Beginning Python - From Novice to Professional

116 CHAPTER 6 ■ ABSTRACTION
storage = {}
storage['first'] = {}
storage['middle'] = {}
storage['last'] = {}
The data structure storage is a dictionary with three keys: 'first', 'middle', and 'last'.
Under each of these keys, you store another dictionary. In these subdictionaries, you’ll use
names (first, middle, or last) as keys, and insert lists of people as values. For example, to add me
to this structure, you could do the following:
>>> me = 'Magnus Lie Hetland'
>>> storage['first']['Magnus'] = [me]
>>> storage['middle']['Lie'] = [me]
>>> storage['last']['Hetland'] = [me]
Under each key, you store a list of people. In this case, the lists contain only me.
Now, if you want a list of all the people registered who have the middle name Lie, you
could do the following:
>>> storage['middle']['Lie']
['Magnus Lie Hetland']
As you can see, adding people to this structure is a bit tedious, especially when you get
more people with the same first, middle, or last names, because then you have to extend the list
that is already stored under that name. Let’s add my sister, for example, and let’s assume you
don’t know what is already stored in the database:
>>> my_sister = 'Anne Lie Hetland'
>>> storage['first'].setdefault('Anne', []).append(my_sister)
>>> storage['middle'].setdefault('Lie', []).append(my_sister)
>>> storage['last'].setdefault('Hetland', []).append(my_sister)
>>> storage['first']['Anne']
['Anne Lie Hetland']
>>> storage['middle']['Lie']
['Magnus Lie Hetland', 'Anne Lie Hetland']
Imagine writing a large program filled with updates like this—it would quickly become
quite unwieldy.
The point of abstraction is to hide all the gory details of the updates, and you can do that
with functions. Let’s first make a function to initialize a data structure:
def init(data):
data['first'] = {}
data['middle'] = {}
data['last'] = {}
In the preceding code, I’ve simply moved the initialization statements inside a function.
You can use it like this: