Mojo vs Python: Is the Newcomer Set to Replace the Old Favorite?

A variety of causes contributed to Python's rise. Its simplicity and ease of use are two of the key reasons for its appeal. Python, in contrast to other programming languages, has a clear and succinct syntax that is simple to read and grasp. As a result, it is an excellent language for novices, and it is extensively used in educational institutions to teach programming.

Python's adaptability is another reason for its popularity. Python has many uses, ranging from web development to scientific computing, machine learning, and artificial intelligence. It's also popular in data analysis and visualization, as well as automation and scripting.

Python has also proven to be effective in replacing previous technologies. Python, for example, has essentially overtaken Perl as the preferred language for scripting and automation. In scientific computing, it has also supplanted other programming languages such as Matlab.

Python's primary features include dynamic typing, garbage collection, and object-oriented programming capabilities. Python also has a strong and active developer community that contributes to the language by providing libraries and frameworks that make application development easier.

With so many advanced features and a simple syntax Python is still one of the most widely used programming language . But here comes into picture a new language named 'Mojo' which claims to be 35000x faster than Python.

Mojo is a new programming language that combines the best of Python syntax with systems programming and metaprogramming to bridge the gap between research and production.

With Mojo we can write efficient codes which has a faster execution time than C language and syntactically similar to Python codes which are simple and readable.

With this language AI model training can become very fast and can also develop applications quickly.

While there are many ongoing projects to make Python faster. Some of the examples are 'JAX' - used for high performance and numerical computing, a python compiler named 'Codon'- compiles python code directly to native machine code thus increasing the efficiency of each thread by 10-100 times.

Now the question arises how cum this language is that much efficient that it becomes 35000x faster than python, so this is because of the compiler infrastructure which is being used over here i.e 'MLIR'. We are going to discuss about MLIR in the upcoming blog.

One more significant feature is that it is a superset of Python so it will also be able to access different libraries thus reducing size of code and improving efficiency as seen in Python.

Now the big question arises that is Mojo going to replace Python ?

So here the answer is not that easy because it is just in the testing phase and the developers have claimed that it will take some time to add all these features. Now how much time that's a big question. Let us assume that it takes around 1 to 2 years to completely implement the features and usability but till that time there will be many upgrades in the Python as well with the usability and requirements according to the demands at that time since technology is emerging so quickly so the features which are required today after 6 months or 1 year they may become obsolete and something else is required.

But yes this can be a great language for Researchers and Data Analysts to work on.

Comment down your views whether Mojo can be a better alternative for Python used worldwide or not.