Explore the insights gleaned from analyzing 750 billion GitHub events and 42 TB of code in this comprehensive conference talk. Dive into the world of open-source software development, examining coding patterns, project design decisions, and community dynamics. Learn how to leverage data to guide feature requests, measure community health, and understand the effects of social media on project popularity. Discover the most effective ways to phrase change requests and gain insights into who stars projects and their interests. Delve into static code analysis at scale, addressing age-old debates like tabs vs. spaces. Through live on-stage analysis, uncover valuable information about GitHub metadata, coding trends, and the evolution of software development practices over the past five years.
What Can We Learn from 750 Billion GitHub Events and 42 TB of Code
Overview
Syllabus
Introduction
Who is this data for
GitHub stars
Comparing freecode and tensorflow
Looking at issues and comments
How to start an issue
Data analysis
Top projects
Code
Top imports
Stack Overflow
Feature Requests
Code Analysis
Leading and trailing commas
Conclusion
Running queries
Taught by
NDC Conferences
