python

In Post #62, we established a clear rule of thumb: use a list for collections that need to change and a tuple for collections that should remain fixed. The primary reason we discussed was intent—communicating to other developers (and your future self) that a piece of data isn’t meant to be modified. But what are … Read more

We’ve now been introduced to two of Python’s sequence types: the mutable list (Post #46) and the immutable tuple (Post #58). They seem very similar—both are ordered collections that can hold various data types. This often leads to a common question for new programmers: which one should I use, and when? This post is a … Read more

In Post #60, we learned about the art of sequence unpacking, a “Pythonic” way to assign items from a tuple or list to multiple variables at once. This elegant feature is more than just a convenient trick—it’s the key to one of the most powerful capabilities of Python functions. In this post, we will explore … Read more

In Post #58 and Post #59, we learned about tuples as immutable, ordered collections. While their unchangeable nature is useful for data integrity, tuples are also central to one of Python’s most elegant and convenient features. In this post, we will explore sequence unpacking (often called tuple unpacking). This is a “Pythonic” shortcut that allows … Read more

In Post #58, we learned that tuples are created using parentheses, like my_tuple = (1, 2, 3). This seems straightforward, but there is a subtle syntax rule that catches nearly every new Python programmer by surprise, especially when trying to create a tuple with only one item. In this post, we’ll look at this specific … Read more

Throughout Part 3 so far, we’ve focused on the list, Python’s workhorse for storing collections of data. We’ve emphasized that lists are mutable, meaning they are designed to be changed (a concept we covered in Post #49). But what if you have a collection of items that you want to ensure never changes after it’s … Read more

It’s time for another project! We’ve spent the last several posts exploring Python’s most versatile data structure, the list. We’ve learned how to create them, add to them, remove from them, and loop through them like a pro. Now, we will combine all of that knowledge to build a useful, interactive program: a command-line to-do … Read more

In Post #34, we learned that the for loop is the best way to iterate over the items in a list. The simple for fruit in fruits: syntax is clean and effective for when you only care about the items themselves. But what happens when you need to know the position of an item as … Read more

In our previous post on copying lists (Post #54), we briefly mentioned the idea of “nested lists.” This simple concept—putting lists inside other lists—unlocks the ability to represent complex, grid-like data structures. In this post, we will explore 2D lists (also known as matrices). You’ll learn how to structure them to represent tabular data and … Read more

This is one of the most important conceptual posts in this entire section. Understanding the difference between assigning a list and copying a list will save you from hours of debugging mysterious and frustrating bugs. Because lists are mutable (a concept we covered in Post #49), the way we duplicate them is critically important. A … Read more