  A general, minimal Python framework for building hybrid asynchronous
decomposition samplers for quadratic unconstrained binary optimization
(QUBO) problems.

  dwave-hybrid facilitates three aspects of solution development:

  - Hybrid approaches to combining quantum and classical compute
    resources
  - Evaluating a portfolio of algorithmic components and
    problem-decomposition trategies
  - Experimenting with workflow structures and parameters to obtain
    the best application results

  The framework enables rapid development and insight into expected
performance of productized versions of its experimental prototypes.
