Python vs Julia is the crucial battle of modern time. Both of these programming languages are offering massive numbers of functionalities to the users. If you also want to pick the best between Python vs Julia
Here in this blog post, we will compare these programming languages based on some criteria. First, we start with an overview of both of these programming languages; then we will go further. Here we go:-
Python is one of the best programming languages of the modern day. The majority of programmers like to work on Python because of its simplest syntaxes. Thus Python code is quite readable and easy to understand by the programmers.
It was developed around 1990, but it did not get success in the initial years. But after the boost in web applications and data science, Python is getting more value and importance than other programming languages.
That is why many programmers and coders either start their programming journey with Python or switch to Python. That is why there are more than 7 million python programmers and coders globally, and this number is growing rapidly. Most of the startups prefer Python because it is an open-source programming language.
It is used in almost every popular app such as Netflix, Instagram, Google, and Spotify. Python is the first choice for data science, machine learning, deep learning, and artificial intelligence.
Python is quite slower than most programming languages. It can also work seamlessly with other programming languages; it means you can easily integrate other programming codes with Python.
Julia is one of the leading programming languages of the modern day. It is the most flexible programming language. It was introduced in the year 2012. It is the best programming language that has almost the same functionality as Python.
Apart from that, it also has the same computational capabilities that are offered by Matlab. It is also one of the fastest programming languages in the world, similar to C.
But sometimes, it executes the code even faster than C programming. That is why a massive number of developers are shifting towards Julia. And it is becoming one of the leading programming languages in the world.
Julia is the best programming language for data science, complex linear algebra, data mining, and machine learning. In other words, it is a modern world programming language that supports all the latest technologies.
It is a highly interactive programming language that supports the REPL to add commands and scripts easily and quickly. Julia supports both LLVM and JIT for the fastest execution. It offers straightforward and powerful syntax.
It also supports various external libraries used to integrate Julia with other programming languages such as C, C++, Java, Python, etc. It supports both the statically typed and dynamically typed programming language.
You can also check variable results and add breaks in Julia with the help of its debugging suite. It also supports metaprogramming in which the program written in Julia can generate other Julia apps.
Python vs Julia
When we talk about Python, then Julia is quite faster than Python. It is a compiled programming language; therefore, Julia’s code is pre-compiled and can be directly executed. It can also execute with other programming languages such as Python, C, R, C++.
It offers rapid and efficient results to the programmers without any additional optimizations and native profiling techniques. It is quite easy to compile the code that is written once in other programming languages.
That is why it is becoming more popular for data science and machine learning. It can execute massive lines to code in less time as compared with Python. When we try to execute the code in Python, it takes more time than usual because it needs to be optimized using several methods.
The major motive behind the development of Julia is speed. It is the only fastest programming language that is too powerful. It also has the same functionality as Python, but it also offers the same speed as C.
It has been estimated that Julia offers one petaflop per second when it is in peak performance. It offers the JIt compilation and type declaration to execute codes that allow run time compilation.
It is designed for speed. That is why it quickly executes the codes. If we talk about Python, it is fast in some cases but not as fast as Julia. But there are few ways to speed the code execution in Python with external libraries, optimization tools, and third-party JIT compilers.
When we talk about libraries, then Python is the king of libraries. There are a massive number of libraries in Python for different purposes. Julia has a limited number of libraries.
Any organization does not maintain Python’s libraries because of its open-source nature; you can’t find well-managed libraries for data plotting and data execution. On the other hand, Julia’s libraries are well maintained and steadily growing.
Tools support is crucial for every programming language. Python supports a massive number of tools as compared with Julia. Python is a supportive and active programming community; that is why it has brilliant tool support.
Julia is a new programming language and still needs to develop much more that is why it doesn’t support great resources.
Python has one of the largest programming communities in the world. It has crossed the three-decade mark recently. It became popular in recent times, and many developers became a part of its community.
It has one of the vast and most supportive programming communities. Because of its community, Python has become one of the fastest-growing programming languages. There are many resources in Python libraries.
That is why programmers can easily resolve their problems and get assistance from other programmers to solve the problem. Whereas Julia has not a massive community,
Now let’s end this comparison with an opinion from our experts. Julia’s major motive was to create a faster programming language for machine learning and scientific calculations. It is one of the most popular programming languages among professionals.
It is as easy as Python, but it is quite faster than Python in terms of speed. In comparison, Python is the greatest programming language of all time. You can speed up the python code execution with the help of external libraries.
But the execution will not become super fast. Both of these programming languages have excellent support for modern and futuristic technologies. Apart from that, you can also use these programming languages for data science and machine learning.
But because of the large community support and popularity, you should go with Python. Because whenever you get stuck in a problem, many developers can help you.
On the other hand, you can go with Julia if you need speed and you also can get rid of any problem without having additional help. Overall, Python can be a better option for beginners. In contrast, if you spend some time learning Julia, you find it more efficient and powerful to perform most of the operations than Python.