Basic Dictionary Operations

In normal operation, you create dictionaries with literals and store and access items by key with indexing:

% python
>>> D = {'spam': 2, 'ham': 1, 'eggs': 3}      # Make a dictionary
>>> D['spam']                                 # Fetch a value by key
2
>>> D                                         # Order is scrambled
{'eggs': 3, 'ham': 1, 'spam': 2}

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Here, the dictionary is assigned to the variable D; the value of the key 'spam' is the integer 2, and so on. We use the same square bracket syntax to index dictionaries by key as we did to index lists by offset, but here it means access by key, not by position.

Notice the end of this example: the left-to-right order of keys in a dictionary will almost always be different from what you originally typed. This is on purpose: to implement fast key lookup (a.k.a. hashing), keys need to be reordered in memory. That’s why operations that assume a fixed left-to-right order (e.g., slicing, concatenation) do not apply to dictionaries; you can fetch values only by key, not by position.

The built-in len function works on dictionaries, too; it returns the number of items stored in the dictionary or, equivalently, the length of its keys list. The dictionary in membership operator allows you to test for key existence, and the keys method returns all the keys in the dictionary. The latter of these can be useful for processing dictionaries sequentially, but you shouldn’t depend on the order of the keys list. Because the keys result can be used as a normal list, however, it can always be sorted if order matters (more on sorting and dictionaries later):

>>> len(D)                                    # Number of entries in dictionary
3
>>> 'ham' in D                                # Key membership test alternative
True
>>> list(D.keys())                            # Create a new list of my keys
['eggs', 'ham', 'spam']

Notice the second expression in this listing. As mentioned earlier, the in membership test used for strings and lists also works on dictionaries—it checks whether a key is stored in the dictionary. Technically, this works because dictionaries define iterators that step through their keys lists. Other types provide iterators that reflect their common uses; files, for example, have iterators that read line by line. We’ll discuss iterators in Chapters 14 and 20.

Also note the syntax of the last example in this listing. We have to enclose it in a list call in Python 3.0 for similar reasons—keys in 3.0 returns an iterator, instead of a physical list. The list call forces it to produce all its values at once so we can print them. In 2.6, keys builds and returns an actual list, so the list call isn’t needed to display results. More on this later in this chapter.

Note

The order of keys in a dictionary is arbitrary and can change from release to release, so don’t be alarmed if your dictionaries print in a different order than shown here. In fact, the order has changed for me too—I’m running all these examples with Python 3.0, but their keys had a different order in an earlier edition when displayed. You shouldn’t depend on dictionary key ordering, in either programs or books!