Python has a very easy and flexible set of built-in containers. As a Python developer, there is little you can't achieve with a dict or a list. The convenience of Python dictionaries and lists is such that developers often forget that those have limits. Like any data structure, they are optimized and designed for specific use cases and might be inefficient in some conditions, or even unable to handle them.
Ever tried to put a key in a dictionary twice? Well you can't, because Python dictionaries are designed as hash tables with unique keys, but the MultiDict recipe will show you how to do that. Ever tried to grab the lowest/highest values out of a list without traversing it whole? The list itself can't, but in the Prioritized entries recipe, we will see how to achieve that.
The limits of standard Python containers are well known to Python experts. For that reason, the standard library has grown over the years to overcome those limits, and frequently there are patterns so common that their name is widely recognized, even though they are not formally defined.
