Kedro
Python framework for reproducible, maintainable data science pipelines.
About
Kedro is an open-source Python framework for building production-ready data engineering and data science pipelines. It enforces software engineering best practices — modular nodes, versioned datasets, experiment tracking, and project templating — so ML pipelines stay reproducible as teams grow.
It is hosted by the LF AI & Data Foundation and installs from PyPI. While it predates the LLM boom, it remains a standard choice for structuring training and evaluation data workflows.
What it can do
- Modular pipeline nodes and catalogs
- Versioned, reproducible datasets
- Experiment tracking integration
- LF AI & Data hosted open source
Setup
pip install kedro (or uv pip install kedro), then kedro new to scaffold a project.
Prerequisites
Python 3.9+ and familiarity with Python data tooling.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 76; Trending score 72/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.