lilpipe 0.1.4

A tiny, typed, sequential pipeline engine for Python

lilpipe

A tiny, typed, sequential pipeline engine for Python.

lilpipe is a lightweight, Pydantic-powered library for building and running sequential workflows in Python. It’s ideal for data processing, scientific workflows, and any task that benefits from a clear, linear sequence of steps. With built-in caching and simple control signals, lilpipe is small, typed, and practical.

Features

• Sequential workflows — run steps in a fixed order.
• Type-safe context — Pydantic-based PipelineContext.
• Smart caching — fingerprint_keys to skip unchanged work.
• Flow control — ctx.abort_pass() and ctx.abort_pipeline().
• Composable steps — nest via Step(name, children=[...]).
• Tiny surface area — minimal API and dependencies.

Installation

pip install lilpipe

See pyproject.toml for supported Python versions.

Example Notebook

The full, runnable demo lives here:

• examples/example.ipynb (in repo): https://github.com/andrewruba/lilpipe/blob/HEAD/examples/example.ipynb

• nbviewer (rendered view): https://nbviewer.org/github/andrewruba/lilpipe/blob/HEAD/examples/example.ipynb

• Google Colab (optional): https://colab.research.google.com/github/andrewruba/lilpipe/blob/HEAD/examples/example.ipynb Tip: in Colab, add a cell !pip install lilpipe before running the notebook.

License

Licensed under the Apache 2.0 License.

Links

• Issues: https://github.com/andrewruba/lilpipe/issues
• PyPI: https://pypi.org/project/lilpipe/