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Q1. What buit-in Python data type is commonly used to represent a queue?

  • A. dictionary
  • B. set
  • C. None. You can only build a stack from scratch.
  • D. list

Q2. How does defaultdict work?

  • A. defaultdict will automatically create a dictionary for you that has keys which are the integers 0-10.
  • B. defaultdict forces a dictionary to only accept keys that are of the types specified when you created the defaultdict (such as string or integers).
  • C. If you try to access a key in a dictionary that doesn't exist, defaultdict will create a new key for you instead of throwing a KeyError.
  • D. defaultdict stores a copy of a dictionary in memory that you can default to if the original gets unintentionally modified.

Q3. What is an abstract class?

  • A. An abstract class is the name for any class from which you can instantiate an object.
  • B. Abstract classes must be redefined any time an object is instantiated from them.
  • C. Abstract classes must inherit from concrete classes.
  • D. An abstract class exists only so that other "concrete" classes can inherit from the abstract class.

Q4. What is key difference between a set and a list?

  • A. A set is an ordered collection unique items. A list is an unordered collection of non-unique items.
  • B. Elements can be retrieved from a list but they cannot be retrieved from a set.
  • C. A set is an ordered collection of non-unique items. A list is an unordered collection of unique items.
  • D. A set is an unordered collection unique items. A list is an ordered collection of non-unique items.

Q5. Given the following three list, how would you create a new list that matches the desired output printed below?

fruits = ['Apples', 'Oranges', 'Bananas']
quantities = [5, 3, 4]
prices = [1.50, 2.25, 0.89]

# Desired output
[('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)]
  • A.
output = []

fruit_tuple_0 = (first[0], quantities[0], price[0])
output.append(fruit_tuple)

fruit_tuple_1 = (first[1], quantities[1], price[1])
output.append(fruit_tuple)

fruit_tuple_2 = (first[2], quantities[2], price[2])
output.append(fruit_tuple)

return output
  • B.
i = 0
output = []
for fruit in fruits:
    temp_qty = quantities[i]
    temp_price = prices[i]
    output.append((fruit, temp_qty, temp_price))
    i += 1
return output
  • C.
groceries = zip(fruits, quantities, prices)
return groceries

>>> [
('Apples', 5, 1.50),
('Oranges', 3, 2.25),
('Bananas', 4, 0.89)
]
  • D.
i = 0
output = []
for fruit in fruits:
    for qty in quantities:
        for price in prices:
            output.append((fruit, qty, price))
    i += 1
return output

Q6. Correct representation of doctest for function in Python

  • A.
def sum(a, b):
    # a = 1
    # b = 2
    # sum(a, b) = 3

    return a + b
  • B.
def sum(a, b):
    """
    a = 1
    b = 2
    sum(a, b) = 3
    """

    return a + b
  • C.
def sum(a, b):
    """
    >>> a = 1
    >>> b = 2
    >>> sum(a, b)
    3
    """

    return a + b
  • D.
def sum(a, b):
    '''
    a = 1
    b = 2
    sum(a, b) = 3
    '''
    return a + b

Q7. Review the code below. What is the correct syntax for changing the price to 1.5?

fruit_info = {
'fruit': 'apple',
'count': 2,
'price': 3.5
}
  • A. fruit_info ['price'] = 1.5
  • B. my_list [3.5] = 1.5
  • C. 1.5 = fruit_info ['price]
  • D. my_list['price'] == 1.5

Q8. What is the correct syntax for defining an __init__() method that takes no parameters?

  • A.
class __init__(self):
    pass
  • B.
def __init__():
    pass
  • C.
class __init__():
    pass
  • D.
def __init__(self):
    pass

Q9. Why would you use a decorator?

  • A. A decorator is similar to a class and should be used if you are doing functional programming instead of object oriented programming.
  • B. A decoratore is a visual indicator to someone reading your code that a portion of your code is critical and should not be changed.
  • C. You use the decorator to alter the functionality of a function without the without having to modify the functions code.
  • D. An import statement is preceded by a decorator, pyhton knows to import the most recent version of whatever package or library is being imported.

Q10. What is the runtime complexity of searching for an item in a binary search tree?

  • A. The runtime for searching in a binary search tree is O(1) because each node acts as a key, similar to a dictionary.
  • B. The runtime for searching in a binary search tree is O(n!) because every node must be compared to every other node.
  • C. The runtime for searching in a binary search tree is generally O(h), where h is the height of the tree.
  • D. The runtime for searching in a binary search tree is O(n) because every node in the tree must be visited.