Monitoring GitHub Clone Counts: Understanding and Tools with Example From the /graphs/traffic tab in your repo you can see clone activity — a more concrete form of interest numbers, represented as counts over the last 14 days. This is a little disappointing, as you want to get stats for the total amount of clones and not only those from yesterday. To cope up with this shortcoming, developers introduced scripts where they can scrape clone data over a period by using the API of GitHub from traffic graphs.
Learn Clone Tracking on GitHub
This traffic graph in Github gives information about how many times a repository I have is being cloned from github, but this data works only for past two weeks. It is found under the Insights tab, and users with push access on your repository have permissions to use this feature. Some terminologies are used solely for analysis, eg full clones and unique visitors but still no total count of clones14.
Better Tracking with Github API
Developers can work around GitHub default metrics by using scripts to scrape clone data through the available APIs, but not all teams have access or availability of such tools. With a cron job to run these scripts in regular intervals, users can compile their historical clone data into local files.GitHub Cloning (ad) This way users have a persistent history of how their repository has been performing, even as GitHub refreshes its traffic metrics every 14 days.
Real-Live Use-Cases Using Clone Data
In particular, being able to count the number of clones is important for researchers and developers who need this as a metric when thesis statistics on funding applications or project reviews. For example, institutions such as the NSF mandate comprehensive tracking of how often code is accessed or used. On API-based data collection to automatically report, repository owners are able consolidate their efforts with deep awareness106 of how far and wide the project has been growing.
In short, while the direct APIs provided by GitHub can only be used for basic clone-level tracking on repositories, using custom scripts to communicate with API yields richer data and additional control over moving average based analysis helping developers in making decisions about users engagement.