python

In Post #65, we learned how to access dictionary values using square brackets, like my_dict[‘key’]. We also discovered a dangerous side effect: if the key doesn’t exist, our program crashes with a KeyError. This is not ideal for robust applications that need to handle optional or missing data. In this post, we’ll learn the best … Read more

In Post #64, we were introduced to Python’s dictionary, a powerful data structure for storing data as key-value pairs. Now that we know how to define a dictionary, it’s time to learn how to interact with it. This post covers the three fundamental operations you’ll perform on dictionaries every day: accessing a value using its … Read more

So far in Part 3, we’ve explored lists and tuples. Both are powerful sequence types that store collections of items in a specific order, which we access using integer indexes like 0, 1, and 2 (a concept we learned in Post #47). But what if we don’t want to access data by its numerical position? … Read more

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