Data Structures- Hashmaps, Sets, Hash Tables, Hashing and Collisions
Observing hashmaps with python dictionaries
What is a Hashtable/Hashmap?
A hashtable is a data structure that with a collection of key-value pairs, where each key maps to a value, and the keys must be unique and hashable.
- In Python there is a built in hashtable known as a dictionary.
The primary purpose of a hashtable is to provide efficient lookup, insertion, and deletion operations. When an element is to be inserted into the hashtable, a hash function is used to map the key to a specific index in the underlying array that is used to store the key-value pairs. The value is then stored at that index. When searching for a value, the hash function is used again to find the index where the value is stored.
The key advantage of a hashtable over other data structures like arrays and linked lists is its average-case time complexity for lookup, insertion, and deletion operations.
- The typical time complexity of a hashtable is O(1).
What is Hashing and Collision?
Hashing is the process of mapping a given key to a value in a hash table or hashmap, using a hash function. The hash function takes the key as input and produces a hash value or hash code, which is then used to determine the index in the underlying array where the value is stored. The purpose of hashing is to provide a quick and efficient way to access data, by eliminating the need to search through an entire data structure to find a value.
However, it is possible for two different keys to map to the same hash value, resulting in a collision. When a collision occurs, there are different ways to resolve it, depending on the collision resolution strategy used.
Python's dictionary implementation is optimized to handle collisions efficiently, and the performance of the dictionary is generally very good, even in the presence of collisions. However, if the number of collisions is very high, the performance of the dictionary can degrade, so it is important to choose a good hash function that minimizes collisions when designing a Python dictionary.
What is a Set?
my_set = set([1, 2, 3, 2, 1])
print(my_set)
# What do you notice in the output?
# All the duplicate values were removed
# This is because a set is a collection of unique values
# Why do you think Sets are in the same tech talk as Hashmaps/Hashtables?
# Sets eable us to ensure that there are no duplicate values in the hashmap that will cause any collisions
# It gives us a method to resulve potential ollisions in the hashmap
lover_album = {
"title": "Lover",
"artist": "Taylor Swift",
"year": 2019,
"genre": ["Pop", "Synth-pop"],
"tracks": {
1: "I Forgot That You Existed",
2: "Cruel Summer",
3: "Lover",
4: "The Man",
5: "The Archer",
6: "I Think He Knows",
7: "Miss Americana & The Heartbreak Prince",
8: "Paper Rings",
9: "Cornelia Street",
10: "Death By A Thousand Cuts",
11: "London Boy",
12: "Soon You'll Get Better (feat. Dixie Chicks)",
13: "False God",
14: "You Need To Calm Down",
15: "Afterglow",
16: "Me! (feat. Brendon Urie of Panic! At The Disco)",
17: "It's Nice To Have A Friend",
18: "Daylight"
}
}
# What data structures do you see?
# I see a python disctionary (hashmap) used and also other structres nested in the main hashmap, such as an array and another idctionary.
#
# Printing the dictionary
print(lover_album)
print(lover_album.get('tracks'))
# or
print(lover_album['tracks'])
print(lover_album.get('tracks')[4])
# or
print(lover_album['tracks'][4])
lover_album["producer"] = ['Taylor Swift', 'Jack Antonoff', 'Joel Little', 'Taylor Swift', 'Louis Bell', 'Frank Dukes']
# What can you change to make sure there are no duplicate producers?
# We can convert the producers list into a set first to remove duplicate entries, and then copy the values over to a new array or overwrite the existing one
#
lover_album["producer"] = [i for i in set(lover_album["producer"])]
# Printing the dictionary
print(lover_album)
lover_album["tracks"].update({19: "All Of The Girls You Loved Before"})
# How would add an additional genre to the dictionary, like electropop?
# We can either update the key-value pair with a new list that we create
# Or we can reference the list item with the key value, and then append an item to the list
lover_album["genre"].append("Taylor")
# Printing the dictionary
print(lover_album["genre"])
# for k,v in lover_album.items(): # iterate using a for loop for key and value
# print(str(k) + ": " + str(v))
# Write your own code to print tracks in readable format
#
#
for key in lover_album:
print(str(key) + "\t" + str(lover_album[key]) )
def search():
search = input("What would you like to know about the album?")
if lover_album.get(search.lower()) == None:
print("Invalid Search")
else:
print(lover_album.get(search.lower()))
# search()
# This is a very basic code segment, how can you improve upon this code?
# we could improve it by adding a try/except block, where it will also filter improper entries
# to prevent look up errors
# We can make sure that it catches certain errors
def better_search():
query = input("What would you like to know more about the album? ").lower()
try:
print(query + ":\t" + str(lover_album[query]))
except:
print("Invalid input")
better_search()
Hacks
- Answer ALL questions in the code segments
- Create a diagram or comparison illustration (Canva).
- What are the pro and cons of using this data structure?
- Dictionary vs List
- Expand upon the code given to you, possible improvements in comments
-
Build your own album showing features of a python dictionary
-
For Mr. Yeung's class: Justify your favorite Taylor Swift song, answer may effect seed
from random import randint as rand
nectar_album = {
"title": "Nectar",
"artist": "Joji",
"year": 2020,
"genre": ["Lo-fi", "Rhythm", "blues", "Synth-pop", "Alternative R&B"],
"tracks": {
1: "Ew",
2: "MODUS",
3: "Tick Tock",
4: "Daylight",
5: "Upgrade",
6: "Upgrade",
7: "Gimme Love",
8: "Run",
9: "Sanctuary",
10: "High Hopes",
11: "NITROUS",
12: "Pretty Boy (feat. Lil Yachty)",
13: "Normal People (feat)",
14: "You Need To Calm Down",
15: "Afterglow",
16: "Me! (feat. Brendon Urie of Panic! At The Disco)",
17: "It's Nice To Have A Friend",
18: "Daylight"
}
}
# Getting the genres:
print("-----Genres------")
counter = 1
for genre in nectar_album.get("genre"):
print(str(counter) + ") " + genre)
counter+=1
print()
# Inserting new Attribute
print("Adding collaboration entries")
nectar_album["collaborations"] = ["Benee", "Lil Yachty", "Omar Apollo", "Yves Tumor", "Rei Brown"]
print("-----Collaborations------")
counter = 1
for collab in nectar_album.get("collaborations"):
print(str(counter) + ") " + collab)
counter+=1
print()
# Get random song, utilizing the nested dictionary
index = rand(1,18)
print("-----Retrieving Random Song-----")
print(nectar_album["tracks"][index])