-smoke` CI job runs each of the five targets for 30 s on
every push and pull-request — enough to catch a regression in the
harness without slowing CI to a crawl. Long fuzz campaigns belong
on dedicated infrastructure with persistent corpora.
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.
The repository had no supply-chain auditing — no deny.toml and no CI
job to catch vulnerable, unmaintained, wrongly-licensed, or
unexpectedly-sourced dependencies.
Add deny.toml covering advisories, bans, licenses and sources:
- licenses: an allow-list of the permissive licenses the dependency
tree actually uses, plus the workspace's own PolyForm-Noncommercial
license and a scoped LLVM-exception for target-lexicon.
- bans: warn on duplicate versions, deny external wildcard deps
(internal path deps are allowed).
- sources: only crates.io.
- advisories: RUSTSEC-2025-0020 (pyo3 0.22) is ignored with a documented
reason — it is reachable only through bindings/python and the pyo3
upgrade is tracked separately; the published crates do not use pyo3.
Add a `supply-chain` CI job running cargo-deny-action (SHA-pinned).
`cargo deny check` passes locally: advisories/bans/licenses/sources ok.
Every CI job used dtolnay/rust-toolchain on stable, so the declared
minimum supported Rust version was never exercised — an accidental use
of a newer API would only break for downstream users on an older
compiler.
Add an `msrv` job with a two-row matrix: the workspace crates
(wickra-core, wickra, wickra-data) build and test on Rust 1.75, and the
node binding on Rust 1.77, matching the rust-version each manifest
declares. Both rows use the SHA-pinned toolchain action.
Every action in ci.yml and release.yml was pinned to a movable tag
(actions/checkout@v4, dtolnay/rust-toolchain@stable, ...). A compromised
upstream tag would run with access to the crates.io / PyPI / npm
publish tokens.
Pin every `uses:` to the full 40-character commit SHA the referenced
ref currently resolves to, with the human-readable version kept as a
trailing comment so Dependabot can still bump them:
actions/checkout v4.3.1
actions/setup-python v5.6.0
actions/setup-node v4.4.0
actions/upload-artifact v4.6.2
actions/download-artifact v4.3.0
dtolnay/rust-toolchain stable branch @ 2026-03-27
Swatinem/rust-cache v2
jetli/wasm-pack-action v0.4.0
PyO3/maturin-action v1.51.0
softprops/action-gh-release v2.6.2
SHAs were resolved against the GitHub API. The github-actions Dependabot
ecosystem that keeps these pins current is added with E3.
The WASM binding had no tests; CI only checked that artefacts existed.
Adds a wasm-bindgen-test suite covering SMA reference values, EMA
batch==streaming equivalence, RSI pure-uptrend behaviour, fallible
constructors returning JsError, and the unequal-length batch guards from
B3. Wires wasm-pack test --node into the CI wasm job. The suite
type-checks on the host; it executes under wasm-pack in CI (the local
environment is a non-rustup Rust install without the wasm32 target).
The Windows Node 18 and Node 20 CI jobs failed because:
- ci.yml ran 'napi build --release' (no --platform), which produces a
filename without the target triple ('wickra.node').
- The committed loader at bindings/node/index.js looked for the
triple-suffixed file ('wickra.win32-x64-msvc.node') and then for the
per-platform npm subpackage as a fallback.
- 'wickra-win32-x64-msvc' isn't on npm yet (blocked by the spam filter),
so Windows had nothing to load. Linux and macOS passed only because
their optionalDependencies do exist on npm and got fetched.
Two-part fix:
- ci.yml now runs 'napi build --platform --release', matching release.yml.
--platform encodes the target triple in the filename, so the loader's
primary lookup always finds the freshly built binary on every host.
- bindings/node/index.js is now the canonical napi-rs auto-generated
loader (it gets regenerated by 'napi build'). It covers all the platforms
napi knows about (linux glibc/musl, Android, FreeBSD, ARM, etc.) rather
than just the four we publish, so unsupported platforms get a clear
'this binding isn't built for your system' error instead of a confusing
ENOENT.
Local sanity: 'npx napi build --platform --release' then 'node --test
__tests__/' succeeds end to end on Windows; the eight existing tests
pass.
Two unrelated failures in the post-release CI run:
- Python jobs: `maturin develop` requires an activated virtualenv on
CI runners that don't have a system Python set up that way. Switch
to `maturin build --release --out dist` followed by `pip install
--find-links dist`, which is venv-agnostic and OS-portable.
- WASM job: the wasm-opt bundled with wasm-pack is older than the WASM
features rustc 1.92 enables by default. The fix is to opt every feature
in explicitly via the package metadata — reference-types, multivalue,
bulk-memory, sign-ext, mutable-globals, nontrapping-float-to-int — so
wasm-opt accepts the input.
Same code as before; only the build steps and the wasm-opt config changed.
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