Abstract
This article examines the development and implementation of a customized Python script utilizing the Elsevier Scopus and Clarivate Web of Science Journal Citation Reports Application Programming Interfaces (APIs). The aim was to streamline and expedite the labor-intensive process of collecting research metrics, which were traditionally compiled manually by librarians at the University of Miami Miller School of Medicine Louis Calder Memorial Library. The script significantly reduces the time and effort required to generate comprehensive reports on research productivity, thereby enabling more efficient resource allocation and aiding in faculty evaluations.