Earlier quoted context omitted.
Python is still vital and thriving but I wouldn't be surprised if its market share is declining (slowly). As you say, it's dominant for data science... but recently it and R were the only practical choices... now other languages (Julia, for example) are valid options. The development of alternative Jupyter (formerly IPython) kernels has accelerated adoption of other languages. Similarly, a few years back it seemed li…
I want this to be true, by the way. As I mention in some other comment, I think Python is rather mediocre as an actual language for building software. Its appeal cannot be denied, but a majority of my peers would really like to use a language that has its tooling shit together. Python is the only language I've had to deploy that makes me understand why anybody would want to use containers.
Spending a bit of time with Rust's tooling, static analysis, and "if it compiles it's pretty likely to work" (at least way more so than with Python) definitely emphasizes a lot of Python's flaws.