Pynblint: a Static Analyzer for Python Jupyter Notebooks

TL;DR

Pynblint is a static analysis tool designed to improve the quality of Jupyter notebooks by checking for adherence to best practices and providing actionable recommendations.

Contribution

It introduces a static analyzer specifically for Jupyter notebooks that enforces empirically validated best practices to enhance code quality.

Findings

Detects common bad practices in notebooks

Provides targeted recommendations for improvements

Helps improve reproducibility and maintainability

Abstract

Jupyter Notebook is the tool of choice of many data scientists in the early stages of ML workflows. The notebook format, however, has been criticized for inducing bad programming practices; indeed, researchers have already shown that open-source repositories are inundated by poor-quality notebooks. Low-quality output from the prototypical stages of ML workflows constitutes a clear bottleneck towards the productization of ML models. To foster the creation of better notebooks, we developed Pynblint, a static analyzer for Jupyter notebooks written in Python. The tool checks the compliance of notebooks (and surrounding repositories) with a set of empirically validated best practices and provides targeted recommendations when violations are detected.