Learning Python, 6th Edition

Chapter 6. The Dynamic Typing Interlude

In the prior chapter, we began exploring Python’s core object types in depth by studying Python numbers and their operations. We’ll resume our object type tour in the next chapter, but before we move on, it’s important that you get a handle on what may be the most fundamental idea in Python programming and is certainly the basis of much of both the conciseness and flexibility of the Python language: dynamic typing, and the polymorphism it implies.

As you’ll see here and throughout this book, in Python, we do not need to declare the specific types of the objects our scripts use. In fact, most programs should not care about specific types—on purpose. By avoiding constraints this way, code naturally works in many contexts and often more than expected. Because dynamic typing is the root of this flexibility, and is also a potential stumbling block for newcomers, let’s take a brief side trip to explore the model here. At the end of the trip, we’ll also make a short stop at the paradox of type hinting, to learn why you should avoid it.

The Case of the Missing Declaration Statements

If you have a background in statically typed languages like C, C++, or Java, you might find yourself a bit perplexed at this point in the book. So far, we’ve been using variables without declaring their existence or their types, and it somehow works. When we type a = 3 in an interactive session or program file, for instance, how does Python know that a should stand ...