Combining map and reduce transformations

In the other recipes in this chapter, we've been looking at map, filter, and reduce operations. We've looked at each of these in isolation:

• The Applying transformations to a collection recipe shows the map() function

• The Picking a subset – three ways to filter recipe shows the filter() function

• The Summarizing a collection – how to reduce recipe shows the reduce() function

Many algorithms will involve combinations of functions. We'll often use mapping, filtering, and a reduction to produce a summary of available data. Additionally, we'll need to look at a profound limitation of working with iterators and generator functions. Namely this limitation:

Tip

An iterator can only produce values once.

If we create an iterator from a generator function and a collection data, the iterator will only produce the data one time. After that, it will appear to be an empty sequence.

Here's an example:

>>> typical_iterator = iter([0, 1, 2, 3, 4]) 
>>&gt...