We have produced a new software package for the simulation of pulsar
populations, , based on the package. The
codebase has been re-written in Python (save for some external libraries, which
remain in their native Fortran), utilising the object-oriented features of the
language, and improving the modularity of the code. Pre-written scripts are
provided for running the simulations in standard' modes of operation, but the code is flexible enough to support the writing of personalised scripts. The modular structure also makes the addition of experimental features (such as new models for period or luminosity distributions) more straightforward than with the previous code. We also discuss potential additions to the modelling capabilities of the software. Finally, we demonstrate some potential applications of the code; first, using results of surveys at different observing frequencies, we find pulsar spectral indices are best fit by a normal distribution with mean $-1.4$ and standard deviation $1.0$. Second, we model pulsar spin evolution to calculate the best-fit for a relationship between a pulsar's luminosity and spin parameters. We used the code to replicate the analysis of Faucher-Gigu\ere & Kaspi, and have subsequently optimized their power-law
dependence of radio luminosity, , with period, , and period derivative,
. We find that the underlying population is best described by $L
\propto P^{-1.39 \pm 0.09} \dot{P}^{0.48 \pm 0.04}$ and is very similar to that
found for -ray pulsars by Perera et al. Using this relationship, we
generate a model population and examine the age-luminosity relation for the
entire pulsar population, which may be measurable after future large-scale
surveys with the Square Kilometer Array.

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