Hash Table Practice Guide 🧩

Hash tables are fundamental data structures that enable efficient key-value storage and retrieval. Here's a quick breakdown:

🔑 Key Concepts

• Hash Function: Converts keys into array indices (e.g., hash(key) = key % array_size)
• Collision Handling:
  • Chaining (linked lists at each bucket)
  • Open Addressing (probing for empty slots)
• Time Complexity:
  • Average case: O(1) for insert, delete, lookup
  • Worst case: O(n) (if collisions are frequent)

📚 Practical Applications

• Database indexing 🗂️
• Caching systems 🔄
• Implementing dictionaries 📖
• Managing unique elements in sets 🧾

Explore more about data structures at /en/learn/data_structures ➡️

💻 Code Example (Python)

class HashTable:
    def __init__(self):
        self.size = 10
        self.table = [[] for _ in range(self.size)]
    
    def hash_func(self, key):
        return hash(key) % self.size
    
    def insert(self, key, value):
        bucket = self.hash_func(key)
        self.table[bucket].append((key, value))  # Simple chaining
    
    def lookup(self, key):
        bucket = self.hash_func(key)
        for k, v in self.table[bucket]:
            if k == key:
                return v
        return None

For advanced topics like collision resolution strategies, visit /en/learn/collision_resolution 🔍