QuaPy (https://github.com/HLT-ISTI/QuaPy) is an open-source framework for performing quantification, written in Python. QuaPy provides implementations of a number of baseline methods and advanced quantification methods (including CC, ACC, PCC, PACC, X, MAX, T50, MS, SLD, HDy, SVM(KLD), SVM(NKLD), SVM(Q), SVM(AE), SVM(RAE), QuaNet, and ensemble methods), of routines for quantification-oriented model selection, of several broadly accepted evaluation measures (including AE, RAE, SE, KLD, NKLD), and of robust evaluation protocols (including the generation of test samples by sampling uniformly at random from all legitimate prevalence distributions) routinely used in the field. QuaPy also makes available datasets commonly used for testing quantifiers, and ofers visualization tools (including diagonal plots, error-by-shift plots, and bias boxplots) for facilitating the analysis and interpretation of the results. The software is open-source, publicly available under a BSD-3 licence via GitHub, can be installed via pip (https://pypi.org/project/QuaPy/), and is open to contributions of new material by the quantification community.