Python is a trending programming language that came out at the end of the 20th century. It finds its use in creating websites, developing new software, and in school subjects like mathematics and can be used to perform complex mathematical calculations.

Some of the reasons for the popularity of Python include its use in different platforms like Windows, Mac, Linux, etc. Not only that but the syntax used for writing with Python is comparable to the English language and takes fewer lines than the other programming languages.

Very recently Julia, another programming language, has posed competition to Python by nearing the top 20 programming languages in the annual TIOBE index.

It has found its use in solving complex computations apart from being used in data analysis. It has even surpassed Matlab because of its great speed and is completely free.

Introduction to Julia

Julia, which was initially developed by four people at the Massachusetts Institute of Technology, is an extraordinary and effective programming language. Julia is a high throughput language that can be applied to solving problems of scientific nature. Just like R software, it can be employed for statistics and data analysis.

The unique advantage that Julia has in comparison to other programming languages is its extra high speed because of which it can execute at a much higher speed than Python and R. Two intricate but complex phenomena i.e., cloud computing and parallelism are being performed by Julia as it assists giant data analytics which in turn have vital importance in big data analysis.

To gain such attributes, Julia has on one hand followed the ways of descent of the previously developed programming languages but on the other hand, it has taken a lot more features from other languages like Perl, Python, Lua, Lisp, and Ruby.

Features of Julia

Some of their FEATURES of Julia are mentioned under

1. Fast

The motivation behind the development of this language was to be able to come up with a high-performing language. Because being a low-level virtual machine, Julia programs compile effective native code which enables it to perform on various platforms as well.

2. Dynamic

Julia has a high-level construct that allows it to carry out one command at a time. It is dynamically typed and provides good support for interactive use.

3. Reproducible

Reproducible environments make it possible to recreate the same Julia environment every time, across platforms, with pre-built binaries.

4. Composable

The methods to operate with Julia are so convenient that there is no requirement for customization and even putting all The blocks together is enough to be operated on, eg: plain Julia arrays or tuples, etc.

5. General

Julia provides asynchronous I/O, metaprogramming, debugging, logging, profiling, a package manager, and more. One can build entire Applications and Microservices in Julia.

6. Open source

Julia, which is made available under an MIT license, is an open-source project with about 1000 contributors. The source code is available on GitHub.

Introduction to Python:

Python, which is a very commonly used programming language, was developed for the first time in 1991 by Guido van Rossum. It is a high throughput and efficient programming language that was improvised by the Python Software Foundation. Its important features were that the reading of the code was comparatively easier and its syntax is such that the concepts can be written down in fewer lines of code.

This language is very expeditious and merges the systems very effectively. Also, two types of Python versions have been formed which are Python 2 and Python 3 which are both distinct in their properties.

Features of Python

Some of the features of Python which make it very famous among users are as under

● ‌It is very easy to learn and make use of it. It finds acceptance by the lopers because it is an extraordinary programming language.

● ‌ It can be downloaded free of cost and you will find it as a You can download free and publicly accessible online.

● ‌Its concepts are Object-oriented which include polymorphism, encapsulation, and classes are supported.

● ‌ Not only these but this language can be further extended, and even can fit in the C/C++ codes.

● ‌ There is no requirement of putting together the language because it is an interpreted language. Hence, it is very efficiently debugged as lines are executed line by line.

● ‌Its typing occurs synchronously which means that it doesn’t need variable declaration before usage, they can be easily written down when running this language.

● ‌ Python libraries can be developed which then can be used to import the codes and thus the codes need not be rewritten.

Julia vs Python: Differences

Given below now is a comparison of the two languages so a person can select the one he wants according to his needs.

● Popularity

So far, Python has been the most famous programming language which has seen a growth period of more than 30 years and is continuing to grow further. It provides practical solutions to almost every problem. Julia, on the other hand, can also be used in multiple platforms but its growth depends upon its expansion in the world of data science and an increase in the number of its development options.

● Speed

As far as speed is concerned, Julia overpowers Python because it doesn’t need an interpreted mode for execution. Rather, it is built on an LLVM network which allows it to handle big data and data analysis which needs a lot of speed. Hence, it is more effective in its performance.

● Libraries

Regarding the use of libraries, Python has a very strong hold because it makes Python coding very easy. That is because the codes which are imported into these libraries can be used as functions. This becomes a major setback for Julia whose libraries suffer from inadequacy and there are only a few of these in Julia.

● Dynamically Typed

Even though both programming languages have the advantage of dynamic typing which enables a user to use variables without any direct declaration, Julia is also a static language. Therefore, users can make use of it according to their needs.

● Parallelism

Both languages can carry out simultaneous operations. That means the segmentation and desegmentation of data are very important for Python. in comparison, Julia makes use of more complicated techniques. Also, the grammar used for parallelization is less top-heavy as compared to Python’s, which decreases its applicability.

● Versatility

Python makes the operations of coding and reading very easy and that is why it’s considered trendy nowadays. It is very adjustable when it comes to making new websites and scripting them. It is being used by a lot of developers because it can carry out the work in an effective way and in less time because of the libraries available. Python is more flexible in answering most of the difficulties faced in computer programming than Julia.

What makes Python a better option than Julia?

Even though Julia’s is increasing in its achievements and popularity, Python still isn’t out of the battle. Each programming language has its pros and cons. Both these languages have a brilliant future ahead concerning their use in data analysis and data science apart from their use in the growing fields i.e., artificial intelligence and machine learning.

Julia has started to make its way in these areas but it still needs to hit the ground to stand shoulder to shoulder with Python and then only it can become one of the most accepted programming languages in the industry. Till then, Julia’s popularity can in no way affect the momentousness of Python across all technology fields.