The performance Python is a real problem but Python has succeeded because scientific computing really needs interactive and dynamic programming languages. You n

The performance Python is a real problem but Python has succeeded because scientific computing really needs interactive and dynamic programming languages. You need something which lets you easily experiment with data, plot, change code in rapid iterations without constant recompilations and reloading of data. This has been recognized for some time. The compromise had been to build performance sensitive parts in C/C++ and do the experimental/iteration part in Python. But today you don’t really have to compromise anymore. We got Julia. It solves the whole problem. You get the interactivity you need combined with the performance. Of course in my his industry momentum matters. Python has built up the momentum of an oil tanker. Even if you shut off the engines it is going to keep going for many years. But Julia is the obvious end station. It does all the things HPC and scientific computing needs. But building mains share, documentation, community, polish tools etc will of course take time.