Have you ever run into unexpected bugs when checking conditions in your Python code? If so, you might have stumbled upon a subtle, yet common mistake: using a method reference without parentheses when evaluating conditions.
When working with data in Python, we often need to count occurrences of items in a list or a string. While we could write our own code to do this, Python comes with the collections module that provides a convenient and efficient way to handle this task: the Counter class.
Creating DTOs with NamedTuple was a nice way to create read-only structures to pass between functions. But not always is a read-only structure the right tool for the job. Let us look how we can create changeable structures like classes with ease.
Last week we worked with the main methods of the re module. However, when we need to be specific about the text parts we search, we miss a lot of the flexibility we can get from regular expressions. In this post we look at metacharacters and how they make regular expressions so powerful.
I waited a long time to explore regular expressions, then they tend to get complicated in no time. But for some problems there is simply no way around. Let us explore the basics and how we can use them in our Python code.
If our application uses recursion, we may call the same function with the same values many times. When that function is side-effect free, we can save a lot of time by caching the result. And even better, in Python we can do that without much effort.
When we work with dictionaries that contains lists, we need to make sure that the list exists before we can add items. Or when we use a dictionary for counters, we must make sure that we have a value before we can increment it. While this can be done by hand, there is a much more elegant way in Python.
I had to do a lot of work with lists and dictionaries to solve the puzzles for Advent of Code. Here is my little cheat sheet for these two basic data structures from which you could also benefit.
Internally Python uses classes and therefore types everywhere. However, when we declare our methods, we omit the types and end up with limited functionality for our code editors. In this post we look at type hints and how they can improve our experience to write code.
You may run into code examples where the parameters are prefixed with a star or a double star. This little feature of Python comes in handy when we need a bit more flexibility for our methods. Let us explore how that works.