Existing software platforms are not well suited to the task of processing data from a network of GNSS receivers. Because data are expected to be shared amongst networked receivers, not only must new algorithms be designed, but new software platforms upon which these algorithms can be tested must also be built. In this work a software platform for simultaneously processing data from many GNSS receivers is designed and implemented. An object oriented design philosophy is used so that objects such as receivers, networks of receivers, and constellations of satellites are all defined as separate blocks of code with the capacity to store relevant data and perform object-specific functions. Under this coding design and with this software platform, experiments on cooperative positioning that leverage shared data between receivers in a network can be quickly implemented. Therefore the fast prototyping of ideas in cooperative GNSS can be realized. As an example of this, a real-world experiment involving data from two SiGe Samplers was performed at Lake Titicaca in Peru in which both receivers shared tracking data to help prevent loss-of- lock during scalar tracking. Acquisition, cooperative scalar tracking, and navigation were all performed using the software platform developed in this work. For the example experiment of this project, two receivers on a moving boat maintained a fixed baseline and thus shared code phase information to prevent loss-of-lock situations due to signal loss at either receiver. Experimental results show that indeed loss-of-lock is prevented. In addition, example usages from this experiment highlight the benefits of using the Python Software Receiver over traditional software receivers.