This is the Clash of the Titans!!
Well, some of the reasons for that are:
Python is an interpreted, general-purpose programming language that has multiple uses ranging from web applications to data analysis. This means that Python can be seen in complex websites such as YouTube or Instagram, in cloud computing projects such as OpenStack, in Machine Learning, etc. (basically everywhere!)
Python has been steadily increasing in popularity so much so that it is the fastest-growing major programming language today according to StackOverflow Developer Survey Results 2019.
All these trends indicate that Python is extremely popular and getting even more popular with time. Some of the reasons for this incredible performance of Python are given as follows:
- Python is Easy To Use
No one likes excessively complicated things and that’s one of the reasons for the growing popularity of Python. It is simple with an easily readable syntax and that makes it well loved by both seasoned developers and experimental students. In addition to this, Python is also supremely efficient. It allows developers to complete more work using fewer lines of code. With all these advantages, what’s not to love?!!
- Python has a Supportive Community
Python has been around since 1990 and that is ample time to create a supportive community. Because of this support, Python learners can easily improve their knowledge, which only leads to increasing popularity. And that’s not all! There are many resources available online to promote Python, ranging from official documentation to YouTube tutorials that are a big help for learners.
- Python has multiple Libraries and Frameworks
Python is already quite popular and consequently, it has hundreds of different libraries and frameworks that can be used by developers. These libraries and frameworks are really useful in saving time which in turn makes Python even more popular. Some of the popular libraries of Python are NumPy and SciPy for scientific computing, Django for web development, BeautifulSoup for XML and HTML parsing, scikit-learn for machine learning applications, nltk for natural language processing, etc.
So What’s the Conclusion?
However, this will merely impact the relative popularity of these two languages and not specify which among them is the better language. That choice is entirely subjective and may depend on multiple factors such as project requirements, scalability, ease of learning as well as the future growth prospects.
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