HackerRank Python Solution - Date and Time - Calendar Module

• The calendar module allows you to output calendars and provides additional useful functions for them.

• class calendar.TextCalendar([firstweekday])

• This class can be used to generate plain text calendars.

Sample Code:

HackerRank Python Solution - Collections Topic - Counter()

A counter is a container that stores elements as dictionary keys and their counts are stored as dictionary values.

Sample Code:

>>> from collections import Counter
>>> 
>>> myList = [1,1,2,3,4,5,3,2,3,4,2,1,2,3]
>>> print Counter(myList)
Counter({2: 4, 3: 4, 1: 3, 4: 2, 5: 1})
>>>
>>> print Counter(myList).items()
[(1, 3), (2, 4), (3, 4), (4, 2), (5, 1)]
>>> 
>>> print Counter(myList).keys()
[1, 2, 3, 4, 5]
>>> 
>>> print Counter(myList).values()
[3, 4, 4, 2, 1]

HackerRank Python Solution - Collections Topic - deque()

• A deque is a double-ended queue. It can be used to add or remove elements from both ends.

• Deques support thread-safe, memory-efficient appends, and pops from either side of the deque with approximately the same O(1) performance in either direction.

HackerRank Python Solution - Collections Topic - OrderedDict

An OrderedDict is a dictionary that remembers the order of the keys that were inserted first. If a new entry overwrites an existing entry, the original insertion position is left unchanged.

Example Code:

>>> from collections import OrderedDict
>>> 
>>> ordinary_dictionary = {}
>>> ordinary_dictionary['a'] = 1
>>> ordinary_dictionary['b'] = 2
>>> ordinary_dictionary['c'] = 3
>>> ordinary_dictionary['d'] = 4
>>> ordinary_dictionary['e'] = 5
>>> 
>>> print ordinary_dictionary
{'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4}
>>> 
>>> ordered_dictionary = OrderedDict()
>>> ordered_dictionary['a'] = 1
>>> ordered_dictionary['b'] = 2
>>> ordered_dictionary['c'] = 3
>>> ordered_dictionary['d'] = 4
>>> ordered_dictionary['e'] = 5
>>> 
>>> print ordered_dictionary
OrderedDict([('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)])

HackerRank Python Solution - Collections Topic - namedtuple()

• Basically, namedtuples are easy to create, lightweight object types.

• They turn tuples into convenient containers for simple tasks.

• With namedtuples, you don’t have to use integer indices for accessing members of a tuple.

Example:

Code 01:

>>> from collections import namedtuple
>>> Point = namedtuple('Point','x,y')
>>> pt1 = Point(1,2)
>>> pt2 = Point(3,4)
>>> dot_product = ( pt1.x * pt2.x ) +( pt1.y * pt2.y )
>>> print dot_product
11

HackerRank Python Solution - Collections Topic - DefaultDict

The defaultdict tool is a container in the collections class of Python. It's similar to the usual dictionary (dict) container, but the only difference is that a defaultdict will have a default value if that key has not been set yet. If you didn't use a defaultdict you'd have to check to see if that key exists, and if it doesn't, set it to what you want.

For example:

 

from collections import defaultdict
d = defaultdict(list)
d['python'].append("awesome")
d['something-else'].append("not relevant")
d['python'].append("language")
for i in d.items():
    print i

HackerRank Python Solution - Itertools Topic - Maximize it!

• You are given a function f(X) = X². You are also given K lists. The i_th list consists of N_i elements.

• You have to pick one element from each list so that the value from the equation below is maximized:

• S = (f(X₁) + f(X₂) +....+ f(X_k)) % M

• X_i denotes the element picked from the i^th list. Find the maximized value S_max obtained.

• % denotes the modulo operator.

• Note that you need to take exactly one element from each list, not necessarily the largest element. You add the squares of the chosen elements and perform the modulo operation. The maximum value that you can obtain, will be the answer to the problem.