In this workshop, we will take a look at Swiftlet, a Grasshopper plugin that lets you make web requests directly from your GH definition. Utilizing web services and external APIs opens up unique opportunities for data scraping, cloud computing, and live data processing directly within your favorite modeling software. As a fun example of fetching geospatial information from an online resource, we will use Google Maps API to get real-time driving directions between two points inside a Rhino model of New York City. You will also learn how Swiftlet has been used to integrate machine learning models into a cloud compute workflow.
Sergey Pigach is an Associate Applications Developer at CORE Studio | Thornton Tomasetti. Sergey’s work builds on his architectural training by bridging the domains of technology and design, driving him to develop computational tools for architects, designers, and engineers. Since joining CORE Studio he has worked on desktop and web-based projects including Swarm, a cloud compute solution for Grasshopper; ShapeDiver, a desktop client integration following a merger; and—most recently—Cortex, CORE Studio’s new ML platform.