Introduction.py

#Hash Tables are data structures which generally provide very fast(O(1)) lookups, insertions and deletions
#In Python, dictionaries are implemented as hash tables.

#The way hashing works is that there is a bucket containing slots to fill with elements.
#Like in arrays, elements are referenced by their integer indexes, in dictionaries, or hash tables,
#values are referenced by their keys, which can be of any data type.
#Now there are different kinds of hash functions (eg: MD5, SHA1, SHA256) which are used to convert the keys into hashes, which are unique for each key
#And the hashes are then mapped to some slot in the bucket. And the key and value pair get stored in the slot,
#or in some accompanying data structure within the slot (like, linked lists)

#In general, the lookup, insert and delete operations all are very fast, in the order of O(1)
#But in some cases, more than one keys can map to the same slot and that increases the time complexity by some margin,
#although not by a lot in most cases. This is known as a collision.
#Now, like for almost all problem there is some sort of a solution in the computer science world,
#collisions can also be resolved by numerous collision resolution techniques like open addressing and closed addressing

#Enough details, let's look at how hash tables are implemented in Python using dictionaries.

dictionary = dict()
dictionary = {'one':1, 'two':2, 'three':3, 'four':4, 'five':5}
print(dictionary)
#{'one': 1, 'two': 2, 'three': 3, 'four': 4, 'five': 5}

print(dictionary.keys())
#dict_keys(['one', 'two', 'three', 'four', 'five'])

print(dictionary.values())
#dict_values([1, 2, 3, 4, 5])

print(dictionary.items())
#dict_items([('one', 1), ('two', 2), ('three', 3), ('four', 4), ('five', 5)])

print(dictionary['one']) #Accessing a value by its key in O(1) time
#1

dictionary['six'] = 6 #Inserting the value 6 for the key 'six' in O(1) time.
print(dictionary)
#{'one': 1, 'two': 2, 'three': 3, 'four': 4, 'five': 5, 'six': 6}