Dynamic, up-to-date, spacialized and summarized information on the possibility of landslide occurrences is important for many areas of society. Landslide Advisor is a library of computational functions implemented in Python and GDAL. This library is capable of automatically classifying the risk of a landslide occurrence in near realtime, as well as in terms of prediction (future), and abstracting the information in a summarized manner for the end user. The Landslide Advisor was developed as a product of a research and innovation project in the Brazilian electricity sector, via the National Electric Energy Agency (ANEEL). This paper's objective is to present the main characteristics of this library.