Files
wickra/bindings/python
kingchenc 8228be7069 python: drop the NumPy runtime dependency (zero third-party deps) (#317)
Makes the Python binding truly dependency-free (Task 5b). `pip install wickra` now pulls **zero** third-party packages, and `import wickra` never imports NumPy (verified: `"numpy" not in sys.modules` after a batch call).

## What changed
- **Inputs** accept any sequence or buffer of numbers — `array.array`, `memoryview`, a NumPy `ndarray`, or a plain `list` — via `Vec` extraction (newtypes `Buf1`/`BufI64`). `PyBuffer` is unavailable under `abi3-py39`, and `unsafe_code = forbid` rules out a zero-copy slice, so inputs are copied once (negligible vs. compute).
- **Single-output `batch(...)`** returns a stdlib `array.array('d')` (native buffer protocol → `numpy.asarray` zero-copy).
- **Multi-output `batch(...)`** returns a buffer-protocol `Matrix` preserving `.shape`, integer-row and `[i, j]` access, and `.tolist()`.
- **NumPy** moves to an optional extra (`pip install wickra[numpy]`); it is never required.
- Streaming `update(...)` is unchanged; results are numerically identical.

## Implementation
- Trait `IntoPyData` + a `matrix()`/`f64_array()` helper collapse the ~400 batch call sites; `array.array` is built via `bytemuck` (Zlib/MIT/Apache — `cargo deny check licenses` ok).
- Tests migrated to `array.array`/`Matrix` (1-D `.shape`→`len()`, `.dtype`→`.typecode`; numeric comparisons normalize through a `_to_np` helper). The non-contiguous-input test now asserts acceptance instead of rejection.

## Verification (local)
- `pytest bindings/python/tests` — **1991 passed**.
- `cargo fmt --all`, `cargo clippy --workspace --all-targets --all-features -- -D warnings`, `cargo test --workspace --all-features`, `cargo deny check licenses` — all green.

**BREAKING for Python**: batch return types change from NumPy arrays to `array.array`/`Matrix`. Documented in CHANGELOG; ships with the data-layer release bundle (no separate tag).
2026-06-17 03:19:50 +02:00
..

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 WASM, 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 all 514 streaming-first indicators across twenty-four 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:

Wickra ships native bindings for Python, Node.js, WASM and Rust, plus a C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against — all exposing the same indicators from the shared, unsafe-forbidden Rust core.

Security

Found a security issue? Please don't open a public issue. Report it privately via the affected repository's Security tab ("Report a vulnerability") or email support@wickra.org with a subject line starting [wickra security]. Full policy: https://github.com/wickra-lib/wickra/blob/main/SECURITY.md.

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.