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Python is one of the hottest programming languages in the world right now. According to StackOverflow’s Developer Survey 2021, Python is the third most popular programming language. It is primarily due to its easy-going syntax coupled with powerful dynamic typing and binding. In this article, we will focus on building efficient and scalable applications in Python using popular design patterns. Design patterns are standards or conventions used to solve commonly occurring problems.

There are a variety of technology stacks for Artificial intelligence (AI), Machine learning (ML) and data analytics applications. However, the ideal programming language for AI must be powerful, scalable and readable. All three conditions are met by the Python programming language. With outstanding libraries, tools and frameworks for AI, ML and data analytics, Python has proven success leveraging all three technologies.

Memory leaks are one of developers’ worst nightmares. They can easily take down a healthy running application within hours if not minutes. It can be difficult to detect some of such leaks since they slowly grow and take over your app’s available memory. On top of it, each programming language manages memory in its own unique ways and hence can leak memory in different ways. Hence proactive measures to identify and prevent such leaks from happening is crucial.

Flask is the most popular micro-framework for web programming in Python. Known for its lightweight build and flexibility, it is a fan favorite amongst beginners because of how easy it is to get started with, especially for building prototypes and small-scale projects. Even though Flask is one of the faster frameworks out there, there’s almost always scope for improving performance in web applications. Things might run fine when you serve minimal, static websites with ample compute resources.

With a plethora of programming languages available today, the important question is “Which programming language does a programmer prioritize learning?” Without a doubt, the world of programming revolves around experienced programmers with cutting-edge coding skills. So, if you’re planning a successful career in software development, understanding the hottest, trending languages is key.

Flask and Django are two of the most popular Python packages. More importantly, they are the two most preferred web frameworks you can use with the language. Both frameworks are open-source and offer excellent APIs for developers to build robust Python web applications. While both frameworks serve the same purpose, they take two philosophically opposed routes to achieve it.

You just finished creating your web application and want to clean it from any possible bugs, imperfections, and performance issues. But you feel a bit overwhelmed with the choice of testing tools and frameworks and the articles singing their praises. In this article, we will explore using Selenium with Python for test automation.

I have a bit of a confession to make, I’ve never really bothered to learn Python. The last time I briefly used it, Python 3 had just been released and was being ignored by almost everyone due to all to breaking changes people had porting over to it from Python 2. This is crazy, as in my opinion, Python is only behind JavaScript in terms of the most used language in the world. I have no excuse not to learn it and see what the fuss is all about!