I&#x27;m not the parent author, but why I haven&#x27;t tried the Python ecosystem:<p>I&#x27;ve heard of NumPy, PyPy, SciPy, Pandas, matplotlib, and now Numba. I don&#x27;t particularly know what these do or how they overlap or interact. Which is kind of the point: to a complete outsider, the world of Python scientific computing feels like a wild west where everybody is happily proclaiming that their setup is just right.<p>Additionally, Python is slow; Julia is fast. I&#x27;ve heard things like &quot;well, Python is only slow at certain things, and makes it easy to write C code when needed.&quot; I don&#x27;t want to write any C code. Same goes for &quot;typically only a small portion of your Python code is a bottleneck, and it&#x27;s easy to port that to C.&quot;<p>A huge part of the appeal of Julia is that you don&#x27;t have to worry about language interoperability, calling C, etc. Everything can be written efficiently and readably in Julia, and because the base language is designed around scientific computing, there&#x27;s little worry about add-on scientific computing packages not playing nice together.<p>Now, I fully believe that I could get the right Python environment and set of packages set up be productive. But to get going with Julia, I just download Julia and go.<p>Also, JuMP [1] is just amazing.<p>[1] <a href="http:&#x2F;&#x2F;www.juliaopt.org" rel="nofollow">http:&#x2F;&#x2F;www.juliaopt.org</a>