It's because Python is both simple and easy to use, and complicated and hard to understand. It's a Janus of a programming language. There are lots of complexit

It's because Python is both simple and easy to use, and complicated and hard to understand. It's a Janus of a programming language. There are lots of complexities that alternately tie software engineers up in knots and let them go into raptures of blissful hackery. But they generally aren't all that visible in the face it presents to data scientists and devops. And it's hard to make sweeping statements about "big or performance critical". A couple times in the past few years years I've seen or been involved in projects that successfully replaced big Java applications with Python implementations that were 1% the SLOC and had better performance. They were special situations, to be sure, though more so, I think, in terms of explaining the performance improvement than the cost savings.