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<p align="center"><a href="https://github.com/Renumics/sliceguard"><img src="https://github.com/Renumics/sliceguard/raw/main/static/img/sliceguard.svg" alt="Sliceguard Logo" height="80"/></a></p> <h1 align="center">sliceguard</h1> <p align="center">Detect problematic data slices in unstructured and structured data – fast.</p> <p align="center"> <a href="https://pypi.org/project/sliceguard/"><img src="https://img.shields.io/pypi/pyversions/sliceguard" height="20"/></a> <a href="https://pypi.org/project/sliceguard/"><img src="https://img.shields.io/pypi/wheel/sliceguard" height="20"/></a> <a href="https://sliceguard.readthedocs.io/en/latest/index.html"><img src="https://readthedocs.org/projects/sliceguard/badge/?version=latest&amp;style=flat" height="20"></a> </p> <p align="center"><img src="https://github.com/Renumics/sliceguard/raw/main/static/img/sliceguard_github.gif" width="100%"/><img src="https://github.com/Renumics/sliceguard/raw/main/static/img/dropshadow.png" width="100%"/></p>

πŸš€ Introduction

Sliceguard helps you to quickly discover problematic data segments. It supports structured data as well as unstructured data like images, text or audio. Sliceguard generates an interactive report with just a few lines of code:

from sliceguard import SliceGuard

sg = SliceGuard()
issues = sg.find_issues(df, features=["image"])

sg.report()

⏱️ Quickstart

Install sliceguard by running pip install sliceguard[all].

Go straight to our quickstart examples for your use case:

πŸ—ΊοΈ Public Roadmap

We maintain a public roadmap so you can follow along the development of this library.