HashMap (Dictionary)

A hash map (also known as a hash table, dictionary, or associative array) is a data structure that stores data in key-value pairs. Think of it like a real-world dictionary where a word (the key) is used to look up its definition (the value).

Think of it like a real-life dictionary:

• You look up a word (key) and get its definition (value)
• You don’t go page by page — you jump directly to the word, thanks to indexing (like hashing)

The core of a hash map is a hash function, which takes the key as input and computes an integer, called a hash code or hash. This hash code is then used as an index to find the correct location (or “bucket”) in an underlying array where the key-value pair is stored. This allows for extremely fast lookups, insertions, and deletions, regardless of the size of the data.

The main advantage of hash maps is their average O(1) time complexity for these operations, meaning the time it takes doesn’t grow with the number of elements.

Implementing Dictionaries in Programming Languages: In Python, the dict data type is a highly optimized hash map implementation. Other languages like Java, C++, and JavaScript also have built-in hash map structures (HashMap, unordered_map, and Object/Map respectively).

Storing Unique Values: Hash maps can be used to efficiently store unique elements, as each key in a hash map must be unique. This makes them useful for tasks like removing duplicate items from a list.

Feature
Fast Lookup	O(1) average time to access data by key
Flexible Keys	Keys can be strings, numbers, or tuples (Keys must be unique)
Dynamic Size	Grows as needed
Built-in Support	Available in almost all languages (e.g., dict in Python, Map in JavaScript, HashMap in Java)

# Create a HashMap using a dictionary
user_info = {
    "ada": "[e-mail]",
    "einstein": "[e-mail]",
    "newton": "[e-mail]",
	"curie":"[e-mail]"
}

# Accessing data by key
print(user_info["bob"])  # Output: [e-mail]

# Adding a new key-value pair
user_info["diana"] = "[e-mail]"

# Updating a value
user_info["alice"] = "[e-mail]"

# Deleting a key
del user_info["charlie"]

# Printing the final HashMap
print(user_info)

Use Cases

1. Fast Data Lookups: Hash maps are ideal for situations where you need to retrieve a value based on a specific key very quickly. For example, a phone book application where you want to find a person’s number using their name, or a user database where you want to retrieve a user’s profile using their username.
2. Counting Frequencies: You can use a hash map to count the occurrences of items in a list. The item itself becomes the key, and its count becomes the value. For instance, counting the frequency of each word in a document.

https://en.wikipedia.org/wiki/Hash_table