In terms of Analytics. Is Go set to take on Python?
When Rossum developed Python in the 1980s, did he know that it would become the world’s most widely used programming language? More than 8 million developers today, use Python as their primary development language. Thanks to its abundance of libraries, and plenty of applications. Be it website development, machine learning, or analytics, Python is being used everywhere that people can think.
One of the most important implementations of Python is observed while analyzing data. Ever since the wave of digitization swept industries off their feet. Be it healthcare, business, or any other industry. Developers are utilizing Python for data analytics, and it is proving to be great.
There are a few advantages of data analytics. On the one hand, it is helping people see the future with help from the past and the present. On the other hand, it is helping us to make better decision making in all the processes. The point is, whatever people or industries want to accomplish with the data, Python is assisting in it. Python becomes a tool that makes complex and tangled data appear sorted and clear.
As the world evolves, new programming languages keep on emerging. They are born out of the shortcomings of existing languages and help improve the performance of the system in one way or another. One such programming language is Google’s Go.
Golang or Go is a programming language developed by Google, whose idea was realized in the year 2007. However, it was only in 2009 that the world saw its first release. Go is relatively much fresh than Python. Being known for ten years, why are people realizing Golang’s important now more than ever? Is it because the light around Python is dimming? Whatever be the reason, recent events have suggested that Google’s Go has more than a few advantages over Python, especially when we talk of data analytics.
Google’s Go was born out of the need for a language that was based on the syntax of C. As a result of this, the lead developers at Google Robert Greisemer, Rob Pike, and Ken Thompson created Go with many features of modern languages. Having said this, developers can easily find object-oriented features such as operator overloading, pointer arithmetic, along with others. Apart from this, Go also has a robust library with unmatched performance and speed.
Even though Python can do a lot of what Go does, it lacks in some aspects. When it comes to speed, dynamic typing, GIL, concurrency support, etc. Python shows clear signs of limitations for analytics. Let’s take a more in-depth look at what this comparison between Go and Python means for analytics.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
For Big Data Analytics, the challenges faced by businesses are unique and so will be the solution required to help access the full potential of Big Data.
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