PFLlib is a beginner-friendly federated learning library that enables model training across decentralized data sources without sharing raw data. It provides implementations of federated algorithms (FedAvg, FedCP, GPFL, FedDBE) along with benchmarks for evaluation. Users can create FL scenarios and run algorithms via provided scripts, supporting datasets like ImageNet and DomainNet with various heterogeneity configurations.