Complete the Python implementations of usability benchmarks

[szhorvat]

We have a set of usability benchmarks—a collection of small tasks that help us judge how convenient it is to use the library. This issue is to implement each such task using python-igraph.

https://github.com/igraph/usability-benchmarks

This collection of solutions will also be useful as a "dictionary" that helps users familiar with another high-level interface of igraph (or even a different graph library) get up to speed with python-igraph.

Ideally, the Python solutions would eventually be collected into a Jupyter notebook: this way usability in notebook environments could also be explored.

If you plan to work on this issue, choose one or a few exercises of your liking, and post a comment noting which ones you will be implementing.

[yanchenm]

Hi, currently working on a PR for the following examples:

• Clique percolation
• Community visualization
• Visualize cliques

[szhorvat]

@yanchenm Thanks for offering to contribute!

We created a new repository to host the solutions. You can open a pull request (a separate one for each task) there. https://github.com/igraph/usability-benchmarks This is still a new project, and we are still exploring the best way to move forward with it. Things may change rapidly.

I would suggest opening a draft PR before you are completely done with the task. Create a new directory within solutions/python-igraph for each task. This way, we can see how you approach the task, and we can learn something not only about what is possible with python-igraph, but how easy it is a newcomer to discover the best way to do it.

[dkhl65]

I am working with @yanchenm, @ChenyanWang and @jamesjiang52 on this issue and I completed the visualize cliques task.

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed in 14 days if no further activity occurs. Thank you for your contributions.