xileh 0.2.1

A lightweight, composable pipeline abstraction built around a hierarchical data container.

xileh

A lightweight, composable pipeline abstraction built around a hierarchical data container.

Overview

xileh abstracts complex processing pipelines, motivated by sklearn.Pipeline but with data capacities going beyond a feature matrix X and target y. It is built from two components:

• xData — a hierarchical container holding data, a header (description / control flags), and meta information. It can nest other xData objects to pass multiple data entities through a pipeline.
• xPipeline — an ordered set of plain Python functions, each taking and returning an xData object.

Why build something new?

Placing libraries on two axes — built-in functionality and specificity / restrictions — xileh deliberately aims for minimal built-in functionality and maximal freedom of customization.

sklearn.Pipeline is great for ML pipelines but specific about data shape and the fit/transform contract. Config-driven tools like hydra provide a single source of truth but impose a format that can hinder rapid prototyping. xileh instead:

• imposes as few restrictions on your workflow as possible (arbitrary data objects and plain Python functions),
• integrates easily with a function-based workflow during development,
• provides a single source of truth for the processing,
• enables reuse of whole pipelines by strongly motivating composition.

Installation

pip install xileh

The bare install is lite (numpy only). Optional data backends are available as extras:

pip install xileh[pandas]   # pandas DataFrame/Series save & load (parquet)
pip install xileh[polars]   # polars DataFrame/Series save & load (parquet)

Saving or loading a container that holds a backend-specific type without the corresponding extra installed raises an error pointing at the extra to install.

Or from source:

git clone [e-mail]:matthiasdold/xileh.git
cd xileh
pip install -e .

xileh targets Python 3.11+.

Quick example

from xileh import xData, xPipeline


def add_ones(pdata, name="ones", size=3):
    pdata.add([1] * size, name=name)
    return pdata


pl = xPipeline("demo")
pl.add_steps(("add_ones", add_ones))

root = xData([], name="root")
pl.eval(root)

The container was renamed from xPData to xData; xPData remains available as a backwards-compatible alias.

Documentation

Full documentation, including a quick-start guide, worked examples, and the API reference, is available at matthiasdold.github.io/xileh.

License

MIT