search

eXascaleInfolab / PyCABeM

Python Benchmarking Framework for the Clustering Algorithms Evaluation: networks generation and shuffling; failover execution and resource consumption tracing (peak RAM RSS, CPU, ...); evaluation of Modularity, conductance, NMI and F1 Score for overlapping communities
Other
19 stars 4 forks source link

Pip package #14

Open luav opened 3 years ago

luav commented 3 years ago

To make the usage of your software more accessible, could you put it on pypi and make sure that people are able to install it by simply running pip?
By @Make42

luav commented 3 years ago

@Make42, thank you for the proposal. I have not packaged Clubmark because not so many people benchmark clustering algorithms. The pip package exists for PyExPool (utils/mpepool.py), which is a general purpose scheduler that is used in this benchmarking framework.