Introduction to Dictionaries
The last standard type to add to our repertoire is the dictionary, the sole mapping type in Python. A dictionary is mutable and is another container type that can store any number of Python objects, including other container types. What makes dictionaries different from sequence type containers like lists and tuples is the way the data is stored and accessed.
Sequence types use numeric keys only (numbered sequentially as indexed offsets from the beginning of the sequence). Mapping types may use most other object types as keys, strings being the most common. Unlike sequence type keys, mapping keys are often, if not directly, associated with the data value that is stored. But because we are no longer using “sequentially-ordered” keys with mapping types, we are left with an unordered collection of data. As it turns out, this does not hinder our use because mapping types do not require a numeric value to index into a container to obtain the desired item. With a key, you are “mapped” directly to your value, hence the term “mapping type.” The most common data structure that maps keys with associated values are hash tables.
Sequence types use sequentially-ordered numeric keys as index offsets to store your data in an array format. The index number usually has nothing to do with the data value that is being stored. There should also be a way to store data based on another, associated value such as a string. We do this all the time in everyday living. You file people’s phone numbers in your address book based on last name, you add events to your calendar or appointment book based on date and time, etc. For each of these examples, an associated value to a data item was your key.
Hash tables are a data structure that does exactly what we described. They store each piece of data, called a value, based on an associated data item, called a key. Together, these are known as key-value pairs. The hash table algorithm takes your key, performs an operation on it, called a hash function, and based on the result of the calculation, chooses where in the data structure to store your value. Where any one particular value is stored depends on what its key is. Because of this randomness, there is no ordering of the values in the hash table. You have an unordered collection of data.
The only kind of ordering you can obtain is by key. You can request a dictionary’s keys, which is returned to you as a list. From there, you can call the list’s sort() method to order that data set. This is only one type of ordering you can perform on your keys. In any case, once you have determined that the set of keys is “sorted” to your satisfaction, their associated values may be retrieved from the dictionary. Hash tables generally provide good performance because lookups occur fairly quickly once you have a key. For a sequential access data structure, you must march down to the correct index location and then retrieve the value. Naturally, performance is based on the type of hash function used. Python dictionaries are implemented as resizeable hash tables. If you are familiar with Perl, then we can say that dictionaries are similar to Perl’s associative arrays or hashes.
We will now take a closer look at Python dictionaries. The syntax of a dictionary entry is key:value. Also, dictionary entries are enclosed in braces ( { } ).
