volas 0.0.0

High-performance, Rust-backed columnar kernel for stock / candlestick (OHLCV) time-series data.

volas

High-performance, Rust-backed columnar kernel for stock / candlestick (OHLCV) time-series data.

Status: early development — version 0.0.0. APIs are not yet stable and may change at any time.

What is volas?

volas is a focused, DataFrame-like data structure purpose-built for financial candlestick (OHLCV) time series and quantitative-trading workflows.

Rather than being a general-purpose DataFrame, volas supports only what this domain needs — a time-indexed, two-dimensional table of numeric and boolean columns — and implements its storage and compute core in Rust for low, predictable latency on incremental ("append one bar") workloads.

Goals

• Live-trading first — optimized for the incremental hot path: append a new bar, update indicators, read the result, with minimal per-bar latency.
• Small, regular data model — a time index plus 2-D columns of numbers and booleans; no multi-level indexes, no heterogeneous storage, no general-purpose reshaping.
• Rust core — storage and computation live in a compiled Rust extension.
• First-class NumPy interop — zero-copy to_numpy export, designed so data flows cheaply into NumPy and torch.Tensor for both training and inference.

Installation

Not yet published to PyPI. For a local build, see Development.

pip install volas

Requires Python >= 3.11.

Usage

Preview of the intended API. Not yet implemented at 0.0.0; subject to change.

from volas import Volas

v = Volas({
    'open':   [...],
    'high':   [...],
    'low':    [...],
    'close':  [...],
    'volume': [...],
})

# Zero-copy export to NumPy (where possible)
close = v['close'].to_numpy()
matrix = v.to_numpy()

Development

Requires Python >= 3.11 and a Rust toolchain.

# Build the Rust extension and install the package in-place (development)
make build

# Build a release wheel + sdist into dist/
make build-pkg

# Publish to PyPI (build + upload)
make publish

License

MIT