Using Git tags for data science

Tagging in Git is a way to mark specific points in your repository’s history as being important. Typically, people use this functionality to mark release points (v1.0, v2.0, and so on). In this section, we’ll cover the concept of tagging and how it can benefit data scientists.

Understanding Git tags

There are two types of tags that Git recognizes, lightweight and annotated. A lightweight tag is similar to a branch that doesn’t change. It’s just a pointer to a specific commit. Annotated tags, however, are stored as full objects in the Git database. Using the annotated tag is generally recommended because it is fully tracked and contains more info than the lightweight tag.

To create an annotated tag in Git, you can use the git tag -a command, followed by the tag name (usually the version), and then the message, such as the following:

git tag -a v1.0 -m "my version 1.0"

To view the tags in your repository...