[Apologies for cross-postings] Dear colleagues, It is our pleasure to introduce the release of the python package BindsNET <https://github.com/Hananel-Hazan/bindsnet>and its companion paper in Frontiers in Bioinformatics “BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python <http://journal.frontiersin.org/article/10.3389/fninf.2018.00089>”. BindsNET is a python package to simulate a spiking neuronal network using a GPU. The framework is easy and well in line with Python, NumPy and PyTorch standard that runs on CPU’s/GPU’s. BindsNet will serve both the novel researcher and the seasoned programmer wanting to perform rapid prototyping prior to diving into hardware implementation. To achieve maximum performance and flexibility, BindsNET re-purposes the powerful and flexible PyTorch <http://pytorch.org/> library. By wrapping around PyTorch we avoid "reinventing the wheel" by reusing it's function and sub-modules for the spiking neuronal networks computational needs. For more details on performance, usability and code examples please see the Frontier paper <http://journal.frontiersin.org/article/10.3389/fninf.2018.00089> as well in the GitHub repository <https://github.com/Hananel-Hazan/bindsnet>. BindsNet welcomes researcher, students and neuro-scientists to both utilize and contribute to this leading-edge toolbox. *Happy spiking* Thanks Hananel Hazan Postdoctoral Research Associate BINDS Lab, UMass Amherst, USA http://Hananel.Hazan.org.il