  Practitioners wishing to experience the efficiency gains from using low
discrepancy sequences need correct, well-written software. This article, based
on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo
(QMC) software available. We highlight the key software components required to
approximate multivariate integrals or expectations of functions of vector
random variables by QMC. We have combined these components in QMCPy, a Python
open source library, which we hope will draw the support of the QMC community.
Here we introduce QMCPy.
