Lecture 9

• what happens when procedure execution hits an unexpected condition?
• get an exception… to what was expected
  • trying to access beyond list limits

  test = [1,7,4]
  test[4]                     -> IndexError

  • trying to convert an inappropriate type

  int(test)                   -> TypeError

  • referencing a non-existing variable

  a                           -> NameError

  • mixing data types without coercion

  'a'/4                       -> TypeError

• already seen common error types:
  • SyntaxError: Python can’t parse program
  • NameError: local or global name not found
  • AttributeError: attribute reference fails
  • TypeError: operand does not have correct type
  • ValueError: operand type okay, but value is illegal
  • IOError: IO system reports malfunction (e.g. file not found)

• Python code can provide handlers for exceptions

try:
  a = int("burkay")
  b = int(5)
  print(a/b)
except:
  print("Bug in user input.")

## Bug in user input.

• exceptions raised by any statement in body of try are handled by the except statement and execution continues with the body of the except statement

• Code gets executed until exception occurs
  • after exception, except block starts executing

try:
  print(1)                   # (1) executes
  print("burkay")            # (2) executes
  print(int("genc"))         # (!) creates exception
  print(2)                   # (-) this is never executed
  print("genc")              # (-) this is never executed
except:
  print("Bug found!")        # (3) executes
  print("Please fix bug!")   # (4) executes

## 1
## burkay
## Bug found!
## Please fix bug!

• When exception occurs the rest of the try block is omitted
  • You shouldn’t simply put everything into a try block!

try:
  for i in range(-2, 3):
    print("For i=",i, " 1/i=", 1/i)
except:
  print("Bug found!")

## For i= -2  1/i= -0.5
## For i= -1  1/i= -1.0
## Bug found!

for i in range(-2, 3):
  try:
    print("For i=",i, " 1/i=", 1/i)
  except:
    print("Bug found!")

## For i= -2  1/i= -0.5
## For i= -1  1/i= -1.0
## Bug found!
## For i= 1  1/i= 1.0
## For i= 2  1/i= 0.5

• You can use clever coding to pinpoint bugs

try:
  for i in range(-5, 5):
    for j in range(-5, 5):
      k = 2 * i + j
      l = 10 / k
except:
  print("Bug at i=", i, "and j=", j)

## Bug at i= -2 and j= 4

• have separate except clauses to deal with a particular type of exception

try:
  a = int(input("Tell me one number: "))
  b = int(input("Tell me another number: "))
  print("a/b = ", a/b)
  print("a+b = ", a+b)
except ValueError:
  print("Could not convert to a number.")
except ZeroDivisionError:
  print("Can't divide by zero")
except:
  print("Something went very wrong.")

• else:
  • body of this is executed when execution of associated try body completes with no exceptions
• finally:
  • body of this is always executed after try, else and except clauses, even if they raised another error or executed a break, continue or return
  • useful for clean-up code that should be run no matter what else happened (e.g. close a file)

try:
  # First try to run the regular code
except:
  # If there is AN exception in try, then run this
else:
  # If there is NO exception in try, then run this
finally: 
  # No matter what, at the end, run this

try: 
  i = 3
  print(i / x)       # is x defined?
except:
  print("There is an error in the code.")
else:
  print("There is no error in the code.")
finally: 
  print("procedure ended.")

## There is an error in the code.
## procedure ended.

vs.

try:
  i, x = 3, 4
  print(i / x)       # x is defined
except:
  print("There is an error in the code.")
else:
  print("There is no error in the code.")
finally: 
  print("procedure ended.")

## 0.75
## There is no error in the code.
## procedure ended.

• what to do when encounter an error?
• fail silently:
  • substitute default values or just continue
  • bad idea! user gets no warning
• return an “error” value
  • what value to choose?
  • complicates code having to check for a special value
• stop execution, signal error condition
  • in Python: raise an exception raise Exception("descriptive string")

• write a function that takes two lists of numbers and returns a list of sum of items

def listSum(li1, li2):
  li3 = []
  for i in range(len(li1)):
    li3.append(li1[i] + li2[i])
  return li3
    
print(listSum([1,2,3], [4,5,6]))

## [5, 7, 9]

• can you see where this function can fail?

• write a function that takes two lists of numbers and returns a list of sum of items

def listSum(li1, li2):
  li3 = []
  for i in range(len(li1)):
    li3.append(li1[i] + li2[i])
  return li3
    
print(listSum([1,2,3,4,5], [1,2,3]))

IndexError: list index out of range

• Solution 1: use the shorter length

def listSum(li1, li2):
  li3 = []
  for i in range(min(len(li1), len(li2))):
    li3.append(li1[i] + li2[i])
  return li3
    
print(listSum([1,2,3,4,5], [1,2,3]))

## [2, 4, 6]

• Solution 2: use try/except to control output

def listSum(li1, li2):
  li3 = []
  for i in range(max(len(li1), len(li2))):
    try:
      li3.append(li1[i] + li2[i])
    except:
      if i >= len(li1):
        li3.append(li2[i])
      else:
        li3.append(li1[i])
  
  return li3
    
print(listSum([1,2,3,4,5], [1,2,3]))

## [2, 4, 6, 4, 5]

• Solution 3: raise an exception at the beginning

def listSum(li1, li2):
  if (len(li1) != len(li2)):
    raise Exception("Length of list1 is different than length of list2")
    
  li3 = []
  for i in range(len(li1)):
    li3.append(li1[i] + li2[i])
  return li3
    
print(listSum([1,2,3,4,5], [1,2,3]))

• Solutions 1 and 2 makes it possible to continue execution
  • But they may cause unpredictable results
• Solution 3 stops execution
  • But it avoids confusing results

• assume we are given a class list for a subject: each entry is a list of two parts
  • a list of first and last name for a student
  • a list of grades on assignments

  test_grades = [[['peter', 'parker'], [80.0, 70.0, 85.0]], 
                [['bruce', 'wayne'], [100.0, 80.0, 74.0]]]

• create a new class list, with name, grades, and an average

[[['peter', 'parker'], [80.0, 70.0, 85.0], 78.33333],
  [['bruce', 'wayne'], [100.0, 80.0, 74.0], 84.666667]]]

• example class_list object

[[['peter', 'parker'], [80.0, 70.0, 85.0]],
  [['bruce', 'wayne'], [100.0, 80.0, 74.0]]]

• possible solution

def get_stats(class_list):
  new_stats = []
  for elt in class_list:
    new_stats.append([elt[0], elt[1], avg(elt[1])])
  return new_stats

def avg(grades):
  return sum(grades)/len(grades)

• if one or more students don’t have any grades, we get an error

test_grades = [[['peter', 'parker'], [10.0, 5.0, 85.0]],
                [['bruce', 'wayne'], [10.0, 8.0, 74.0]],
                [['captain', 'america'], [8.0,10.0,96.0]],
                [['deadpool'], []]]

• get ZeroDivisionError: float division by zero
  • because of: return sum(grades)/len(grades)

• decide to notify that something went wrong with a message

def avg(grades):
  try:
    return sum(grades)/len(grades)
  except ZeroDivisionError:
    print('warning: no grades data')

• running on test data gives

get_stats(test_grades)

## warning: no grades data
## [[['peter', 'parker'], [10.0, 5.0, 85.0], 33.333333333333336], [['bruce', 'wayne'], [10.0, 8.0, 74.0], 30.666666666666668], [['captain', 'america'], [8.0, 10.0, 96.0], 38.0], [['deadpool'], [], None]]

• None, because avg() didn’t return anything in except block.

• decide that a student with no grades gets a zero

def avg(grades):
  try:
    return sum(grades)/len(grades)
  except ZeroDivisionError:
    print('warning: no grades data')
    return 0.0

• running on test data gives

get_stats(test_grades)

## warning: no grades data
## [[['peter', 'parker'], [10.0, 5.0, 85.0], 33.333333333333336], [['bruce', 'wayne'], [10.0, 8.0, 74.0], 30.666666666666668], [['captain', 'america'], [8.0, 10.0, 96.0], 38.0], [['deadpool'], [], 0.0]]

• after warning, we return 0.0
  • nicer solution

• want to be sure that assumptions on state of computation are as expected
• use an assert statement to raise an AssertionError exception if assumptions not met
• an example of good defensive programming

def avg(grades):
  assert len(grades) != 0, 'no grades data'
  return sum(grades)/len(grades)

• raises an AssertionError if it is given an empty list for grades
  • otherwise runs ok

## AssertionError: no grades data

• assertions don’t allow a programmer to control response to unexpected conditions
• ensure that execution halts whenever an expected condition is not met
• typically used to check inputs to functions, but can be used anywhere
• can be used to check outputs of a function to avoid propagating bad values
• can make it easier to locate a source of a bug

• goal is to spot bugs as soon as introduced and make clear where they happened
• use as a supplement to testing
• raise exceptions if users supplies bad data input
• use assertions to
  • check types of arguments or values
  • check that invariants on data structures are met
  • check constraints on return values
  • check for violations of constraints on procedure (e.g. no duplicates in a list)

These slides are a direct adaptation of the slides used for MIT 6.0001 course present (as of February 2020) on MIT OCW web site.

Original work by:

Ana Bell, Eric Grimson, and John Guttag. 6.0001 Introduction to Computer Science and Programming in Python. Fall 2016. Massachusetts Institute of Technology: MIT OpenCourseWare. License: Creative Commons BY-NC-SA.

Adapted by and for:

Asst. Prof. Dr. Burkay Genç. MUH101 Introduction to Programming, Spring 2020. Hacettepe University, Computer Engineering Department.