Ruby was more popular, especially when Rails exploded. It was great for scrappy startups, that didn't need Java level quality (and costly time) nor the risks of

Ruby was more popular, especially when Rails exploded. It was great for scrappy startups, that didn't need Java level quality (and costly time) nor the risks of PHP 4. The python modules eco-system lead to the stake change. Scikit-learn, Pandas and Numpy made it so useful for visualisation, research, old school modelling ML. Writing and saving files was simple. Making your own module took 2 files with 4 lines of code. How easy. After establishing use cases in Python 2, which already allowed a lot of C code in practise for speed, Python 3 changed everything with a simpler language that makes it clear what is normal and weird. You might dislike [:-1] at first, but you definitely know it's weird compared to other languages, so you can know what to search for. Not true of abstractions in some other languages like Ruby, for migrating devs. Then Python caught with Tensorflow/PyTorch a real wave of being the place to go. Kaggle involved 100,000s all coding in Python for data science in the latter half of the 10s. It did this at the same time as the LAMP stack and LAMP pre-installed VPS running cPanel were dying to React/node.js and PaaS approaches on the one hand, and big cloud providers on the other. So suddenly, there was not an easy default 'nix environment with PHP to rely on being available so easily, and adding python to an existing server is super easy (and Flask/Django easy to grep), making adding a backend for ML or whatever, very easy too. Ruby wasn't even on the playing field for many of these use cases. I think a last small impact was that Ruby was misused where shell scripts could have worked. Many people made Ruby cli tools for their internal team, when shell scripts would have been fine - this frustrated some of their peers away from Ruby. There is no difference from Python here, but I just noticed it more.