Knowledge Islands

Knowledge Islands

In software development, it’s all about knowledge – both technical and the business domain. But we software developers transfer only a small part of this knowledge into code. But code alone isn’t enough to get a glimpse of the greater picture and the interrelations of all the different concepts. There will be always developers that know more about some concept as laid down in source code. It’s important to make sure that this knowledge is distributed over more than one head…

Reading a Git repo’s commit history with Pandas efficiently

Reading a Git repo’s commit history with Pandas efficiently

There are multiple reasons for analyzing a version control system like your Git repository. See for example Adam Tornhill’s book “Your Code as a Crime Scene” or his upcoming book “Software Design X-Rays” for plenty of inspirations:

You can analyze knowledge islands, distinguish often changing code from stable code parts, identify code that is temporal coupled to other code.

Having the necessary data for those analyses in a Pandas DataFrame gives you many possibilities to quickly gain insights into the evolution of your software system in various ways…

Storing Git commit information into Pandas’ DataFrame

Storing Git commit information into Pandas’ DataFrame

Software version control systems contain a huge amount of evolutionary data. It’s very common to mine these repositories to gain some insight about how the development of a software product works. But there is the need for some preprocessing of that data to avoid false analysis.

That’s why I show you how to read the commit information of a Git repository into Pandas’ DataFrame!