In Python, a hash table and a dictionary are often used interchangeably because the built-in dict type in Python is implemented using a hash table. Here are the main points of difference between a hash table and a dictionary:
- A hash table is a data structure that stores key-value pairs and provides efficient lookup, insertion, and deletion operations.
- It uses a hash function to compute an index or hash code from the key, which determines the location where the value is stored in an underlying array.
- The hash function should be designed to minimize collisions (different keys mapping to the same hash code) to maintain optimal performance.
- Hash tables have a constant-time average case complexity for insertion, deletion, and lookup operations, but worst-case scenarios may result in linear time complexity due to collision resolution.
- Hash tables are commonly used when quick access to data based on keys is required, and the order of elements is not significant.
- In Python, the built-in dict type represents a hash table.
Dictionary in Python:
- In Python, a dictionary is an unordered collection of key-value pairs enclosed in curly braces () or created using the dict() constructor.
- Dictionaries allow you to map keys to values and provide fast access to values based on their associated keys.
- Keys in a dictionary must be unique and immutable (e.g., strings, numbers, or tuples), while values can be of any type.
- Dictionaries are mutable, meaning you can add, remove, or update key-value pairs.
- Python dictionaries have built-in methods and functionalities, such as iterating over keys or values, checking membership, and retrieving values based on keys.
- Dictionaries are widely used in Python for various purposes, including data storage, data retrieval, and mapping relationships between entities.
In summary, a hash table is a general data structure that provides efficient lookup, insertion, and deletion operations based on hash codes, while a dictionary in Python is a specific implementation of a hash table that provides key-value mapping with additional built-in functionalities.