Python offers a number of functions that process whole collections. They can be applied to sequences (lists or tuples), sets, mappings, and iterable results of generator expressions. We'll look at Python's collection-processing features from a functional programming viewpoint.
We'll start out by looking at iterables and some simple functions that work with iterables. We'll look at some design patterns to handle iterables and sequences with recursive functions as well as explicit for loops. We'll look at how we can apply a scalar function to a collection of data with a generator expression.
In this chapter, we'll show you examples of how to use the following functions with collections:
- any() and all()
- len(), sum(), and some higher-order statistical processing related to these functions
- zip() and some related techniques...
