Skipping out on Python updates means leaving potential financial gains and performance improvement on the line, as well as missing out on substantial developer efficiency boosts.
In the ever-evolving world of software development, the importance of keeping up with updates, particularly in the case of Python, has become a pressing concern for many enterprises.
According to a recent study, a significant number of enterprises are still using older versions of Python. Over three-quarters (83%) are relying on versions older than 3.13, with just 15% using the latest version. A closer look reveals that just under a quarter (21%) are using Python version 3.11, and a mere 25% have not had the time to update their Python version. On the other hand, 35% of enterprises are already using Python version 3.12.
Maurice Kalinowski, product director at Qt, and Daniele Volpe, a software engineer at SecureFlag, both agree that updating any technical dependency is a concern for development teams. Kalinowski emphasized that while it's tempting to stick with what works, he acknowledges the potential risks associated with upgrading, such as potential regressions, incompatible changes, or removed functionality, especially when it comes to the underlying programming language.
Volpe, however, points out that missing out on language improvements in newer versions of Python could make day-to-day work less efficient. He explains that slower runtimes lead to slower feedback loops, slowing down the development lifecycle. Moreover, he notes that developers spend more time waiting on tests, builds, or jobs to finish when using older versions of Python.
Running old Python versions adds up over time, according to Volpe. This results in slower runtimes and higher cloud costs. However, upgrading to newer versions of Python can result in significant performance benefits. For instance, if an enterprise is on Python version 3.10 or older, upgrading can result in a whopping ~42% speed increase with no code changes, and memory use can drop by ~20-33%.
The benefits of upgrading are not just limited to performance improvements. Upgrading to Python 3.11, 3.12, and 3.13 all include major performance benefits. Leading technology companies like Google, Meta, Microsoft, and Amazon are among the primary users of the latest Python versions, especially in AI, data analysis, and cloud infrastructure.
JetBrains, a prominent player in the software development industry, expects containerization to provide more flexibility for enterprises and ease the transition to the latest version of Python. The article also mentions that JetBrains CEO Kirill Skrygan believes AI is transforming software development, and developers need to transform with it.
AI coding tools are finally delivering results for enterprises, according to the article. These tools are designed to automate repetitive tasks, reduce human error, and improve productivity. As software development continues to evolve, it's clear that enterprises need to keep pace with the latest technologies to remain competitive.
However, it's important to note that more than half (53%) of enterprises are satisfied with the performance of their current Python version. If it isn't broken, it's not necessary to fix it, as Kalinowski aptly puts it. The key is to find the right balance between staying current and maintaining stability.
In conclusion, while upgrading to newer versions of Python can offer significant benefits, it's crucial for enterprises to weigh the risks and benefits carefully and plan their upgrades strategically. By doing so, they can ensure they're staying competitive in the rapidly evolving world of software development.
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