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StochPy (Stochastic modelling in Python) is an easy-to-use package, which provides several stochastic simulation algorithms (SSAs), which can be used to simulate biochemical systems in a stochastic manner. Further, several unique and easy-to-use analysis techniques are provided by StochPy.
SSA’s try to describe the time evolution of a reacting system, such that it takes into account discreteness and stochasticity. Discreteness and stochasticity play often important roles in biochemical systems. Therefore, SSA’s are widely used to simulate biochemical systems. Especially for biochemical systems that contain low copy numbers. For such systems, deterministic models often fail to capture the stochasticity of the system, while SSAs are capable of capturing this stochastic behaviour.
StochPy is an extension of PySCeS. PySCeS - the Python Simulator for Cellular Systems - is a toolkit for the analysis and investigation of cellular systems.

StochPy's features:

Stochastic Simulations
Sophisticated Analysis Techniques
Usable as a Library
Accepts SBML and PySCeS input
Multi-Platform
User-Friendly
Works together with the PySCeS package
Structural Analysis
Integrators for the simulation of a cellular system's evolution over time (LSODA).
Non-linear solvers that can be used to calculate a systems steady state (HYBRD, NLEQ2)
Metabolic Control Analysis (i.e. elasticities, flux and concentration control coefficients)
A bifurcation module for the study of systems which exhibit multiple (stable and unstable) steady states (PITCON)
A variety of extra utilities such for performing parameter scans, data output and plotting