A local engineering uni is sending one of their students to a local software development firm for a three-months stint, in order to train her as a prospective, entry-level data scientist or scientific programmer after her BSc graduation. The student knows theoretical Python, understands the fundamentals of data science and is able to set up a working pipeline under Windows and Linux. The professor is asking for a modern productivity benchmark reference or two, so that the student can use next month to try and improve her skills before starting. Any good practical tip from you smart HNers? Thanks.