Reproducibility and accuracy have become increasingly important issues for the molecular simulation community. The availability of validated open-source postprocessing tools to analyze simulation trajectories and compute properties is key to helping researchers conduct more accurate and reproducible simulations. Here we describe a suite of open-source Python-based postprocessing routines we have developed called PyLAT. PyLAT is compatible with the popular molecular dynamics package LAMMPS and enables users to compute viscosities, self-diffusivities, ionic conductivities, molecule or ion pair lifetimes, dielectric constants, and radial distribution functions using best-practice methods.