wickra/bindings/python

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, plus a C ABI for C/C++, C#, Go, Java, R and any other C-capable language. 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.

Benchmark

Two benchmarks ship with the binding:

• benchmarks/throughput.py — streaming and batch updates-per-second for SMA, ATR and MACD. This is per-binding FFI overhead (the same Rust core runs under every binding), not a cross-library ratio.
• benchmarks/compare_libraries.py — the cross-library comparison against TA-Lib, pandas-ta, tulipy and finta that backs the headline speedups.

maturin develop --release
python -m benchmarks.throughput
python -m benchmarks.compare_libraries   # cross-library; auto-detects installed peers

See the repository BENCHMARKS.md.

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 native bindings for Python, Node.js, WebAssembly and Rust, plus a C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against — all exposing 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.