GSoC IDEA: Open Source Software Health Metrics Visualization Exploration

[sgoggins]

IDEA: Open Source Software Health Metrics Visualization Exploration

The CHAOSS Community currently delivers pre-packaged visualizations of open source software health data through Augur APIs (https://github.com/chaoss/augur/blob/main/augur/routes/pull_request_reports.py and https://github.com/chaoss/augur/blob/main/augur/routes/contributor_reports.py), and the https://github.com/chaoss/augur-community-reports repository. This project seeks to expand, refine, and standardize the visualization of different classes of community health metrics data. Specifically, some analyses are temporal, others are anomaly driven, and in some cases, contrasts across repositories and communities are required. In each case, the visualization of data is an essential component for metrics, and what we are now referring to as metrics models (https://github.com/chaoss/wg-metrics-models).

The aims of the project are as follows:

• Experiment with standard metrics visualizations using direct Augur database connections, or through the Augur API.
• Refine metrics, and metrics model visualizations using Jupyter Notebooks are similar technology.
• Transform visualizations, as they are completed, into Augur API endpoints, following the pull request, and contributor reports examples.

• Difficulty: Medium
• Requirements: Strong interest in data visualization.
• Recommended: Experience with Python is desirable, and experience designing, or developing visualizations is desirable.
• Mentors: Sean Goggins, Andrew Brain, Vinod Ahuja.

Microtasks

For becoming familiar with Augur, you can start by reading some documentation. You can find useful information at in the links, below. Grimoirelab also has a set of installation instructions and documentation here: https://chaoss.github.io/grimoirelab-tutorial/

Once you're familiar with Augur, you can have a look at the following microtasks.

• Microtask 0:
  Download and configure Augur, creating a dev environment using the general cautions noted here:

  • Augur
    • https://oss-augur.readthedocs.io/en/dev/getting-started/installation.html and the full documentation here:
    • https://oss-augur.readthedocs.io/en/dev/development-guide/toc.html
  • Grimoirelab
    • https://chaoss.github.io/grimoirelab-tutorial/

• Microstask 1: Work on any Augur or Grimoirelab Issue that's Open

• Microtask 2: Identify new issues you encounter during installation.

• Microstask 3: Explore data presently captured, develop an experimental visualization using tools of your choice. If Jupyter Notebooks against an Augur database/API endpoint collection, use https://github.com/chaoss/augur-community-reports for development.

• Microtask 4: Anything you want to show us. Even if you find bugs in our documentation and want to issue a PR for those!