In this article, we will focus on these topics:
What is Python?
We not gonna talk about the snake but a high-level programming language. Python is developed by Guido van Rossum and introduced in 1991. It is one of the most popular programming languages as it is readable, maintainable, and easy to use and has been loved by a lot of developers and beginners. Python is considered a “very powerful and clear object-oriented programming language”. Users can download it for free as it is available under the GNU General Public License (GPL).
Python's now powerful and versatility have made it an indispensable tool in virtually every scientific application around the world. It is a general-purpose programming language that is compatible with various programming paradigms.
It is widely used in data science, artificial intelligence, machine learning, computer science education, computer vision and image processing, medicine, biology, and even astronomy.
Where does JavaScipt win python?
Python is used for back-end development, which is mainly for web development and is responsible for developing ‘elements’ that users are not able to see. In another word, it‘s server-side implementation.
On the other hand, Python is a better option for processing vast amounts of data in machine learning where to solve a specific problem. Due to its readability and easiness of use, it has been loved by a lot of developers and also novices.
Furthermore, even though Python might take longer to respond, there are some methods for improving its performance by benefiting from the C programming language with Numpy and Cython. As Cython is a Python compiler, it allows developers to create fast C modules, which speeds up the execution of raw Python code.
There is a sightly difference when it comes to scalability. Python uses a global interpreter lock (GIL), in simple words, it is a lock, also known as mutex (What is GIL?) which allows only one thread to hold and control the Python interpreter. However, GIL ensures only one thread can be running at any given time.
Obviously, GIL causes it harder to use multiple processors with thread but the multiprocessing library, as a tool from python itself — is allowed to use by developers to fully leverage multiple processors on a particular machine.
They have significant differences, but they both share the basic elements required to write powerful programs.
Thanks for reading, and if you found this article helpful, you might want to check out my other articles as well!
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This article is written by Han Sheng, Technical Lead in Arkmind, Malaysia. He has a passion for Software Design/Architecture related stuff, Computer Vision and also Edge Devices. He made several AI-based Web/Mobile Applications to help clients solving real-world problems. Feel free to read about him via his Github profile.