GrimoireLab is a powerful toolset for software development analytics. It is able to collect, process and visualize data from a large plethora of tools and platforms used in software development. The obtained data is stored in ElasticSearch and shown via web-based dashboards built on top of Kibana. Predefined dashboards are provided by GrimoireLab, however each user can easily create their own ones to address specific needs, such as the implementation of CHAOSS metrics.
In the current stage, GrimoireLab doesn't provide an approach to share custom dashboards, thus limiting the end-user capabilities. This project idea is about implementing such an approach leveraging on Python, the Kibana API, ElasticSearch and OpenDistro for ElasticSearch (ODFE).
Task: Download PyCharm and get familiar with it.
Work done can be found here
Task: Set up Perceval to be executed from PyCharm.
Work done can be found here
Task: Create a Python script to execute Perceval via its Python interface using the Git and GitLab backends.
Work done can be found here
Task: Based on microtask #2, try to answer the following questions
Work done can be found here
Task: Set up a dev environment to work on GrimoireLab.
Work done can be found here
Task: Execute micro-mordred to collect, enrich and visualize data from any GitHub repository.
Work done can be found here
Task: Execute micro-mordred to collect, enrich and visualize data from any GitHub repository.
Work done can be found here
Task: Read through the documentation and try to answer the following questions
Work done can be found here
Task: Submit at least a PR to one of the GrimoireLab repositories to fix an issue, improve the documentation, etc.
Work done can be found here