Learning Python

Why Use Built-in Types?

If you’ve used lower-level languages such as C or C++, you know that much of your work centers on implementing objects—what some folks call data structures—to represent the components in your application’s domain. You need to lay out memory structures, manage memory allocation, implement search and access routines, and so on. These chores are about as tedious (and error prone) as they sound, and usually distract from your programs’ real goals.

In typical Python programs, most of this grunt work goes away. Because Python provides powerful object types as an intrinsic part of the language, there’s no need to code object implementations before you start solving problems. In fact, unless you have a need for special processing that built-in types don’t provide, you’re almost always better off using a built-in object instead of implementing your own. Here are some reasons why:

Built-in objects make simple programs easy to write

For simple tasks, built-in types are often all you need to represent the structure of problem domains. Because we get things such as collections (lists) and search tables (dictionaries) for free, you can use them immediately. You can get a lot of work done with just Python’s built-in object types alone.

Python provides objects and supports extensions

In some ways, Python borrows both from languages that rely on built-in tools (e.g., LISP), and languages that rely on the programmer to provide tool implementations or frameworks of their own (e.g., ...