The open-source PlanetProfile framework was developed to investigate the
interior structure of icy moons based on self-consistency and
comparative planetology. The software, originally written in Matlab,
relates observed and measured properties, assumptions such as the type
of materials present, and laboratory equation-of-state data through
geophysical and thermodynamic models to evaluate radial profiles of
mechanical, thermodynamic, and electrical properties, as
self-consistently as possible. We have created a Python version of
PlanetProfile. In the process, we have made optimization improvements
and added parallelization and parameter-space search features to utilize
fast operation for investigating unresolved questions in planetary
geophysics, in which many model inputs are poorly constrained. The
Python version links to other scientific software packages, including
for evaluating equation-of-state data, magnetic induction calculations,
and seismic calculations. Physical models in PlanetProfile have been
reconfigured to improve self-consistency and generate the most realistic
relationships between properties. Here, we describe the software design
and algorithms in detail, summarize models for major moons across the
outer solar system, and discuss new inferences about the interior
structure of several bodies. The high values and narrow uncertainty
ranges reported for the axial moments of inertia for Callisto, Titan,
and Io are difficult to reconcile with self-consistent models, requiring
highly porous rock layers equivalent to incomplete differentiation for
Callisto and Titan, and a high rock melt fraction for Io. This effect is
even more pronounced with the more realistic models in the Python
version. Radial profiles for each model and comparison to prior work are
provided as Zenodo archives.