python

Up to this point, our custom functions have performed actions—they’ve printed banners or messages to the console. They do things, but they don’t give us anything back that we can store and use later in our program. What if we want a function to perform a calculation and hand us the result? How do we … Read more

This post covers what is arguably one of the most famous and confusing “gotchas” in the Python language. In Post #89, we learned how to use default parameter values, which is a fantastic feature for making functions more flexible. However, using a mutable type (like a list or a dictionary) as a default can lead … Read more

In Post #87 and Post #88, we learned how to pass information to our functions using positional and keyword arguments. In all of our examples so far, every parameter we defined was required. If we defined a function with two parameters, we had to call it with two arguments, or the program would crash. But … Read more

In Post #87, we learned about positional arguments and saw their biggest weakness: they depend entirely on the correct order. If you have a function with several parameters, it’s easy to forget their sequence and introduce a bug, like in our example where we accidentally called describe_pet(‘Harry’, ‘hamster’) and got a nonsensical result. To solve … Read more

In Post #86, we learned the crucial difference between parameters (the placeholders in a function definition) and arguments (the actual values we pass in a function call). Now, we need to understand how Python knows which argument to assign to which parameter. The simplest and most common way Python does this is by position. In … Read more

In our previous posts, we created simple functions that performed the same task every time they were called. Our display_welcome_banner() function from Post #84 was useful, but it wasn’t very flexible—it couldn’t greet different users by name. To make functions truly powerful and reusable, we need a way to pass information into them. In this … Read more

In Post #84, we learned how to define a function with def and then use it by “calling” it. We established that defining a function is like writing a recipe, and calling it is like cooking the dish. This distinction is one of the most important concepts when working with functions. In this post, we’re … Read more

In Post #83, we learned about the “Don’t Repeat Yourself” (DRY) principle and why avoiding repeated code is so important for writing clean and maintainable programs. We established that the solution is to package our reusable logic into a block called a function. Now it’s time to learn how to do that. In this post, … Read more

Welcome to Part 4 of our series: Functions and Modularity! Until now, all of our programs have been written as single scripts that run from top to bottom. As our programs grow in complexity, this approach becomes difficult to manage. The key to writing clean, professional, and maintainable code is organization. In this post, before … Read more

Welcome to the final post of Part 3! Over this section, we have taken a deep dive into Python’s four essential built-in data structures, the containers that hold and organize all of our program’s data. To wrap up, we will first briefly recap the unique role of each data structure. Then, we’ll build a final … Read more