Algorithms For Dummies

 

   

  PART 2 

 Understanding the Need to Sort and Search

Finding data using dictionaries

Creating and using a 

dictionary

 is much like working with a 

list

 except that you 

must now define a key and value pair. The great advantage of this data structure 

is that dictionaries can quickly provide access to specific data items using the key. 

There are limits to the kinds of keys you can use. Here are the special rules for 

creating a key:

 

»

The key must be unique. When you enter a duplicate key, the information 

found in the second entry wins; the first entry replaces the second.

 

»

The key must be immutable. This rule means that you can use strings, 

numbers, or tuples for the key. You can’t, however, use a 

list

 for a key.

The difference between mutable and immutable values is that immutable 

values can’t change. To change the value of a string, for example, Python 

actually creates a new string that contains the new value and gives the new 

string the same name as the old one. It then destroys the old string.

Python dictionaries are the software implementation of a data structure called a 

hash table, an array that maps keys to values. Chapter 7 explains hashes in detail 

and how using hashes can help dictionaries perform faster. You have no restric-

tions on the values you provide. A value can be any Python object, so you can use 

a dictionary to access an employee record or other complex data. The following 

example helps you understand how to use dictionaries better:

Colors = {"Sam": "Blue", "Amy": "Red", "Sarah": "Yellow"}

  

print(Colors["Sarah"])

print(Colors.keys())

  

for Item in Colors.keys():

   print("{0} likes the color {1}."

      .format(Item, Colors[Item]))

  

Colors["Sarah"] = "Purple"

Colors.update({"Harry": "Orange"})

del Colors["Sam"]

  

print(Colors)

  

Yellow

dict_keys(['Sarah', 'Amy', 'Sam'])

Sarah likes the color Yellow.

Amy likes the color Red.

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CHAPTER 6