commit-classification VS pydriller

Compare commit-classification vs pydriller and see what are their differences.

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commit-classification pydriller
5 2
16 797
- -
5.0 7.1
2 months ago 5 months ago
Python Python
- Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

commit-classification

Posts with mentions or reviews of commit-classification. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-24.

pydriller

Posts with mentions or reviews of pydriller. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-25.

What are some alternatives?

When comparing commit-classification and pydriller you can also consider the following projects:

Software-Development-Project-Structure - This repository has the purpose of creating a hierarchical tree file organization system standard for small to medium size projects. Each folder sorted by the programming language will contain a file structure template that can be cloned or downloaded to start new projects. I have come to a project structure that shall avoid confusion being as simple as possible and should keep your code clean, neat, structured, and clutter free. The file structure system is modular and suited to modern standards, therefore you can add or remove files and folders to tailor it to a particular project or task. Each folder has its own explanation in this guide and more documentation in the folder itself.

git-sim - Visually simulate Git operations in your own repos with a single terminal command.

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.

kopf - A Python framework to write Kubernetes operators in just a few lines of code