Skip to content

Inhibits commits with bad messages from getting merged

License

Notifications You must be signed in to change notification settings

CELLINKAB/bad-commit-message-blocker

 
 

Repository files navigation

Bad Commit Message Blocker Build Status

A simple script, doing some natural language processing, to inhibit git commits with bad messages from getting merged.

screenshot

What?

A Python3 script, easy to integrate with various CI machinery (e.g. see TravisCI example) that is meant to keep bad commit messages out of a project. It verifies whether the seven rules of a great Git commit message by Chris Beams, are being followed:

  1. Separate subject from body with a blank line
  2. Limit the subject line to 50 characters
  3. Capitalize the subject line
  4. Do not end the subject line with a period
  5. Use the imperative mood in the subject line
  6. Wrap the body at 72 characters
  7. Use the body to explain what and why vs. how

Why?

The more a project grows in contributors and size, the more important the quality of its commit messages becomes.

It is ultimately hard to quantify what makes a good commit message. However, we can easily determine automatically whether it adheres to most of the git commit message best practices. Having a script to automatically verify that, aside of other rules that you might already enforce (e.g. checking whether a task or a requirement is referenced) can save a lot of time in the long run as well as even avoid conflicts between the reviewer(s) and the reviewee.

After adopting this script, what you get is a set of best practices, agreed upon by the project and automatically applied. This way, everyone has to follow them or CI will not allow that commit in. Simple as that! 😇

How?

Most of the rules are trivial to implement in code, except two of them, no. 5 and no. 7. Specifically, checking whether the commit subject begins with imperative mood is tricky due to limitations of the Natural Language Processing libraries being utilized. You can read more about the constraints here. Essentially, it boils down to the lack of many imperative sentences existing in the datasets used when training the relevant statistical models. Subsequently, the enforcement of this rule might produce some false positive and false negative errors.

On the other hand, verifying whether the commit body actually explains what and why instead of how is not (?) possible, due to the subjective nature of the problem. All in all, in most cases, this is all the reviewers would have to do themselves manually, to ensure the quality of a commit message.

Get started

You need to have Python3 installed and follow the steps bellow:

  • Install TextBlob
    • pip3 install --user textblob
  • Install NLTK corpora
    • python3 -m textblob.download_corpora
  • Run the script to verify a commit message
    • python3 bad_commit_message_blocker.py --message "Add a really cool feature"
  • To define your own maximum character limits, call the script with the appropriate arguments:
    • --subject-limit (defaults to 50) to set the subject line limit. E.g.:
      • python3 bad_commit_message_blocker.py --subject-limit 80 --message "Add a really cool feature"
    • --body-limit (defaults to 72) to set the body line limit. E.g.:
      • python3 bad_commit_message_blocker.py --body-limit 120 --message "Add a really cool feature"

About

Inhibits commits with bad messages from getting merged

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 95.6%
  • Shell 4.4%