Julia vs. Python: Comparison of the two programming languages



There is no denying the fact that Pythonprogramming language has found greater acceptance with programmers across the world. In fact, as per the TIOBE index, Python was the programming language of the year in 2018. 

One of the reasons for the popularity of this open source programming language is its simplicity and the fact that it has a short learning curve for a programmer. Today,Python is used extensively for AI and machine learning. 

A high-performance and dynamic programming language that is now challenging the dominance of Python is Juliaprogramming language. First unveiled to developers in 2012 by MIT Professors Viral Shah, Stefan Karpinski, Jeff Bezanson, and Alan Edelman, the programming language made its official debut in 2018 when Julia 1.0 was released at JuliaCon conference in London. 




Julia is designed for speed and to be used for high performance computing requirements. The programming language leverages the positive aspects of similar programming languages like Python as well as eliminate their shortcomings. Some of the features of Julia programming language include:

Key features of julia 


#1. Built for speed as it is compiled at Just-In-Time or runtime using the LLVM framework. The fact that it is not interpreted makes it a fast programming language and ideal for machine learning and AI-related activities.

#2. Julia is a dynamically typed programming language where you don’t have to specify variables.

#3. While using Julia you can access the libraries of other programming languages such as C and Python.

#4. The metaprogramming ability of Julia programming language allows developers to create a Julia programs from another Julia program with unique codes.


Key features of Python:


#1. Python is a high-level and object-oriented programming language.

#2. Python is also a dynamically typed language like Julia.

#3. There is no need to compile Python as it is an interpreted language.

#4. Python is an open source language and you can download and use it freely.

#5. Python programming language is highly portable and can run on any machine. 

Conclusion

The jury is still out on whether Julia programming language will be able to outperform Python in the long run and become the go-to programming language for programmers to build high performance computational projects using AI and machine learning. 

The fact that linear algebra and matrix representations can be quickly executed in Julia programming language means that it is faster in execution than Python. Code conversion is another area where Julia has an edge over Python. Code conversion is much easier and faster while converting Python and C to Julia than the other way around.

Another fact that Python is much older than Julia works to its advantage, as Python has a bigger and more active community. Julia, being a relatively new programming language has a smaller community and therefore it is at a disadvantageous position over Python which is also supported by more third-party libraries.

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