Neuroscientists have relied on Excel for simple analyses and MATLAB for their programming needs for decades. Other data intensive domains like astrophysics and machine learning have embraced Python but many neuroscientists are hesitant to make the switch and continue to use legacy code in MATLAB. When I started doing neuroscientific data analysis in 2012 I started with Python because of the mature scientific Python stack and its community that encourages transparency and reproducible pipelines. Since then I have worked on projects ranging from analyzing how rats behave in conditioning experiments to detailed electrical recordings of individual neurons. Python has lent itself to elegant solutions for these two extremes and many domains in between. Some parts of the analysis pipeline come up frequently in all types of neuroscientific experiments, whether it's high level behavior or low level recordings and I have assembled a core set of these utilities in a Python package called Nept (NeuroElectroPhysiological Tools). My goal is to provide a well documented and tested base to which others can contribute and help grow the community of Pythonistas in neuroscience.