  In recent years, there has been increasing interest in network diffusion
models and related problems. The most popular of these are the independent
cascade and linear threshold models. Much of the recent experimental work done
on these models requires a large number of simulations conducted on large
graphs, a computationally expensive task suited for low-level languages.
However, many researchers prefer the use of higher-level languages (such as
Python) for their flexibility and shorter development times. Moreover, in many
research tasks, these simulations are the most computationally intensive task,
so it would be desirable to have a library for these with an interface to a
high-level language with the performance of a low-level language. To fill this
niche, we introduce CyNetDiff, a Python library with components written in
Cython to provide improved performance for these computationally intensive
diffusion tasks.
