Python’s popularity shows no signs of fading – here’s why software developers love it
Python’s popularity continues to surge, according to the Tiobe index, with the programming language reaching a 25.25% share in May.
Figures from the index show Python now holds the highest rating for any programming language since 2001, surpassing Java’s record-breaking rating in June 2001.
But as Tiobe CEO Paul Jansen noted, this was the first month of the Tiobe index and there were far fewer languages being tracked.
Nonetheless, the programming language has surged in popularity in recent years, and in the last month alone increased by around 2.2%, with Tiobe figures from April showing the language boasted a rating of 23.08%.
Notably, May 2025 marked another record-breaking month for Python, according to Jansen. It’s the first time a programming language has held this big a lead over other languages ranked in the index. Python currently holds a 15% lead compared to the second-placed language, C++.
So what is it about Python that makes it such a popular choice for devs? There are a number of factors here, but one key appeal is its simplicity, experts told ITPro.
Python’s ease of use is a major draw
According to Allon Mureinik, senior software engineering manager at Black Duck, ease of use is a major draw, with the programming language having a “very low barrier of entry”.
“While you can technically write code in any language with no more than a text editor, Python is one of the few programming languages that actually make it practical”, he told ITPro.
“All you need to start coding in Python is the Python binary itself and a text editor, and you’re good to go.”
Mureinik added that this ease of use is a “huge factor” even for seasoned developers while the ecosystem surrounding the language is vibrant and still growing at pace.
“The syntax is simple without being simplistic, and the language constructs themselves make a lot of the developers’ routine tasks (such as manipulating or transforming data structures) very easy,” he said.
“Python has a rich ecosystem that offers libraries to integrate and interact with a wide variety of services, protocols and environments without having to implement those integrations from scratch.”
Darren Meyer, Security Research Advocate at Checkmarx, echoed Mureinik on the ecosystem front, noting that the Python community “really participates actively in thinking about security and compliance, which is appreciated”.
“While parts of the ecosystem (like PyPI, the Python Package Index which makes it easy to adopt open source Python libraries) have had security issues in the past, the community and maintainers are very responsive,” he told ITPro.
Python is the language of choice for AI developers
With the advent of generative AI, it’s hardly surprising that Python has soared higher in popularity, experts told ITPro. Indeed, research from Snowflake last year showed it has now become the “programming language of choice” for AI developers.
Analysis by the company found Python use grew by 571% on its Snowpark platform, highlighting its growing appeal. Moreover, this marked a considerable increase compared to other popular languages, such as Java and Scala.
“Python skills will be increasingly essential to development teams as they venture into advanced AI,” the report said.
So what makes it ideal for AI development? According to Meyer, Python is an “excellent language for rapid prototyping”, meaning developers aren’t bogged down by cumbersome workflows.
Meanwhile, Mureinik told ITPro its simplicity and ease of use again offers marked benefits here – an aspect of the language that Snowflake said enables developers to “focus on solving AI problems rather than parsing abstract syntax”.
“Python is a very convenient language for integrations and for stitching together workflows,” he said. “This makes it the obvious choice for programs that take data from source A, use it in a prompt to an LLM (through a Python client library, of course), and then take the output from that prompt as input for system B.”
Python does have some limitations
While Python has a lot going for it, there are certain limitations – particularly with regard to speed. Jansen specifically highlighted this issue in the latest Tiobe index update, suggesting that Python’s low performance is the “only reason other languages still have a reason for existing”.
This lower performance is due to how Python operates. It relies on an ‘interpreter’, a program that processes and executes code from a script file, or in some cases interactively. This allows programmers to test code – and run said code – on a line by line basis.
Notably, Python uses a Global Interpreter Lock, or ‘GIL’. This is a mutex, or lock, which limits the throughput of code, Jeff Watkins, chief technology officer at CreateFuture, told ITPro.
“The interpreter and its “global interpreter lock” limit throughput to a single, slow thread, so heavy-duty computing needs to be offloaded to C/C++ libraries,” he explained.
Efforts have been made to increase interpreter performance and remove these single-threading limitations, Watkins added, but still leaves developers wanting when compared to the performance of languages such as C++.
“Python will likely never outperform C++, but it doesn’t need to, as it was never its original purpose,” he noted.
Other limitations of Python are due to its dynamic typing approach, which Watkins said “trades off any ‘compile time’ safety for ease of implementation” and therefore can result in errors.
“This looser approach to typing means that runtime errors can slip through the net unless you put in belt and braces testing and typing hints through annotations,” he explained.
“Outside of niche projects, it also doesn’t have a mobile or client front-end footprint,” Watkins added. “As the Web runs on HTML, JavaScript, CSS, and WebAssembly, there’s no native way of using Python in the browser. Mobile and client browsers are also payload and performance-sensitive which makes it a less reasonable choice.”
Watkins said these notable gaps in performance and versatility explain why Python has supplemented other ecosystems, echoing Jansen’s earlier comments.
“Python’s rise is predictable, sensible, and more of a realignment than a hostile takeover,” he said.
“It has become the default high-level tool of choice, leaving space for complementary languages where absolute speed, strict typing, or native client experiences are paramount.”
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