Gitinspector: A Glimpse into Git Repo Statistics—Old but Gold!

Gitinspector: A Glimpse into Git Repo Statistics—Old but Gold!

Table of Content

Gitinspector is a statistical analysis tool for git repositories. The default analysis shows general statistics per author, which can be complemented with a timeline analysis that shows the workload and activity of each author.

It offers a breakdown of contributions by author, lines added or removed, file types modified, and more. Gitinspector can generate reports in formats like HTML, making it useful for those who want an easy overview of their repository activity.

Under normal operation, it filters the results to only show statistics about a number of given extensions and by default only includes source files in the statistical analysis.

This tool was originally written to help fetch repository statistics from student projects in the course Object-oriented Programming Project (TDA367/DIT211) at Chalmers University of Technology and Gothenburg University.

Features

  • Shows cumulative work by each author in the history.
  • Filters results by extension (default: java,c,cc,cpp,h,hh,hpp,py,glsl,rb,js,sql).
  • Can display a statistical timeline analysis.
  • Scans for all filetypes (by extension) found in the repository.
  • Multi-threaded; uses multiple instances of git to speed up analysis when possible.
  • Supports HTML, JSON, XML and plain text output (console).
  • Can report violations of different code metrics.

License

gitinspector is licensed under the GNU GPL v3. The gitinspector logo is partly based on the git logo; based on the work of Jason Long. The logo is licensed under the Creative Commons Attribution 3.0 Unported License.

Resources

GitHub - ejwa/gitinspector: :bar_chart: The statistical analysis tool for git repositories
:bar_chart: The statistical analysis tool for git repositories - ejwa/gitinspector







Open-source Apps

9,500+

Medical Apps

500+

Lists

450+

Dev. Resources

900+

Read more

Bias in Healthcare AI: How Open-Source Collaboration Can Build Fairer Algorithms for Better Patient Care

Bias in Healthcare AI: How Open-Source Collaboration Can Build Fairer Algorithms for Better Patient Care

The integration of artificial intelligence (AI), particularly large language models (LLMs) and machine learning algorithms, into healthcare has transformed the industry dramatically. These technologies enhance various aspects of patient care, from diagnostics and treatment recommendations to continuous patient monitoring. However, the application of AI in healthcare is not without challenges.