kingchenc
995f119010
## Summary Adds a new **Chart Patterns** indicator family (counter 351 → 359, families 21 → 22), the first half of the A4 roadmap item (the harmonic patterns follow in a second PR). All eight detectors are built on a shared, non-repainting swing-pivot tracker — the internal, **uncounted** `indicators::pattern_swing` module (declared `pub(crate) mod`, re-exported nowhere). Each consumes candles and emits the uniform pattern sign convention already used by the candlestick family — `+1.0` bullish / `-1.0` bearish / `0.0` otherwise, never `None`. They are parameter-free, baking the swing threshold (5%) and level tolerance (3%) in as documented constants, mirroring how candlestick patterns bake in their geometric thresholds. ## Detectors | Indicator | Signal | |-----------|--------| | `DoubleTopBottom` | twin-peak / twin-trough reversal | | `TripleTopBottom` | three matching extremes (stronger reversal) | | `HeadAndShoulders` | central head + matching shoulders + flat neckline (and inverse) | | `Triangle` | ascending (+1) / descending (-1) / symmetrical | | `Wedge` | rising wedge (-1) / falling wedge (+1) | | `FlagPennant` | shallow consolidation against a pole → continuation | | `RectangleRange` | flat support/resistance mean-reversion | | `CupAndHandle` | rounded base + shallow handle (and inverse) | ## Touchpoints Core modules + `FAMILIES` group and assert, crate root re-exports, Python/Node/WASM bindings via the candle-pattern macros (Node `index.d.ts`/`index.js` regenerated), the candle fuzz target, Python reference + `CANDLE_SCALAR` registry tests and the Node candle-scalar factory, README catalogue counter + banner cache-buster + family table row + family-count word, `docs/README.md` counter, and the changelog. ## Verification - `cargo test -p wickra-core --lib` — 2915 passed - `cargo test -p wickra-core --doc` — 335 passed - `cargo clippy --workspace --all-targets --all-features -- -D warnings` — clean - Node `npm run build && npm test` — 436 passed - Python `maturin develop --release` + `pytest` — 732 passed Every detector branch is unit-tested; multi-condition predicates were flattened to single-line precomputed booleans to keep patch coverage at 100%.
Wickra — Python
Streaming-first technical indicators for Python. pip install wickra — no
system dependencies, no C build tooling.
Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1) streaming state machine, so live trading bots and historical backtests share the exact same implementation. This package is the Python binding (PyO3); it exposes 200+ streaming-first indicators across sixteen families.
Install
pip install wickra
Pre-built wheels ship for Linux, macOS, and Windows — there is nothing to compile and no C library to track down.
Quick start
import numpy as np
import wickra as ta
# Batch: classic TA-Lib-style usage over a whole array.
prices = np.linspace(100, 200, 1000)
rsi = ta.RSI(14)
values = rsi.batch(prices) # numpy array, NaN during warmup
# Streaming: the same indicator, fed tick by tick in O(1).
rsi = ta.RSI(14)
for price in live_feed:
value = rsi.update(price) # no recomputation over history
if value is not None and value > 70:
print("overbought")
batch(prices) and feeding the same prices through update() produce
identical values — the equivalence is enforced by the test suite.
Documentation
The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:
- Repository & full indicator list: https://github.com/wickra-lib/wickra
- Docs (quickstarts, cookbook, TA-Lib migration): https://docs.wickra.org
- Runnable examples:
examples/python/
Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
expose the same indicators from the shared, unsafe-forbidden Rust core.
Disclaimer
Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.
License
Licensed under either of Apache-2.0 or MIT at your option.