This repository contains a set of simple tasks to gauge not the performance, but the usability of network analysis and graph theory libraries.
These exercises will be solved using various graph libraries in various programming languages (including all three high-level interfaces of igraph). We will use this comparison to improve igraph's high-level APIs and make sure that they stand out in usability. The solutions may also serve as a "dictionary" to help people translate between different graph libraries, or learn to work with new libraries.
We welcome the developers of other network analysis libraries to join the project, and use the information here to improve their software. Contributions of new benchmark tasks, as well as solutions to the existing tasks are very welcome.
See the tasks descriptions here.
Please open a new issue and describe the task.
Please open a new draft PR. Each solution should go into its own subdirectory, within the directory of the graph library with which it is implemented.
Providing alternative solutions, or improving existing solutions by making them more idiomatic, easier to read, or faster, is also very welcome.
Feel free to contribute solutions using any graph library in any high-level programming language, even if the library is not yet mentioned in this section.
- R: igraph/rigraph#497
- Python: igraph/python-igraph#469
- Mathematica: szhorvat/IGraphM#111