If you are into the programming world, then you would know the battle between Julia and Python is fierce! Both compete for the throne of the best programming language. Unfortunately, it is difficult to choose an obvious champion.
Python is a popular programming language and a senior fella in the tech world with over 3 decades of hype. On the other hand, Julia being the new high schooler has garnered quite a buzz and searches recently.
Julia combines the best parts of other programming languages and makes its features. While Python focuses on general use and durability.
If you are interested in learning a programming language and don’t know which one to select, then let us dive into the battle between Julia and Python. You can certainly decide the best option for you at the end of the article.
What Is Python?
Python consistently ranks as one of the most popular and widely used programming languages among developers. It is a high-level, general- purpose and versatile programming language for the building of websites or software and data analysis. The major characteristic of python is its comprehensive and standard library.
It was first released by Guido van Rossum in 1991 as Python 0.9.0. It was updated ceaselessly with more advanced and interesting features. The latest version of Python was released in 2020 with version 2.7.18.
This program is remarkably easy-to-learn and helps to integrate systems more effectively. Statista Research states that Python has become one of the most popular programming languages, with a wide variety of use cases. In 2021, Python is most used for web development and data analysis, with 45 percent and 51 percent respectively.
What Is Julia?
Julia is a high-level, dynamically performing programming language. It focuses on speed and math orientation. Initially created by a team of four people i.e., Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman in 2012; Julia is a newcomer in the programming society.
However, Julia has been gaining a lot of popularity lately and the users have been coupling in recent years. The number of users has increased to 35 million in 2022, almost five times, which contributes to achieving the milestone of compatibility with Python.
Julia functioned in absorbing the strengths of other programming languages, including C, Ruby, Python, Matlab, and R; plus eliminating their drawbacks such as speed, parallelism, and machine learning.
Python vs Julia
Now that you have understood the basics of these programming languages, let us find the best option in various aspects. Read the following cases so that you can choose the better language to study or use.
The battle has begun!
Popularity and Community
Python stays at the top of the list in terms of popularity. It has been ranked the most popular and used programming language in multiple research projects. The potential reason is its operation for over 30 years. Python has attracted millions of developers directed of its extraordinary features.
On the other hand, Julia is an enthusiastic and worthy competitor but lacks in popularity. Julia’s community is expanding, nonetheless, but is nowhere near python. It has been ranked 36th in the list of popular programming languages.
Julia is an accessible and uncomplicated tool for code conversion purposes. It can convert codes into different data types and formats, uncomplicatedly. In Python, code conversion is a relatively complex process. The code in Python can although be shared with Julia or Program C but the reverse is not possible.
Python offers a large number of extensive and standard libraries that are often supported by third parties. While Julia does not support much library service and is majorly glitched. However, since Julia is a new language, we can expect positive adaptations in the future.
It is hard to praise Julia without mentioning its speed. It surpasses not only python but all other programming languages in terms of speed. It is a compiled language created in its base. Therefore, competitive with other compiled languages as Program C.
However, Python, being an interpreted language takes much time in writing programs. It seeks help from its libraries to increase its pace. Anyways, it loses in speed combat.
Julia was created, keeping data science and mathematical algorithms in mind. It is an immensely helpful tool in dealing with graphs, statistics, and machine learning. Julia mostly involves mathematical terms and is strongly preferred by scientists. Julia syntax and liner algorithms, implemented in it are a great help in data science.
Python does not have linear algorithm implementations for data science. Most users seek help through libraries, but it is a complicated process.
Machine learning follows the same complications. Julia has linear algorithms and math keys and is better at machine learning. While Python utilizes its library extension ‘NumPy’ to research math-related tasks.
If you want to learn either of these programming languages to select your career, you need to know: which offers better job opportunities.
Well, Python owning popularity and a larger community, offers more jobs and a fair salary. The python average salary falls between $110,900. While Julia being less popular has fewer job opportunities. The mean salary of a Julia programmer is $76,735.
The salaries are, somehow, compatible. Hopefully, the scope for Julia increases in the future. Now visibly Python is leading the race for career stability.
Final thought: Python vs Julia
All of this debate suggests there is no obvious champion between Python and Julia. No programming language crowns the position of ‘perfect programming language’. Both got their flaws and the spotlight.
In a nutshell, Python has compiled a programming language that has won the trust of its users. While Julia is an interpreted programming language that overtakes Python in speed, machine learning, and data science.
However, it is still early to say Julia can replace Python in the programming battle. Python has been preferred for small packages or projects while Julia is encouraged in case of large projects and math-related tasks.