As for Julia, the language reads like English, is entirely dynamic, and is still one of the fastest languages in history. For example, Python sacrifices speed for being flexible and dynamically typed, while languages like C, C++, and Java are strictly static and rigid in order to be fast at runtime. Julia excels at certain aspects of programming that no ordinary language does. Yet, when Julia 1.0.0 was released in 2018, they had already delivered on 90% of the promises they had made six years prior.

These out-of-this-world ambitions were, well, ambitious.

As powerful as Matlab for linear algebra.As natural as Perl for string processing.In a blog post explaining why they created Julia, they state that Julia should be: In order for Julia to best the most powerful languages, the founders laid out a specific vision for the language. Shah, all had different backgrounds but shared an appreciation of the collective power of all other programming languages. The four founders who wrote it, Jeff Bezanson, Stefan Karpinski, Alan Edelman, and Viral B. Julia is a scientific computing language that was first announced in 2012. But do these numbers mean Julia will become even half as popular as Python or R in the foreseeable future? Is it worth learning now? Before we answer these questions, let’s take a closer look at the language itself. These are impressive figures, considering that Julia’s earliest stable release was in 2018. In other words, about every 200th programming-related question is about Julia. The actual TIOBE index of Julia is 0.64%, which means that from all programming language-related queries on search engines, Julia’s name popped up 0.64% of the time. Screenshot by the author of the TIOBE Index in May As for its rating among all other languages, the May TIOBE index places it at 25th position, which is three places lower than last year when it jumped from 47th position.

The number of registered packages for Julia reached over 7,400 in April, ten times more packages than had existed six years ago. Julia’s GitHub repo alone stands firm with 39.1K stars, 4.9K forks, and 3.3K issues. The core language and its registered packages have amassed a total of 250k stars on Github, 13 times more than that sum six years ago. To see if they’re right, let’s look at some metrics of Julia’s adoption, which are taken from Julia’s annual newsletter on growth statistics.Īs of January 1, 2022, Julia has been downloaded 35 million times, and it was downloaded three times more often in 2021 than in the last three years combined. Despite its young age, Julia enthusiasts are already calling it the “future language” of data science and AI. In fact, the percentage growth of R usage was much higher than titan languages like JavaScript, Java, C, and PHP in the last year.Ĭombined, Python and R rule the data world, casting a shadow on similar languages.īut one language has distinguished itself from the pack and has slowly been moving towards the light. And while Python is outpacing R on most fronts, R is maintaining its place in the top 15 programming languages in the May TIOBE index, which tracks the popularity of programming languages. When looking at programming languages for data science, Python reigns supreme.

J.u.l.i.a. among the stars download