Research demonstrates that the large-scale access and analysis to data can help cities plan for more inclusive and efficient growth. However, policy makers and researchers around the world still lack sufficient access to granular and dynamic sources of data – a challenge that has come to prominence as cities attempt to respond to the local impacts of the COVID-19 pandemic. To address this challenge, this paper presents UrbanPy, a new open-source library that makes the automated collection, processing, and visualization of spatial urban data simple and consistent for cities. UrbanPy, first developed as a tool to help Latin American cities design rapid responses to COVID-19, presents six innovative capabilities for researchers and practitioners focused on data collection, processing and visualization. To illustrate the potential applications of UrbanPy, this paper presents a case study from Lima, Peru, where the library helped municipal leaders with their COVID-19 response by identifying vulnerable populations, creating food accessibility metrics, and optimizing the location of food supply facilities.