But Python didn't take off because of scientific computing. Google was a heavy user of Python from the start. Python seriously sucked for scientific computing in 2005. I was looking for a new language (the old one wasn't cutting it) and I'd been looking for a use for Python for years. It had some projects but it just was not in a useful state so I went with R, which was quite mature by that time, and it focused on statistical analysis. Years later Python became popular for scientific computing, likely due to the userbase it had built up in other areas.
While it's true in 2004 there was still a Numeric/numarray schism, at the time I was using Pyrex (which soon evolved into Cython) to have a gradually strongly typed Python-like thing cross-compatible with the rest of the ecosystem. That made it quite easy to write code which ran circles around R performance-wise without leaving the Python syntax domain and with a very simple FFI to call C to boot. I even had a tiny "pycc" script to create "executables" instead of "importable modules". Yes, those executables did depend on the installed base of Python stuff.
These days, Nim is a better Cython but with less dynamic temptations and more powerful metaprogramming (and, yes, a much smaller ecosystem..maybe not that much smaller than Python in the late 90s, though). { Not that this is all Nim is...It's actually a really good everything-language that's tricky to summarize in just a few words. }
Yeah I don't disagree re: scientific computing and Python (although I think from the beginning some of the advocacy for Python was coming from more "math-oriented" communities). I still think that when it started accelerating in use (which was mainly among scripting and then web applications, some other stuff too) there were existing solutions. A lot of discussions about established languages versus new ones are very similar to one another; the particular languages are just swapped out for different ones.
But Python didn't take off because of scientific computing. Google was a heavy user of Python from the start. Python seriously sucked for scientific computing in 2005. I was looking for a new language (the old one wasn't cutting it) and I'd been looking for a use for Python for years. It had some projects but it just was not in a useful state so I went with R, which was quite mature by that time, and it focused on statistical analysis. Years later Python became popular for scientific computing, likely due to the userbase it had built up in other areas.