Lecture 6, Thu 01/25

Assert Statements, Lists, Dictionaries

Recorded Lecture: 1_25_24

assert Statements

• When building anything, testing is an important part of a development process
  • Pilots test their planes before using them commercially (hopefully!)
• Software is complex. There’s a lot of code to do very complex things
  • Many engineers may be working on the same code to fix things, add features, improve performance, …
• It’s up to the programmers to ensure their code is working
  • There isn’t an “autograder” to make sure functionality is working as it should
• A common way to ensure software is working properly is by writing checks to see if units of functionality are working according to the specification
  • zyBooks does this when you submit your code
• Python gives us the assert keyword to help us test the code we write
  • assert statements evaluate a boolean expression
    • If the expression evaluates to True, then the assert statement passes and code continues executing normally
    • If the expression evaluates to False, then an error is raised and program execution stops
• Example:

print("Start")
assert 5 == 5
assert True
assert 6 <= 8
print("asserts pass so far!")
assert 4 == 5 # assert statement doesn't pass
print("4 == 5 doesn't pass") # doesn't print

• There are more formal ways to test our code, but assert statements are good “sanity checks” to make sure something isn’t wrong
• It’s common to use assert statements to test whether or not our function returns a correct value according to a specification
• Examples using assert to test a function:

def isEven(value):
	''' Function that returns True if value is even,
		returns False otherwise '''
	if value // 2 == 0: # Error! Should use %
		return True
	else:
		return False

print("Checking isEven functionality")
assert isEven(3) == False # passes
print("passed isEven(3)")
assert isEven(2) == True # Fails, but should pass since 2 is even
print("passed isEven(2)")

• We can use assert statements to help us fix our problem

def isEven(value):
	''' Function that returns True if value is even,
		returns False otherwise '''
	if value % 2 == 0: # Correct
		return True
	else:
		return False

print("Checking isEven functionality")
assert isEven(3) == False # pass
print("passed isEven(3)")
assert isEven(2) == True # pass
print("passed isEven(2)")

Containers

• Our programs may want to have a variable refer to a collection of values, rather than just a single value
• Python provides several ways to store multiple values in a single object
• We’ve already seen some form of containers with strings
  • Strings are basically storing a container of characters
• Python’s len() function allows us to obtain the number of elements in a collection

Lists

• A list is a collection of multiple values (similar to how a str is a collection of characters)
  • Note: Python Lists can consist of heterogenous (different) types
  • Lists can contain duplicate values
  • The bracket notation [] is used to represent a list type
  • We can extract specific elements in lists using an index value based on its position in the list
    • Note that the first value is referred to with index [0] (not 1)
• Example:

evenNumbers = [2, "4", 6, "8", 6]
print(evenNumbers)
print(type(evenNumbers))
print(len(evenNumbers)) # 5
print(evenNumbers[2])  # gets t
print(evenNumbers[-1]) #gets the last element
evenNumbers[1] = "four" # replace index 1 with "four"
print(evenNumbers)

• Note that Python Lists are considered mutable types.
  • We can directly change a value in the List once it has been created
• Immutable types cannot directly change elements once it has been created

Dictionaries

• A dictionary is a collection where we want a unique key mapping to another (non-unique) value
  • Works where a KEY (unique / immutable) maps to a VALUE (non-unique / immutable or mutable)
• Useful to make an association of a KEY : VALUE pair
• Dictionaries themselves are mutable (we can update a KEY : VALUE pair in the dictionary)
• Some examples could include Perm Numbers -> Grades, Zip Code -> City, Course Number -> Instructor, …
• We can extract a KEY’s VALUE in dictionaries using the KEY
• General Syntax (notice curly braces are used instead of brackets), and notice the KEY:VALUE pairs are combined with :

{key1:value1, key2:value2, ... , keyN:valueN}

• Example:

D = {} # Empty dictionary. Notice the curly braces instead of brackets ([])

# Dictionary (mapping unique PERM numbers to Grades)
D = { 1234567:'A+', 7654321:'A-', 5555555:'B+' }
print(type(D))
print(len(D)) # 3
print(D[7654321]) # returns value 'A+'
D[5555555] = 'A-' # updates KEY with new VALUE
print(D)
D[5463278] = 'A' # creates a new KEY : VALUE pair
print(D)
del D[1234567] # removes 1234567 KEY : VALUE pair
print(D)

The in Operator

• Circling back to boolean operators, the in operator can be useful to detect if an element exists in the container
  • Returns True if the element is in the container, returns False if not
• For strings, we can check if a character (or substring) exists in a string
• For lists, we can check if an element exists in the list
• For dictionaries, we can check if an element is a key in the dictionary
• Examples:

evenNumbers = [2, "4", 6, "8", 6]
D = { 1234567:'A+', 7654321:'A-', 5555555:'B+' }
s = "CMPSCW8"

print("4" in evenNumbers) #True
print(4 in evenNumbers) #False
print(7654321 in D) #True
print(9999999 in D) #False
print("SCW" in s) #True
print("CS" in s) #False
print(3 in [1, 2, 3]) # True
print(5 in [1, 2, 3]) # False