I like Julia as a language but the speed argument doesn't really apply vs Python. Yes, benchmarks against pure Python implementations look good but in reality no one uses naive pure-python implementations. Python (with all the bells and whistles that interop with C/C++ like numpy, pytorch, tensorflow, numba, cython...) is very performant.
Python (with all the bells and whistles that interop with C/C++ like numpy, pytorch, tensorflow, numba, cython...) is very performant
I know. I spend much of my days writing 'high performance' Python, and Python is still my go to tool for just about everything. Julia's big advantage is, kind of like Fortran vs C back in the day, that it's fast even if you're just writing things in the most obvious and natural way for your domain.
