Which Data Structure Is Stored in Dictionary?


Larry Thompson

Which Data Structure Is Stored in Dictionary?

When working with Python, you often come across the term “dictionary.” But have you ever wondered what data structure lies behind this powerful tool? In this article, we will explore the inner workings of Python dictionaries and shed light on the data structure used to store their values.

Introduction to Dictionaries

A dictionary in Python is an unordered collection of key-value pairs. It provides a way to store and retrieve data based on unique keys. Dictionaries are incredibly versatile and commonly used due to their efficient lookup time, making them ideal for scenarios where quick access to specific information is crucial.

The Hash Table Data Structure

The underlying data structure used by Python dictionaries is a hash table. A hash table, also known as a hash map, is a data structure that implements an associative array abstract data type. It uses a technique called hashing to map keys to corresponding values.

Hashing involves applying a hash function to a key, which generates an index or hash code. This index is then used as an address in an array-like structure called a bucket. Each bucket holds one or more key-value pairs.

Let’s take a look at how this works:

  • Step 1: The dictionary receives a key-value pair.
  • Step 2: A hash function calculates the index for the given key.
  • Step 3: The calculated index points to the corresponding bucket in the hash table.
  • Step 4: The key-value pair is stored within that bucket.

Collision Handling

While hash tables provide efficient lookup time, collisions can occur. A collision happens when two different keys generate the same hash code or index.

To handle collisions, Python uses a technique called “chaining. “

In chaining, each bucket in the hash table maintains a linked list of key-value pairs that map to the same index. When a collision occurs, the new key-value pair is added to the end of the linked list.

Advantages of Using Hash Tables

The use of hash tables in Python dictionaries offers several advantages:

  • Fast Lookup: Retrieving values from a dictionary based on keys is very efficient, with an average time complexity of O(1).
  • Flexible Key Types: Unlike lists or arrays, dictionary keys can be of any immutable type, such as strings, integers, or tuples.
  • Dynamic Size: Dictionaries can grow and shrink dynamically as key-value pairs are added or removed.


In conclusion, Python dictionaries are implemented using a hash table data structure. The use of hash tables allows for fast lookup times and flexible key types. Collisions are handled through chaining, where multiple key-value pairs are stored within the same bucket.

Dictionaries are powerful tools in Python that provide efficient access to data based on unique keys. Understanding the underlying data structure helps us appreciate their speed and versatility.

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