5.9. Data Structures in Python: Hashing

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In Python, the data structure known as Hashing is one of the fundamental concepts for creating efficient and effective systems. Hashing is a method of translating complex information into a simpler, fixed-length representation that can be used for indexing data. This is done through a hash function, which converts the input into a hash value.

Hash values ​​are used to uniquely identify the original data. This is especially useful when the data volume is large. In Python, the data structure that implements the concept of hashing is known as a Dictionary.

Python Dictionaries

A Python dictionary is a data structure that stores key-value pairs. Keys are used to identify values, which can be any type of data such as numbers, strings, lists, etc. Keys in a dictionary are unique and immutable, while values ​​can change.

The Python dictionary is an implementation of the hash table concept. A hash table is a data structure that uses a hash function to map keys to buckets where values ​​are stored. This allows for a quick search for values ​​based on the keys.

Hash function in Python

In Python, the hash() function is used to return the hash value of an object. The hash function is used internally in Python to manipulate and compare objects. For example, when we use an object as a key in a dictionary, Python uses the hash function to determine where the object will be stored in memory.

It is important to note that the hash function produces different results for different types of data. For example, the hash function of a string is different from the hash function of a number.

Collision Issues

One of the issues that can arise with the use of hash functions is collision. A collision occurs when two different keys produce the same hash value. This can cause problems as the hash function would no longer be able to differentiate between the two keys.

Python handles hash collisions through a method called open probing. If a collision occurs, Python will try to find another slot in the hash table to store the value. This is done through a process called polling, which continues until an empty slot is found.

Hashing Applications

Hashing is a very useful technique in many programming applications. It is used in databases for fast indexing of data, in caches to store and retrieve data quickly, in duplication detection algorithms, in cryptography to ensure data security, among others.

In summary, Python's hashing data structure, implemented through dictionaries, is a powerful tool that allows efficient data storage and retrieval. Understanding how this data structure works and how to use it effectively is essential to building systems with Python and Django.

In our complete Python and Django system building course, you'll learn more about data structures, including hashing, and how they can be used to create efficient and effective systems. This course offers a combination of theory and practice to help you become a proficient Python developer.

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245.10. Data Structures in Python: Sorting