  Non-Markovian dynamics arising from the strong coupling of a system to a
structured environment is essential in many applications of quantum mechanics
and emerging technologies. Deriving an accurate description of general quantum
dynamics including memory effects is however a demanding task, prohibitive to
standard analytical or direct numerical approaches. We present a major release
of our open source software package, OQuPy (Open Quantum System in Python),
which provides several recently developed numerical methods that address this
challenging task. It utilizes the process tensor approach to open quantum
systems in which a single map, the process tensor, captures all possible
effects of an environment on the system. The representation of the process
tensor in a tensor network form allows an exact yet highly efficient
description of non-Markovian open quantum systems (NM-OQS). The OQuPy package
provides methods to (1) compute the dynamics and multi-time correlations of
quantum systems coupled to single and multiple environments, (2) optimize
control protocols for NM-OQS, (3) simulate interacting chains of NM-OQS, and
(4) compute the mean-field dynamics of an ensemble of NM-OQS coupled to a
common central system. Our aim is to provide an easily accessible and
extensible tool for researchers of open quantum systems in fields such as
quantum chemistry, quantum sensing, and quantum information.
