An Easier Way to Keep Old Python Code Healthy and Secure
Jul 22, 2022
Python has its pros and cons, but it's nonetheless used extensively. For example, Python is frequently used in data crunching tasks even when there are more appropriate languages to choose from. Why? Well, Python is relatively easy to learn. Someone with a science background can pick up Python much more quickly than, say, C. However, Python's inherent approachability also creates a couple of problems. Whenever Python is updated, it means a big refactoring workload, which often gets dealt with poorly – or not at all. That leads to poor performance and security vulnerabilities. But maybe there is a better way: a tool to keep your Python tasks running smoothly and securely day in, day out. Let's take a look. It's slow, but it does the job Python isn't the fastest language around, but despite its comparative disadvantages, you'll often see it used for intensive data crunching operations. Think machine learning, computer vision, or even pure math in high-perform