The research within the field of Spiking Neural P systems (SN P systems, for short) is focusing mainly in the study of the computational completeness (they are equivalent in power to Turing machines) and computational efficiency of this kind of systems. These devices have been shown capable of providing polynomial time solutions to computationally hard problems by making use of an exponential workspace constructed in a natural way. In order to experimentally explore this computational power, it is necessary to develop software that provides simulation tools (simulators) for the existing variety of SN P systems. Such simulators allow us to carry out computations of solutions to NP-complete problems on certain instances. Within this trend, P-Lingua provides a standard language for the definition of P systems. As part of the same project, pLinguaCore library provides particular implementations of parsers and simulators for the models specified in P-Lingua. In this paper, an extension of the P-Lingua language to define SN P systems is presented, along with an upgrade of pLinguaCore including a parser and a new simulator for the variants of these systems included in the language.