The science community’s progression toward Python as a primary programing language, facilitated NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) Program to develop a Python-based radar processing system, GVradar. GVradar consists of two modules: Dual-Polarimetric Quality Control (DPQC) and dual-polarimetric precipitation product generation (dp_products). Both modules take full advantage of the open-source Python Atmospheric Radiation Measurement (ARM) Radar Toolkit (Py-ART) and Colorado State University’s Radar Tools (CSU Radar Tools). Within DPQC, parameter threshold gate filters are utilized to identify and remove non­-precipitating echoes based on freezing level, beam height, or by user defined sector. Additional DPQC capabilities include unfolding of Differential Phase (Φdp), Specific Differential Phase (Kdp) retrieval, velocity de-aliasing, and application of calibration offsets. Precipitation products generated with CSU Radar Tools include HIDRO Rain Rate (RC) and Hydrometeor Identification (FH). Additional products include GPM-GV’s mass weighted mean diameter (D_m) and normalized intercept parameter (N_w). D_m and N_w retrievals were computed from empirical equations using disdrometer derived Zdr data obtained during GPM field experiments. The recommended method of executing GVradar is to use a user designated parameter dictionary, however the code will run with default settings. The use of a dictionary allows the user to optimize QC thresholds, specify fields to generate, and select output and plotting options. The ability of GVradar to retrieve sounding data from the Rapid Refresh (RAP) model allows DPQC to be applied and dp_products to be generated in near real-time. NASA’s Dual Polarimetric (NPOL) radar is currently using GVradar to display data in near real-time. GPM-GV developed GVradar as a user-friendly open-source radar processing tool that is freely available to the scientific community.