Mapping Operations

When written as literals, dictionaries are coded in curly braces and consist of a series of “key: value” pairs. Dictionaries are useful anytime we need to associate a set of values with keys—to describe the properties of something, for instance. As an example, consider the following three-item dictionary (with keys “food,” “quantity,” and “color”):

>>> D = {'food': 'Spam', 'quantity': 4, 'color': 'pink'}

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We can index this dictionary by key to fetch and change the keys’ associated values. The dictionary index operation uses the same syntax as that used for sequences, but the item in the square brackets is a key, not a relative position:

>>> D['food']              # Fetch value of key 'food'
'Spam'

>>> D['quantity'] += 1     # Add 1 to 'quantity' value
>>> D
{'food': 'Spam', 'color': 'pink', 'quantity': 5}

Although the curly-braces literal form does see use, it is perhaps more common to see dictionaries built up in different ways. The following code, for example, starts with an empty dictionary and fills it out one key at a time. Unlike out-of-bounds assignments in lists, which are forbidden, assignments to new dictionary keys create those keys:

>>> D = {}
>>> D['name'] = 'Bob'      # Create keys by assignment
>>> D['job']  = 'dev'
>>> D['age']  = 40

>>> D
{'age': 40, 'job': 'dev', 'name': 'Bob'}

>>> print(D['name'])
Bob

Here, we’re effectively using dictionary keys as field names in a record that describes someone. In other applications, dictionaries can also be used to replace searching operations—indexing a dictionary by key is often the fastest way to code a search in Python. As we'll learn later, dictionaries may also be made by passing keyword arguments to the type name: dict(name='Bob', job='dev', age=40) makes the same dictionary.