Python Insights: Line Lengths, NumPy Trends, and Growth

Exploring Modern Python Development

In this episode of Python Bytes, hosts Michael Kennedy and Brian Akin dive into a variety of topics ranging from software engineering best practices to the evolving landscape of major data science libraries.

Key Discussion Points

• Line Length Standards: The hosts discuss the ongoing debate regarding PEP-8's 79-character limit versus more modern, permissive standards. They highlight an insightful Jupyter Notebook article by Jake VanderPlas, which uses data analysis to observe the distribution of line lengths across popular Python packages.
• NumPy's Path Forward: There is significant news regarding NumPy's decision to drop support for legacy Python 2 by 2019. This transition is framed as a necessary step to reduce technical debt and accelerate library innovation.
• Learning Data Science Tooling: The episode covers effective strategies for learning Pandas, moving beyond simple API exploration to utilizing real-world datasets, Kaggle kernels, and engaging with expert communities like Stack Overflow.

Advancements in Infrastructure and Growth

"The hardest thing about making something successful... is getting people to notice it in a busy world."

• Git Virtual File System (GVFS): An exploration of the collaboration between Microsoft and GitHub to address performance bottlenecks in massive repositories, introducing a virtual file system that drastically improves operations like clone and status for huge projects.
• Managing Dependencies: A walkthrough on setting up DevPy servers to cache local packages efficiently, an essential practice for secure enterprise environments behind firewalls.
• Engineering Marketing: The hosts highlight the Marketing for Engineers repository, a curated resource designed to help technical teams grow their user base via non-scalable, grass-roots efforts.