CMU 15-112: Fundamentals of Programming and Computer Science
Class Notes: Dictionaries

• Create and access dictionaries and their keys and values
• Recognize the difference between indexing in lists and using keys in dictionaries.
• Understand why dictionaries are efficient

1. Quick Example
2. Creating Dictionaries
3. Using Dictionaries
4. Properties of Dictionaries
   1. Dictionaries Map Keys to Values
   2. Keys are Sets
   3. Values are Unrestricted
   4. Dictionaries are Very Efficient
5. Check 7.3
6. Some Worked Examples Using Dictionaries

1. Quick Example
   # A dictionary is a data structure that maps keys to values in the same way # that a list maps indexes to values. However, keys can be any immutable value! stateMap = { 'pittsburgh':'PA', 'chicago':'IL', 'seattle':'WA', 'boston':'MA' } city = input("Enter a city name --> ").lower() if (city in stateMap): print(city.title(), "is in", stateMap[city]) else: print("Sorry, never heard of it.")
   
   Another Example:
   counts = dict() while True: n = int(input("Enter an integer (0 to end) --> ")) if (n == 0): break if (n in counts): counts[n] += 1 else: counts[n] = 1 print("I have seen", n, "a total of", counts[n], "time(s)") print("Done, counts:", counts)


2. Creating Dictionaries
   • Create an empty dictionary
     d = dict() print(d) # prints {} # We can also use empty braces d = { } print(d) # prints {}
   
   
   • Create a dictionary from a list of (key, value) pairs
     pairs = [("cow", 5), ("dog", 98), ("cat", 1)] d = dict(pairs) print(d) # unpredictable order!
   
   
   • Statically-allocate a dictionary
     d = { "cow":5, "dog":98, "cat":1 } print(d) # ditto!


3. Using Dictionaries
   # We can interact with dictionaries in a similar way to lists/sets d = { "a" : 1, "b" : 2, "c" : 3 } print(len(d)) # prints 3, the number of key-value pairs print("a" in d) # prints True print(2 in d) # prints False - we check the keys, not the values print(2 not in d) # prints True print("a" not in d) # prints False print(d["a"]) # finds the value associated with the given key. Crashes if the key is not in d print(d.get("z", 42)) # finds the value of the key if the key is in the dictionary, # or returns the second (default) value if the key is not in d d["e"] = "wow" # adds a new key-value pair to the dictionary, or updates the value of a current key del d["e"] # removes the key-value pair specified from the dictionary. Crashes if the key is not in d for key in d: print(key, d[key]) # we can iterate over the keys, then print out the keys or corresponding values


4. Properties of Dictionaries
   1. Dictionaries Map Keys to Values
      
      ages = dict() key = "fred" value = 38 ages[key] = value # "fred" is the key, 38 is the value print(ages[key])
   
   
   2. Keys are Sets
      
      • Keys are unordered
        d = dict() d[2] = 100 d[4] = 200 d[8] = 300 print(d) # unpredictable order
      
      
      • Keys are unique
        d = dict() d[2] = 100 d[2] = 200 d[2] = 400 print(d) # { 2:400 }
      
      
      • Keys must be immutable
        d = dict() a = [1] # lists are mutable, so... d[a] = 42 # Error: unhashable type: 'list'
   
   
   3. Values are Unrestricted
      
      # values may be mutable d = dict() a = [1,2] d["fred"] = a print(d["fred"]) a += [3] print(d["fred"]) # sees change in a! # but keys may not be mutable d[a] = 42 # TypeError: unhashable type: 'list'
   
   
   4. Dictionaries are Very Efficient
      As mentioned above, a dictionary's keys are stored as a set. This means that finding where a key is stored takes constant time. This lets us look up a dictionary's value based on a key in constant time too!
   
   
5. Check 7.3


6. Some Worked Examples Using Dictionaries
   We'll go over these in class.
   
   • mostFrequent(L)
   • isAnagram(s1, s2)