Why is Python the #1 Programming Language of 2019?
The IEEE, the world’s largest technical professional organization, has been around in some form for over 150 years to support electrical, electronic, and computing professionals in their work. As part of these efforts, they released a list of the top programming languages every year, and Python took the top spot for the second year in a row – beating out Java, C++, JavaScript, and other top languages.
Written by Luis Paradela|Posted on October 18, 2019
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The IEEE, the world’s largest technical professional organization, has been around in some form for over 150 years with the goal of supporting electrical, electronic, and computing professionals in their work. As part of these efforts, they release a list of the top programming languages every year, and Python took the top spot for the second year in a row – beating out Java, C++, JavaScript, and other top languages.
Their scoring is based on metrics from a variety of sources, including Google searches, social media, GitHub, Stack Overflow, Reddit, Hacker News, CareerBuilder, and IEEE online resources. In 2018 and 2019, Python easily walked away with the highest score, and has proven itself to be one of the most popular programming languages in the past decade. This is likely driven by its accessibility, flexibility, and efficiency, as well as the wide range of frameworks and toolkits which are perfect for developing the increasingly popular AI and deep-learning applications we see today.
Why Are More Companies and Developers Choosing Python?
Both execs and developers see a number of potential benefits to Python development. These include:
- It’s easy to read: Because of its syntax that focuses on readability, developers of any level or language can easily read, translate, or interpret Python. This makes it less cumbersome and ultimately less expensive to maintain.
- It’s easy to write: Python offers dynamic typing and dynamic binding options that allow the developer to write code similarly to how they would write their thoughts. And, if your programming team encounters a problem, it’s easy enough to find online resources to help them resolve issues.
- Debugging is more efficient: In Python, there is no compilation step, so a bug or a bad input will not cause a segmentation fault. This saves time, reduces costs, and improves overall efficiency.
- There’s a library for everything: Particularly in AI, but for all types of projects.
- It’s versatile: Python can be run on almost any computer without having to change programs or operating systems. It can also be combined with a wide variety of frameworks to suit any project.
- Low startup costs: All of the necessary tools to begin developing with Python are available open-source and free of charge.
Common Python Projects: Machine Learning, Backend APIs, and More
No matter how complex or how integrated, Python is scalable to any particular application’s needs because of the impressive number of specialized libraries available for it. It’s particularly well-suited to projects involving backend APIs, multiple system integrations, machine or deep learning software, financial sector software (including cryptocurrency & blockchain development), eCommerce software development, and many other custom web applications.
Questions about Developing with Python?
If you have questions about Python or developing a custom solution for your business with Python, visit our website for more information or contact us today. We’re happy to set up a meeting with one of our in-house Python experts to discuss your development needs.
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Luis Paradela
Chief Development Officer
Co-Founder
Buenos Aires
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