The Python programming language is used extensively in scientific computing due to its versatility. It is being used in all areas of computing, from small embedded systems to large-scale data analysis and scientific supercomputing. But how did Python become so popular in scientific computing? Read on to find out.

Python’s Humble Beginnings

Guido van Rossum created Python as a hobby project in the early 1990s. At the time, van Rossum was working on the Amoeba distributed operating system at Centrum Wiskunde & Informatica (CWI) in the Netherlands. He needed a scripting language for a small project and decided to create his own.1

Van Rossum named the language after the British comedy group Monty Python. He intended the name to be short, unique, and slightly mysterious.1

The first public release of Python was in 1991. Python was highly popular from the beginning, with van Rossum receiving many requests for new features and improvements. Slowly but surely, the language began to gain traction among developers.1

The Current State of Python

Nowadays, millions of developers use the Python programming language across the world. It has a thriving open-source community and is supported by some of the biggest tech companies in the world.

Python is now the fourth-most popular programming language in the world.2 This is due in part to its versatility and ease of use. Here is a look at six reasons for the popularity of Python in scientific computing.

  • Easy to Learn: One of the main reasons for Python’s popularity as a programming language is its simplicity. The language has a very concise syntax that is easily readable and understood. This makes Python an excellent choice for beginners who want to get started with programming. At the same time, Python is also powerful enough for experienced programmers to do complex tasks. The language has a large standard library that covers many common programming needs. And tens of thousands of third-party libraries are also available for even more specialized tasks.
  • Free and Open Source: A major benefit of Python is that it is free and open-source. This means that everyone can use the language without having to pay any license fees.5 There is also a huge community of developers who contribute to the language and its libraries. This combination of being free and open-source makes Python attractive for scientific computing. Scientists and engineers can use the language without worrying about the cost. And they can be confident that a large community of developers is constantly improving the language.
  • Vibrant Ecosystem: The Python ecosystem is one of the richest of all programming languages. There are tens of thousands of open-source libraries available for Python. There is a library for almost anything you want to do with the language. For scientific computing, this is a huge advantage. There are libraries for numerical computing, data analysis, machine learning, and many other tasks. In short, Python can be used for almost any scientific computation you can think of.
  • Runs Everywhere: Python is a cross-platform language. It can run on any computer, from laptops to supercomputers. It can even be used on embedded systems like Raspberry Pis. This is a big advantage for scientific computing. Scientists and engineers often need to use different types of computers for their work. With Python, they can write their code once and then run it on any type of computer they need.
  • Fast Enough: Of the existing programming languages, Python is certainly not the fastest, but it is efficient for most tasks. And it is getting faster with every iteration. There are also ways to speed up Python code. One common approach is to use compiled extensions written in languages like C or Fortran. There are two main advantages to this: the convextensions written in languages like C or Fortran. There are two main advantages to this: the convenience of Python and the speed of a compiled language.
  • Major Companies Support Python: In recent years, some of the great players and bigwigs in the tech industry have adopted Python. Google, Microsoft, and Amazon all use Python in their businesses.3 They have also invested heavily in the development of the language.

Python enjoys a big vote of trust. It reinforces the belief that major companies think it is a language with a bright future. Thus, a lot of capital, time, and resources are invested in the continued development of Python.

These are the six main reasons for Python’s popularity in scientific computing. There is no doubt that Python will continue to be used on a large scale and will become even more popular in the scientific computing community in the years to come.4

If you found this blog interesting and want to learn more about Python and scientific computing, we suggest you visit BYJU’S FutureSchool Blog.

Disclaimer: This article is being provided for informational purposes only. Any references herein to any organizations, specific programming languages, processes, or services by trade name, trademark, brand, or otherwise, do not constitute or imply endorsement or recommendation by BYJU’s FutureSchool. All trademarks and brand names are the property of their respective owners and are only mentioned for informative purposes. These trademark holders are not affiliated with BYJU’s FutureSchool or its website, nor do they sponsor or endorse BYJU’s FutureSchool or any of its products.

References

  1. Python History – javatpoint. (n.d.). www.javatpoint.com. https://www.javatpoint.com/python-history
  2. Most used languages among software developers globally 2022 | Statista. (n.d.). Statista. https://www.statista.com/statistics/793628/worldwide-developer-survey-most-used-languages/
  3. 46 Famous Tech Companies That Use Python In 2022 – GUVI Blogs. (2022, May 4). GUVI Blogs. https://www.guvi.in/blog/famous-tech-companies-that-use-python/
  4. Panda, T. C. (2022, March 28). Is Python The Future Of Programming? Medium. https://medium.com/interviewnoodle/is-python-the-future-of-programming-f04844c07031
  5. About PythonTM | Python.org. (n.d.). Retrieved December 12, 2022, from https://www.python.org/about/ 

About the Author

More than just Coding and Math! Our proprietary, activity-based curriculum with live, real-time instruction facilitates: Problem Solving. Creative Thinking. Grit. Confidence. Communication