Python provides many data structures to store and access data. One such data structure is a hashmap. In this article, we will learn everything about python hashmap. So let’s get started
Python hashmap function
Before understanding the python hashmap it is important to understand the hashtable and hashmap functions in general.
In Python, the hash() function is used to generate a hash value for an object. The returns hash value is an integer, which is unique for each unique object. The hash() function can be used with built-in types such as numbers, strings and tuples, as well as with user-defined classes.
The hash() function is used internally in Python’s dictionary implementation. When you create a dictionary and add key-value pairs to it, Python automatically generates a hash value for each key and uses it to determine where to store the value in the hash table.
The user needs to keep in mind that if the object is mutable, the hash will change after modification. Thus, a hash map cannot be used with mutable keys or items.
Besides, it’s important to note that for user-defined classes, python by default uses the id of the object as a hash but if we want to define our own hash function for the objects of a class, we can define __hash__() function in class.
Python hashtable
A hash table is the underlying data structure used to implement a hashmap. A hash table uses a hash function to map keys to indices in an array, called buckets. The primary function of a hash function is to convert a given key into a specific index in an array, where the corresponding value associated with that key can be located or stored.
The hash function typically takes a key, performs some operations on it, and returns an integer value, known as the hash code or index. This hash code can be used as an index in the array.
In Python, a hash table is used to implement the dictionary class. When a user creates a dictionary and adds key-value pairs to it, Python automatically uses a hash table to store the key-value pairs in a way that allows for efficient searching, adding and removing elements by a key.
Introduction to python hashmap
Now we have a pretty good understanding of python hashtable and hash function, let’s proceed further and understand python hashmap.
In Python, a hashmap is implemented as a dictionary. The keys in a dictionary are hashed, which means that they are transformed into a fixed-size integer value, called a hash code. The hashmap uses this hashcode to store value on the specific index of the hash table and uses a key to search for the value on that specific index. When you look up a value in a dictionary by its key, the key is first passed through a hash function.
A dictionary is a data structure that stores key-value pairs, where each key is unique. Dictionaries are very efficient for searching, adding and deleting elements by key because the average time complexity of these operations is constant. However, the time complexity can be O(n) in the worst case when two keys have the same hashcode known as a collision.
Below is an example to create a dictionary and access its elements.
my_dict={'Name' : 'harry' , 'Age': 31 , 'Country': 'india' , 'Gender' : 'male'}
my_dict['Name']
my_dict['Gender']The dictionary my_dict contains Name, Age, Country, and Gender as the keys. We can get the values by specifying the keys in the dictionary.
Hashmap in python example
The hashmap or dictionary can be created to store the key-value pair. Below is an example of the same.
# Initialize an empty dictionary
my_dict = {}
# Add key-value pairs to the dictionary
my_dict["first_name"] = "Jack"
my_dict["country"] = "USA"
my_dict["age"] = 45we have initiated an empty directory and added key-value pair to it. Now the values from the my_dict can be retrieved as:
# Access values using their keys print(my_dict["first_name"]) print(my_dict["country"]) print(my_dict["age"])
The above codes print the respective values of keys.
Now all the keys from the my_dict can be retrieved using the below code
for key in my_dict:
print(key)
# Output:
# "first_name"
# "last_name"
# "age"similarly, we can also check if a key exists in the directory using the below code:
if "country" in my_dict:
print("key present in my_dict")
else:
print("key is not present in my_dict")Python hashmap vs dictionary
In Python, “hashmap” and “dictionary” refer to the same data structure. The dictionary data type is implemented as a hash table, which allows for fast access to values using keys. Dictionaries are used to store key-value pairs, where each key must be unique and immutable.
It’s worth noting that while in Python, the terms “hashmap” and “dictionary” refer to the same built-in data structure, in other programming languages the two terms may not be interchangeable.
In other programming languages, “hashmap” generally refers to a specific implementation of a map data structure, while “dictionary” refers to a different data structure.
Conclusion
I hope you have liked this tutorial on the python hashmap. In this blog, we have learned about the python hashmap and hashtables. We also understood python hashmap with various examples.
Please do let me know if you need further input.
