  We introduce CBXPy and ConsensusBasedX.jl, Python and Julia implementations
of consensus-based interacting particle systems (CBX), which generalise
consensus-based optimization methods (CBO) for global, derivative-free
optimisation. The raison d'\^etre of our libraries is twofold: on the one hand,
to offer high-performance implementations of CBX methods that the community can
use directly, while on the other, providing a general interface that can
accommodate and be extended to further variations of the CBX family. Python and
Julia were selected as the leading high-level languages in terms of usage and
performance, as well as their popularity among the scientific computing
community. Both libraries have been developed with a common ethos, ensuring a
similar API and core functionality, while leveraging the strengths of each
language and writing idiomatic code.
