Python’s popularity and importance is backed by data scientists, ML engineers, and AI developers. But if you are active in the developer community especially the AI and ML ones then you know that python is not as popular as it used to be and developers are talking about other languages. Of course, there are problems like being slow, giving runtime errors, and others. Which is one of the reasons many developers are switching to languages like Rust, Go, and the recent addition to the list is Julia.
Julia is more suitable than python for tasks like mathematical operations and dealing with huge amounts of data. Julia is the option for data science. For modular programming developers are switching to GO and Rust is the choice for systems programming. Python developers for hire are aware of the situation, so they are switching to other languages.
Let’s have a look at why Julia is the next choice for developers and what features it offers that python does not. To know more on if python is the language of the future, read on!
Python vs Julia
The reason for creating new programming languages is to cater to the downsides of old languages. So, julia was created to fix the issues python had, for instance, the slow speed. Just like python did with the language ABC, it was easy to read and code, the adaptability and robustness was also better than ABC.
Similarly, Julia is keeping the good bits of python and improving on the ones it is not good at.
According to its creators: they wanted a language which is:
Open source and easy to read, like python, but with the speed of C and the dynamic architecture of Ruby. A language which is homoiconic like Lisp and has mathematical power like Matlab and R like statistical power. A language which was easy and simple to learn but had the characteristics to keep the hackers happy.
So, Julia was created keeping in mind all these upsides. That is the reason it has become popular and achieved success even at an early age.
Python coders vs Julia Coders: what features each has
Versatility
It is a versatile language which can be used to develop anything from machine learning models to web applications to mobile apps and more.
Speed
It is created with the approach to get speeds like C and this language really achieves it. Python has become speedy over the years but Julia is just on another level. Apart from C, C++, and Fortran it is the only language which has been able to reach speeds like those.
Python developer VS Julia developers
Python with more than 30 years of development and time to become famous has a large community. You can find solutions to any problem you face in python but with Julia being so young it does not have a large and active community. Thus, you will have to spend some time finding the solution to your problems.
Python Coders conversion vs Julia
The best thing about Julia is that you do not have to learn a single command of Julia. It is truly convertible meaning, you can write C and python code in Julia and it will adapt to it.
The other benefit is that you can patch your Python and C application with Julia code without having to redevelop the entire application.
Libraries available to python developers vs Julia developers
Python has thousands of libraries which are actively maintained but on the other hand Julia does not have that many libraries. The reason again is because it is a young language, but with passage of time there will come more. For now the libraries available are sufficient to do the job.
Python developers for hire vs Julia developers for hire
The bottom line is, you can easily find thousands of python developers for hire. Even though developers are shifting more towards Julia, you still cannot find them easily. In recent years the trend to shift towards julia has become more and more frequent so in coming years you can find more julia developers than python coders.
Julia language has a low niche as of now but with its growth it will outshine python. If you are comfortable working in python then you can keep on working in the language of your choice. Because of the fact that you can easily learn julia whenever needed and even patch your python and C applications with julia.
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