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I’ve been working with Python for many years, and if there is one thing I’ve learned, it’s that you will almost always deal with JSON. Whether you are pulling data from a retail API or processing financial reports for a New York-based firm, JSON is the standard. Working with JSON arrays can feel a bit … Read more >>
Managing object attributes in Python is usually simple. You just use the dot notation and call it a day. But there are times when I don’t know the name of the attribute until the code is actually running. This often happens when I’m dealing with large datasets or building flexible APIs. In my years of … Read more >>
In my years of developing enterprise-level Python applications, I’ve often found myself needing to add repetitive logic across multiple classes. Whether it was for logging API calls or validating data schemas, manually editing every class felt like a waste of time. That is where class decorators come into play. They are a powerful way to … Read more >>
In my years of developing enterprise software, I have often seen developers get confused when they realize type() does more than just identify an object. It took me a few deep-dive sessions into Python’s internals to realize that type is actually the “class of all classes”, the ultimate metaclass. In this tutorial, I will show … Read more >>
In my years of developing enterprise-level Python applications, I have often found myself needing more control over how classes are created. Standard inheritance is great, but sometimes you need to intercept the very moment a class is defined to enforce rules or inject logic. This is where metaclasses come in. They are essentially the “classes … Read more >>
I’ve spent countless hours writing boilerplate for data-holding classes. I remember the days of manually writing __init__, __repr__, and __eq__ methods for every single entity in a project. It was tedious and often led to small, annoying bugs that were hard to track down during late-night deployments. Then came Python 3.7 and the introduction of … Read more >>
Over my decade of developing Python applications, I’ve often found myself needing to group related data points. Whether I’m handling geographic coordinates for a logistics app in Chicago or processing financial records in New York, tuples are my go-to choice. One question I frequently get from junior developers I mentor is how to efficiently pass … Read more >>
I’ve spent years building applications in Python, and if there is one thing I’ve learned, it’s that the simplest syntax can sometimes be the most deceptive. The other day, I was mentoring a junior developer who was trying to pass a single US State code into a database function as a tuple. He wrote state … Read more >>
In my decade of building Python applications, I’ve found that few symbols are as versatile as the percent sign (%). While most beginners think it’s just for calculating remainders, it actually wears many hats in a professional codebase. I remember early in my career when I had to format complex financial reports for a New … Read more >>
I have spent over a decade wrangling messy data in Python. One thing I’ve learned is that the standard split() method is great, but it often falls short. When you are dealing with real-world strings that have multiple different delimiters, you need something more powerful. That is where the Python split regex (Regular Expressions) comes … Read more >>
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