I am constantly using open source projects during my work.
Usually I view the dependents graph to see which other open source projects use it.
It's more of an art than a science, but there are a few metrics that may be useful to look at:
- Stars on GitHub. A star is essentially someone showing their appreciation and interest in the project.
- Watchers on GitHub. Watching a project essentially says you want to be notified of any change in the repository.
- Forks on GitHub. A fork is the starting point of someone (openly) working on a project in GitHub.
As noted, none of these metrics are iron clad (e.g., you could watch a project but ignore updates from it, or fork a project and do nothing with this fork), but they are somewhat of an indicator of interest.
It's also usually a good idea to normalize these numbers by comparing to similar projects, as the absolute numbers are sometimes hard to interpret. E.g., let's look at Python's psychopg2 library for connecting to PostgreSQL databases. At the time of writing, it has 73 watchers, 464 forks and 2.8K forks. Is this a lot? a little? Hard to tell from the numbers alone. But if you compare it to the mysql-connector-python library for connecting to MySQL databases, you'll see similar numbers, but if you compare it to db2-python for connecting to DB2 database, you'll see substantially smaller numbers. This is a strong indicator that PostgreSQL and MySQL are more popular databases to use in Python applications that DB2.