> it will be incredibly hard to replicate them This is true, sort of. It was also true when people said the same about Perl (some people still say this about P

> it will be incredibly hard to replicate them This is true, sort of. It was also true when people said the same about Perl (some people still say this about Perl!). Then Rails happened to Ruby, just as the web was going through another phase of explosive growth. Likewise, Node or Rust + GitHub effect. The point is not to compare the growth trajectories or projected peaks, but to emphasize the levering effect of an enjoyable language combined with modern collaborative development and infrastructure. A language doesn't need "everyone" to build a viable ecosystem, just a critical mass. > If it's still around in 10 years then it might be worth looking at (but still probably not). Knock on wood and all, but from past observation, I think Julia is at or very close to this critical mass already. I would compare Julia now to the SciPy ecosystem around 2009-2010. That's just when IPython was getting popular, early versions of Pandas were released, and people were starting to trust Cython. (I was a heavy Python user then, and frequently suggested it to Matlab users who had exactly your question even in to 2012-2013). There's already a surprising breadth of packages, they just need time to mature. Sometimes too many, actually -- I recently found three for a relatively obscure geophysics format I used to work with. That lever is big enough that people often don't mind rolling their own.