kingchenc
03ceac1f3b
* feat: add Abandoned Baby candlestick pattern (CDLABANDONEDBABY) * feat: add Advance Block candlestick pattern (CDLADVANCEBLOCK) * feat: add Belt Hold candlestick pattern (CDLBELTHOLD) * feat: add Breakaway and Counterattack candlestick patterns (CDLBREAKAWAY, CDLCOUNTERATTACK) Breakaway is a 5-bar reversal: a trend gaps away on the second bar, drifts two more bars, then the fifth bar snaps back and closes inside the bar1/bar2 body gap (bullish +1, bearish -1). Counterattack is a 2-bar reversal where an opposite-coloured long second bar closes level with the first (the counterattack line; bullish +1, bearish -1). Also suppress libtest's spanless `large_stack_arrays` false positive in wickra-core test builds: the `#[test]` harness collects every test into a compiler-generated array of references that crosses clippy's 16 KB threshold once the suite passes ~2048 unit tests. The allow is scoped to `cfg(test)`, so library code is still linted for genuinely large stack arrays. * chore: sync indicator count to 254 --------- Co-authored-by: wickra-bot <wickra-bot@users.noreply.github.com>
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 the PolyForm Noncommercial License 1.0.0. Personal projects, research, education, non-profits, and hobby trading bots are all fine; the one thing not allowed is commercial sale of the software or of services built around it. See LICENSE.