# Understanding Hash Tables

# Introduction:

Hash tables are data structures that use a hash function to map keys to values. They are useful for quick lookups and are commonly used in applications such as databases, caches, and compilers. In this article, we will learn about hash tables, their components, and how they work, followed by a practical implementation in Python.

# Table of Contents:

- Hash Functions
- Collision Handling
- Creating a Hash Table
- Adding, Retrieving, and Removing Items
- Hash Table Implementation in Python
- Conclusion

# Hash Functions

A hash function is a function that takes an input (or key) and returns a fixed-size string of bytes. The output is typically a "hash code" or "hash value", which is used as the index to store the key-value pair in the hash table. A good hash function should:

- Distribute keys uniformly across the hash table
- Be fast to compute
- Produce unique hash values for distinct keys (although this is not always possible)

# Collision Handling:

A collision occurs when two or more keys have the same hash value. There are several methods to handle collisions in hash tables:

**a. Separate Chaining:**

In this method, each slot in the hash table contains a linked list of key-value pairs. When a collision occurs, the new key-value pair is added to the list.

**b. Open Addressing:**

In open addressing, when a collision occurs, a new slot is found by probing the hash table using different techniques, such as linear probing, quadratic probing, or double hashing.

# Creating a Hash Table:

To create a hash table, you need to decide on the size of the table and the hash function you will use. The size of the hash table should be a prime number to help minimize collisions.

# Adding, Retrieving, and Removing Items:

**Adding:** To add a new key-value pair to the hash table, calculate the hash value using the hash function, find the corresponding index, and store the key-value pair at that index.

**Retrieving:** To retrieve a value for a given key, calculate the hash value using the hash function, find the corresponding index, and return the value stored at that index.

**Removing:** To remove a key-value pair, calculate the hash value using the hash function, find the corresponding index, and remove the key-value pair from the hash table.

# Hash Table Implementation in Python:

```
class HashTable:
def **init**(self, size):
self.size = size
self.table = [None] \* self.size
def _hash(self, key):
return hash(key) % self.size
def add(self, key, value):
index = self._hash(key)
if not self.table[index]:
self.table[index] = []
self.table[index].append((key, value))
def get(self, key):
index = self._hash(key)
if self.table[index]:
for pair in self.table[index]:
if pair[0] == key:
return pair[1]
return None
def remove(self, key):
index = self._hash(key)
if self.table[index]:
for i, pair in enumerate(self.table[index]):
if pair[0] == key:
del self.table[index][i]
return True
return False
```

python

# Conclusion:

In this tutorial, we have covered the basics of hash tables, their components, and their use in applications. We also implemented a simple hash table in Python. Hash tables are an essential data structure for many applications due to their fast lookup times and efficient storage.

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