Wrapping up Python into a Cloud-based PostgreSQL

Specifically, using PL/Python, one can bring in countless Python libraries to process data close to the database. Here I will talk about my efforts to bring in the functionality of PySAL, a spatial analytics library written in Python and developed largely by Serge Rey, et al. at Arizona State University. PySAL makes available robust exploratory spatial data analysis related to spatial cluster and outlier detection, hotspot detection, spatial regression, and much more. Besides the wrappers we wrote for PySAL, we have written classes for bringing in machine learning methods such as random forest, linear regression, support vector machines, and neural networks from scikit-learn and Tensorflow. This talk will specifically cover the challenges we encountered programming in the PL/Python environment, collaborations with some of the PySAL developers, and the power of having spatial statistics and machine learning capabilities baked right into a cloud database.