Julia Vs Python

Comparing Julia and Python

Python is the most popular language used widely by most of the developers. Whereas Julia is launched very recently in 2012 which is much younger than python. But many developers are likely to use Julia as it is catching on quickly, considering the rankings by red monk.

Advantages of Julia

From the beginning, Julia was designed for numerical and scientific computation. It's not surprising that Julia has numerous features for such instances of use: 
Faster by default. JIT compilation and JIT type declarations imply it can frequently beat “pure”, Python. With the means of external libraries, optimizations with tools such as Cython, third party JIT compilers python can be made faster, but Julia was designed to be faster right out from the gate. 
A mathematical friendly syntax. The users of computing languages and environments such as Matlab, R, Mathematica, and Octave are the targeted audience for Julia. Julia's syntax for mathematics operations looks similar to the way mathematics formulas are written outside the computing world, which makes it look easier for non-programmers to pick up on. 
Automated memory management. Like Python, Julia doesn't load the user with the specifics of allocating and freeing memory, and it provides some measure of control over garbage collection. The idea is that if you change to Julia, you do not loses one of Python's common conveniences. 

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