Files
wickra/bindings/python
kingchenc 4250ed99f4 feat(patterns): add the Harmonic Patterns family (8 XABCD detectors) (#169)
## Summary

Adds a new **Harmonic Patterns** indicator family (counter 359 → 367, families 22 → 23) — the second half of the A4 roadmap item, following the Chart Patterns family in #166.

Eight Fibonacci-ratio detectors built on the shared swing-pivot tracker (`indicators::pattern_swing`) plus two new helpers there — `xabcd` (reads the last five pivots as X-A-B-C-D) and `ratios_in` (checks a list of `(value, low, high)` Fibonacci windows in one expression, no multi-line `&&` coverage gaps). Each consumes candles and emits the uniform pattern sign convention — `+1.0` bullish (terminal point D a swing low), `-1.0` bearish (D a swing high), `0.0` otherwise, never `None`. Parameter-free, with the Fibonacci windows documented as constants per detector.

## Detectors

| Indicator | Defining ratio |
|-----------|----------------|
| `Abcd` | four-point AB=CD (BC retraces AB, CD ≈ AB) |
| `Gartley` | AD/XA ≈ 0.786 |
| `Butterfly` | AD/XA ∈ 1.27–1.618 (extended D) |
| `Bat` | AD/XA ≈ 0.886, shallow B |
| `Crab` | AD/XA ≈ 1.618 (deepest D) |
| `Shark` | expansion AB, AD/XA 0.886–1.13 |
| `Cypher` | BC on XA, CD/XC ≈ 0.786 |
| `ThreeDrives` | two symmetric extension drives |

## Touchpoints

Core modules + `FAMILIES` group/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 (`// --- Harmonic Patterns ---` section), 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` — 2966 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` — 444 passed
- Python `maturin develop --release` + `pytest` — 748 passed

Every detector branch is unit-tested, including a bullish and a bearish match per pattern to cover both output arms, plus an out-of-ratio non-match. Fibonacci windows use standard harmonic-trading ranges with documented tolerance bands.
2026-06-03 23:24:25 +02:00
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Wickra — Python

CI codecov PyPI License: MIT OR Apache-2.0

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:

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.