Introduction to programming using Python

Session 6-1

Matthieu Choplin

matthieu.choplin@city.ac.uk

http://moodle.city.ac.uk/

Objectives

• To use tuples as immutable lists
• To use sets for storing and fast accessing non-duplicated elements
• To understand the performance differences between sets and lists
• To store key/value pairs in a dictionary and access value using the keys

Tuples

• Tuples are like lists except they are immutable. Once they are created, their contents cannot be changed.
• If the contents of a list in your application do not change, you should use a tuple to prevent data from being modified accidentally. Furthermore, tuples are more efficient than lists.

Creating Tuples

• With brackets `(` and `)`

t1 = () # Create an empty tuple
t2 = (1, 3, 5)

• By converting a list (comprehension here) into a tuple

t3 = tuple([2 * x for x in range(1, 5)])

• By converting a string into a tuple

t4 = tuple("abac")

Tuples -- len(), max(), min(), [] index

• Tuples can be used like lists except they are immutable

tuple2 = tuple([7, 1, 2, 23, 4, 5]) # Create a tuple from a list
print(tuple2)

print("length is", len(tuple2)) # Use function len
print("max is", max(tuple2)) # Use max
print("min is", min(tuple2)) # Use min
print("sum is", sum(tuple2)) # Use sum

print("The first element is", tuple2[0]) # Use indexer

Tuples -- +, *, [:] slice, in

tuple1 = ("green", "red", "blue") # Create a tuple
tuple2 = tuple([7, 1, 2, 23, 4, 5]) # Create a tuple from a list
tuple3 = tuple1 + tuple2 # Combine 2 tuples
print(tuple3)
tuple3 = 2 * tuple1 # Multiply a tuple
print(tuple3)
print(tuple2[2 : 4]) # Slicing operator
print(tuple1[-1])
print(2 in tuple2) # in operator
for v in tuple1:
    print(v, end = " ")
print()

Tuples -- +, *, [:] slice, in

tuple1 = ("green", "red", "blue")
tuple2 = tuple([7, 1, 2, 23, 4, 5])
list1 = list(tuple2) # Obtain a list from a tuple
list1.sort()
tuple4 = tuple(list1)
tuple5 = tuple(list1)
print(tuple4)
print(tuple4 == tuple5) # Compare two tuples

Sets

• Sets are like lists to store a collection of items. Unlike lists, the elements in a set are:
• unique
• not placed in any particular order
• If your application does not care about the order of the elements, using a set to store elements is more efficient than using lists.
• The syntax for sets is braces {}.

Creating Sets

s1 = set() # Create an empty set
s2 = {1, 3, 5} # Create a set with three elements
s3 = set((1, 3, 5)) # Create a set from a tuple
# Create a set from a list (comprehension here)
s4 = set([x * 2 for x in range(1, 10)])
# Create a set from a string
s5 = set("abac") # s5 is {'a', 'b', 'c'}

Manipulating and Accessing Sets

s1 = {1, 2, 4}
s1.add(6)
print(s1) #  {1, 2, 4, 6}
s1.remove(4)
print(s1) #  {1, 2, 6}

Subset and Superset

s1 = {1, 2, 4}
s2 = {1, 4, 5, 2, 6}
s1.issubset(s2) # s1 is a subset of s2, print True
s2.issuperset(s1) # s2 is a superset of s1, print False

Equality Test

s1 = {1, 2, 4}
s2 = {1, 4, 2}
s1 == s1 #  True
s2 != s1 #  False

Set Operations (union, |)

s1 = {1, 2, 4}
s2 = {1, 3, 5}
s1.union(s2) #  {1, 2, 3, 4, 5}
s1 | s2 # equivalent of s1.union(s2)

Set Operations (intersection, &)

s1 = {1, 2, 4}
s2 = {1, 3, 5}
s1.intersection(s2) # {1}
s1 & s2 #  equivalent of s1.intersection(s2)

Set Operations (difference, -)

s1 = {1, 2, 4}
s2 = {1, 3, 5}
s1.difference(s2) # {2, 4}
s1 - s2 #  equivalent of s1.difference(s2)

Set Operations (symetric_difference, ^)

s1 = {1, 2, 4}
s2 = {1, 3, 5}
s1.symmetric_difference(s2) # {2, 3, 4, 5}
s1 ^ s2 #  equivalent of s1.symmetric_difference(s2)

Examples

Usage of a set SetDemo.py

Set and List performance compared:

• using the time library: SetListPerformanceTest.py

Dictionary

• Why dictionary?
• Suppose your program stores a million students and frequently searches for a student using the social security number. An efficient data structure for this task is the dictionary. A dictionary is a collection that stores the elements along with the keys. The keys are like an indexer.

Key/value pairs

Creating a dictionary

dictionary = {} # Create an empty dictionary
dictionary = {"john":40, "peter":45}

Equivalent to:

dictionary = dict()
dictionary =dict(john=40, peter=45)

Adding/Modifying Entries

To add an entry to a dictionary, use dictionary[key] = value

>>> dictionary["susan"] = 50
>>> print(dictionary)
{'john': 40, 'susan': 50, 'peter': 45}

Deleting Entries

To delete an entry from a dictionary, use del dictionary[key]

>>> del dictionary[“susan”]
>>> print(dictionary)
{'john': 40, 'peter': 45}

Looping Entries

for key in dictionary:
 print(key + ":" + str(dictionary[key]))

The len and in operators

len(dictionary) returns the number of the elements in the dictionary

>>> dictionary = {"john":40, "peter":45}
>>> "john" in dictionary
True
>>> "johnson" in dictionary
False
>>> len(dictionary)
2

The dictionary methods

Exercise: Guess the capital

• Write a program that prompts the user to enter a capital for a random country.
• Upon receiving the user input, the program reports whether the answer is correct.
• The countries and their capitals are stored in a dictionary in this file (import it to use).
• The user’s answer is not case sensitive.