Two core philosophies underlie the framework's design. The first is that the framework should be readily scalable for any required calculations from running on a single machine up to running across hundreds of high performance compute nodes, and potentially even into the cloud. Secondly, it is constructed so that every aspect is user extendable via a flexible plugin system. This includes everything from the extraction of properties of data sources into Python objects, up to defining the workflows for how physical properties should be estimated.