  We develop a theory of weak Poincar\'e inequalities to characterize
convergence rates of ergodic Markov chains. Motivated by the application of
Markov chains in the context of algorithms, we develop a relevant set of tools
which enable the practical study of convergence rates in the setting of Markov
chain Monte Carlo methods, but also well beyond.
