HashMap in Python: A Comprehensive Guide to Dictionary Data Structures

In Python, the equivalent of a HashMap is known as a dictionary. A HashMap data structure stores key-value pairs where each key is unique. The keys are mapped to values using a hashing function, making the data structure efficient for operations like inserting, retrieving, and deleting elements. This article explores the HashMaps (dictionaries) work in Python and demonstrates their key features through examples.

Introduction to HashMap in Python

A Hash Map is a data structure well known as a dictionary in the Python language environment. This is one of the most popular data structures known to everyone. The databases store data like arrays pointing to values connected with keys. As will be seen when comparing it with a list, while elements within lists are referenced through positions, dictionaries use keys to access values. Python uses a hash table in the dictionary, which is why the look-up time for the dictionary is almost negligible.

In Python, creating a HashMap is straightforward. We can use curly braces {} or the dict() function to create a new dictionary.

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Adding Elements to a HashMap

This section will show how to add HashMap elements in Python.

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Accessing Values in a HashMap

We can access the value of a specific key by using the key inside square brackets []. If the key does not exist, Python raises a KeyError. Alternatively, we can use the get() method to safely access values, which returns None if the key is absent.

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Modifying Values in a HashMap

Modifying values in a HashMap is simple. We can assign a new value to an existing key.

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Deleting Elements from a HashMap

We can remove elements from a HashMap using the del statement or the pop() method. The pop() method returns the value of the key being removed, whereas del simply removes the key-value pair without returning the value.

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HashMap Operations and Methods

Python dictionaries offer various built-in methods to work with HashMas effectively.

• len(): This method returns the key-value pairs in the dictionary.
• keys(): This method returns all keys in the dictionary.
• values(): This method returns all values in the dictionary.
• items(): This method returns all key-value pairs as tuples.
• update(): The dictionary is updated with elements from another dictionary.

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HashMap Applications in Python

HashMap is widely used in Python Programming because it is efficient in storing and retrieving data. Let’s look at some applications that use HashMap in Python.

• Counting frequency: Counting occurrences of elements in a dataset.
• Caching: Storing the results of expensive operations to avoid repeating them.
• Symbol tables: We can also use a hashmap to store the variable names and values in interpreters or compilers.
• Graph algorithms: It stores the adjacent lists for graphs.

Time Complexity

It takes the same amount of time to hash and access memory indexes. As a result, the search difficulty of a hash map is constant, which is O(1) time.

Hashtable vs Hashmap

The comparison between Hashtable and HashMap in the context of Python.

Also Read: Python Interview Questions and Answers

Conclusion

This article introduces the HashMap (dictionary) in Python. It is a flexible and effective data structure for storing and retrieving information and using keys and values. It provides a comprehensive list of techniques and convenient notation. Python dictionaries are relevant to many programming tasks. Realizing how to work with HashMaps will enhance your problem-solving skills and make a huge difference in your source code.  Explore Python programming in detail with Hero Vired’s Certificate Program in DevOps & Cloud Engineering, offered in collaboration with Microsoft.