Factor our built-in models into a separate module.
0.0.5
Added a `stepEuler` method to the `Spn` class.
0.0.4
Parsing SBML-shorthand models from a string, to allow convenient inlining of shorthand models in python scripts and notebooks.
0.0.3
Basics now all working, and now with some (minimal) documentation.
0.0.2
Ironing out basic bugs and usage information.
0.0.1
Initial test release. Parsing SBML and SBML-shorthand models into a stochastic Petri net for simulation using the Gillespie algorithm or Poisson time stepping.