The increase in extreme weather events induced  by climate change, and their impact on power systems, has  created a need for tools that can assess and improve system resilience. To meet this need, the R&D team of the Energy  System Consulting segment of Tractebel Engineering GmbH has developed a novel tool called reXplan. ReXplan is a Python  library for resilient electrical system planning under extreme  hazard events, such as windstorms, earthquakes, floods,  wildfire, etc. It is designed to help power system operators and  planners make better-informed decisions to create more  resilient and secure power grids. This paper provides an overview of reXplan’s main features,  architecture, methodology of analysis and metrics. ReXplan is capable of modeling both spatiotemporal  extreme events and electrical power systems. It leverages technologies and techniques such as Julia/JuMP package and sequential Monte Carlo analysis with multivariate stratified  sampling to achieve high accuracy in the results while reducing  computational load. By quantifying resiliency metrics,  comparing different planning strategies, and validating technical solutions, reXplan can help reduce the risks of severe  outages in the grid. The software can be easily integrated into common data  science environments and is available as a Python library. For  computationally intensive tasks, such as optimal power flow,  reXplan is exploiting the fast speed of Julia programming  language, using PowerModels.jl as backend.