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Flask vs. Django: Beyond Comparing Simple & Complex

It doesn’t matter if you’re just starting to learn code or if you’ve been doing it for a few years – sometimes you feel like you have no idea what you’re doing. This feeling can be made even worse by the wealth of information out there, making the right decision can get stressful. Life is full of those tough choices: Coke vs. Pepsi; Yankees vs. Red Sox; Python vs. Flask. You know, regular questions about soda, baseball, and Python frameworks that almost everyone faces.


Flask vs. Django: Which Python Framework is Better for Machine Learning Apps?

Python is insanely popular among machine learning enthusiasts these days. Hence, anyone developing a machine learning model normally turns to Python. The real challenge arises at the deployment stage because you can use many frameworks. Figuring out which Python framework to use may add to the confusion. This post discusses two popular machine learning frameworks, Flask and Django. We’ll also compare them side by side, so that you can make the right choice.


Flask vs. Django - Which One Outperforms the Other?

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.


Django and the N+1 Queries Problem

The N+1 Queries Problem is a perennial database performance issue. It affects many ORM’s and custom SQL code, and Django’s ORM is not immune either. In this post, we’ll examine what the N+1 Queries Problem looks like in Django, some tools for fixing it, and most importantly some tools for detecting it. Naturally, Scout is one of those tools, with its built-in N+1 Insights tool.