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What is a Hash Table in Python? Creation and Implementation

Hash Tables are an essential data structure for efficiently storing and retrieving data in Python. They are used in many applications, including databases, search engines, and caching systems. With a good understanding of how Hash Tables work, you can make use of this powerful tool in your own programs.

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What is a Hash Table?

What is a Hash Table

A Hash Table, also known as a hash map, is a data structure that stores keys and values and uses a hash function to map the key to an index in an array, where the corresponding value can be quickly retrieved. In technical terms, a Hash Table is an implementation of an associative array abstract data type, with constant average time complexity for operations like insertion, deletion, and search.

Hash Tables in Python, are implemented as dictionaries. Dictionaries use a hash table to store the keys and values and provide fast access to the values based on the keys. To create a dictionary in Python, you can use curly braces {} and separate the keys and values with colons. For example:

d = {'key1': 'value1', 'key2': 'value2'}

In this example, the keys “key1” and “key2” are mapped to the values “value1” and “value2” respectively. To retrieve the value associated with a key, you can use square brackets:

value = d['key1'] # value is 'value1'

In Python, dictionaries use a technique called “hashing” to map keys to indices in the underlying array. This means that the average time complexity of the basic operations (insertion, deletion, and search) is constant, which makes dictionaries highly efficient for many use cases.

It’s important to note that dictionaries are not ordered by default. If you need to maintain the order of the key-value pairs, you can use an OrderedDict instead. An OrderedDict is a dictionary that remembers the order of the keys that were inserted into it. You can create an OrderedDict in Python like this:

from collections import OrderedDict

d = OrderedDict()
d['key1'] = 'value1'
d['key2'] = 'value2'

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What is a Hash Function?

What is a Hash Function?

A hash function is a special mathematical tool that takes in some information and creates a unique, fixed-length code from it.

Think of it like a secret code that only the computer can understand. This code is called a “hash value.” The hash function always creates the same hash value for the same information. But it’s impossible to figure out what the original information was just by looking at the hash value. This makes hash functions useful for things like checking if the information hasn’t been changed, or for creating passwords that are secure and can’t be easily figured out.

Hash functions are widely used for various purposes, such as ensuring data integrity, generating digital signatures, and for implementing data structures like hash tables. They are also used in password management systems, where the password is transformed into a hash value before it is stored in a database, so that it can be compared with the hash value of the entered password at a later time to determine if the password is correct.

Here’s a breakdown of these properties:

This means that if you put the same information through the hash function, you’ll get the same result every time.

It’s not possible to turn the result of a hash function (the “hash value”) back into the original information.

The output of the hash function will always be the same length and number of characters, no matter what kind of information was put in.

The result of the hash function will be different for different inputs, even if just a small part of the information is different. This is called the “avalanche effect.”

Creating a Hash Table

Creating a Hash Table

To create a Hash Table in most programming languages, you need to take the following steps:

Here’s an example of how to create a Hash Table in Python:

class HashTable:
    def __init__(self, size):
        self.size = size
        self.table = [[] for _ in range(self.size)]
    def hash_function(self, key):
        return hash(key) % self.size
    def set(self, key, value):
        index = self.hash_function(key)
        self.table[index].append((key, value))
    def get(self, key):
        index = self.hash_function(key)
        for k, v in self.table[index]:
            if k == key:
                return v
        return None

In this example, the size of the Hash Table is specified when it is created. The hash function takes the key as input and returns the index in the array where the key-value pair should be stored. The set function adds the key-value pair to the array at the specified index, and the get function retrieves the value associated with a key.

This is just one way to implement a Hash Table. The actual implementation will depend on the specific requirements of the use case. However, the basic idea of using a hash function to map keys to indices in an array remains the same.

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Hash Table Implementation

Hash Table Implementation

Hash Table in python can be implemented as:

class HashTable:
    def __init__(self, size):
        self.size = size
        self.buckets = [[] for _ in range(self.size)]
    def hash_function(self, key):
        return hash(key) % self.size
    def set_value(self, key, value):
        index = self.hash_function(key)
        found = False
        for i, kv in enumerate(self.buckets[index]):
            k, v = kv
            if key == k:
                self.buckets[index][i] = (key, value)
                found = True
        if not found:
            self.buckets[index].append((key, value))
    def get_value(self, key):
        index = self.hash_function(key)
        for k, v in self.buckets[index]:
            if key == k:
                return v
        return None

This code implements a simple hash table in Python using an array of lists (buckets) to store data. The hash function maps keys to indices in the array, while the set_value and get_value methods allow data to be stored and retrieved. The code uses the built-in hash function to hash the keys, and modulo self.size to ensure that the returned index is within the range of the array.

In case of collisions (when two keys hash to the same index), the code uses a simple linear search in the list at that index to find the key-value pair. The code also handles updating the value associated with a key if the key is already present in the hash table.


To summarise, hash tables are a crucial data structure in computer science and are widely used in many programming languages, including Python. They allow for efficient storage and retrieval of data, making them an important tool for many applications, such as databases, search engines, and caching systems.

We hope this guide has provided you with a good understanding of hash tables in Python, including their basic concepts and implementation. If you have any further questions or doubts, please reach out to us on our community page. We are always happy to help and encourage ongoing learning and growth.

The post What is a Hash Table in Python? Creation and Implementation appeared first on Intellipaat Blog.

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