No other programming language has added more users faster than Python. Second only to Java, Python is currently the most common choice for developers.
Tech giants including Google, Dropbox, Instagram and Spotify use the language as part of their systems. Not only that other industries like the media, healthcare, and even NASA are also using Python. DZone describes Python code as “neat, readable, and well structured”, which is why it is so popular. Industry experts also predict that the programming language will soon edge out C, C++, and Java in terms of its user base.
One reason for Python’s popularity comes from the drastic changes it has undergone since its release 25 years ago. Especially since Python 3.0 introduced the constructive design feature aimed at avoiding duplicate constructs and modules in 2008.
Python is also one of the most versatile languages with an extensive library support and strong integration features. It supports enterprise applications through its COM and COBRA components, integrates with other languages like Java through Jython, and is able to process XML. By being more readable, it’s easier to break up functions in Python. This includes increasing code testability and maintainability.
Vital in Data Science
While Python is a general programming language, it is commonly used for data science applications. A survey conducted by the Python Software Foundation found 58% of users use the language for data analysis. While the contending language R is made solely for statistics and data analysis, Python has increased its user base in data science because of its added functionalities. Its seamless integration with MATLAB alone, with the use of libraries including Numpy and SciPy, makes it an indispensable tool for data scientists. As industries are becoming more data-driven and data-reliant, Python is now a necessity for programmers across a multitude of industries.
Best for Machine Learning
Machine learning (ML) is ‘one of the drivers of the fourth industrial revolution’. Data is key in developing machine learning algorithms. Python makes interpreting data faster as popular libraries like TensorFlow, Numpy, OpenCV, and SciKit to name a few, are easier to integrate within its ecosystem. Today, Python is the most common language used to deploy ML and artificial intelligence (AI). As more businesses embrace AI and autonomous business processes there will be an increase in the demand for full-time employees and freelancers who are skilled in Python.
Its Highly Accessible
As a human-readable language, learning Python is relatively easy compared to C and C++. With less emphasis on syntax and more on readability, many suggest learning Python as your first coding language. A survey from the Association of Computing Machinery revealed that since 2014, more US schools are using Python to introduce programming to students than Java.
The rising popularity of the program also means more support and documentation from the growing community of users and experts in the field. Many online courses provide a positive feedback loop that ensures that learning Python is easily accessible for beginners and experts alike. It also goes to show how immensely valuable these courses have become across the world.
The momentum of Python’s user growth provides opportunities for data-driven innovation in various fields and industries today—making it a vital skill for the modern workforce. If you are thinking of a career in programming or looking to expand your portfolio, learning Python should be very high on your list of priorities.