Pyhton vs Julia

Comaparison between Pyhton and Julia:

as we all know Julia built for data-science,

but we all know as well that python is also evolved in this area more or less doesn't matter.

Python may be the better choice for the data-science developer or maybe not.

as we see in the previous post-Julia as lots of features, more than python.

because Julia has lots of good features from other languages eg: Ruby, c, Perl, shell, etc.

so here are some advantages of Python and some of Julia.

Python Advantages:

Python is very mature:

Python is now used very frequently in the development world, Python is very popular and young between developers.

Julia arrays index start from 1(1-indexed):

as we all are familiar with 0-indexed, java, c, python all are 0-indexed.

e.g.- string[0].

but Julia is 1-indexed.

so we can say Python is user friendly.

Python has far more third-party package:

Python is very popular among the developers, that's why it has lots of third-party libraries.

and packages are very important in any language to attract developers.

Billions of user:

Python community is very huge, and it gives advantage to python to connect the developer to each other.

Julia Advantages:

Julia speed and accuracy:

JIT assemblage and JIT type assertions suggest it can as often as possible beat "unadulterated", Python. With the methods for outside libraries, advancements with devices, for example, Cython, outsider JIT compilers python can be made quicker, yet Julia was intended to be quicker right out from the door.

User-friendly mathematical syntax:

The clients of registering dialects and situations, for example, Matlab, R, Mathematica, and Octave are the focused on crowd for julia. Julia's linguistic structure for science tasks appears to be like the manner in which arithmetic recipes are composed outside the figuring scene, which makes it look simpler for non software engineers to get on.

Superb memory management:

Like Python, Julia doesn't stack the client with the particulars of apportioning and liberating memory, and it gives some proportion of power over trash assortment. The thought is that on the off chance that you change to Julia, you don't loses one of Python's basic accommodations.