Iterables, Iterators, and Generators

Iteration is fundamental to data processing. And when scanning datasets that don't fit in memory, we need a way to fetch the items lazily, that is, one at a time and on demand. This is what the Iterator pattern is about. 

Every generator is an iterator: generators fully implement the iterator interface. But an iterator retrieves items from a collection, while a generator can produce items "out of thin air".

Every collection in Python is iterable, and iterators are used internally to support:

• for loop
• Collection types construction and extension
• Looping over text files line by line
• List, dict, and set comprehensions
• Tuple unpacking
• Unpacking actual parameters with * in function calls

We'll get started studying how the iter(...) function makes sequence iterable.

 

1. Sentence Take #1: A Sequence of Words.

 

 

 

 

 

 

 

 

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