Data Structures and Algorithms Using Python and C++

Data Structures and algorithms are the topics of computer science that every programmer should know no matter what aspect of programming interests you. It is believed that if you are having a good knowledge of data structures and algorithms then you know the foundation of designing algorithms and writing a good piece of code. This is the reason why most of the questions in the coding interviews are based on the concepts of data structures and algorithms. In this article, I will take you through a complete course on Data Structures and algorithms using Python and C++ programming languages.

Data Structures and Algorithms using Python and C++

Data Structures can be defined as elements that are used to store and organize data, and algorithms can be defined as a series of steps that we need to follow to solve a problem. The concepts of data structures and algorithms help us to solve problems effectively and efficiently.

A good algorithm is created by implementing the concepts of data structures which allows an algorithm to manage the data efficiently. In any task of computer science, we need to know the concepts of both data structures and algorithms for designing better algorithms for solving complex problems. In the section below, I will take you through some of the most important data structures and algorithms that you should know:

Stacks:

Stacks are abstract data types that are commonly used in almost all programming languages. A stack is a data structure that simulates real-world stacks such as a deck of cards, a stack of plates, etc. Here is how to implement stacks using Python:

Queues:

A queue is a data structure where we insert items from the back and remove items from the front. It follows the principle of First In, First Out data structures. You can think of Queues data structures as a line of people waiting to buy tickets for a show. Here the first person in line is the first to buy the first ticket and so on. So we can say that the queue data structure in computer science simulates the real queue. Here is how to implement queues using Python:

Hash Tables:

Hash tables are like dictionaries in Python, they are data structures that are used to store and retrieve a large amount of data in the format of keys and values. A hash table is based on the concept of hashing which provides a way to store and retrieve data efficiently in the complexities of time and space. Here is how to implement hash tables using Python:

Binary Trees:

A binary tree is a general and powerful data structure that looks like a real tree. It contains nodes in a connected graph where each node has a parent node and a child node in a specific order. A binary tree is made up of nodes where each node contains a left and right pointer and a data item. It also has a root pointer to the topmost node in the tree. The left and right pointers point to the small subtrees on either side. It also has an empty tree which represents a binary tree with no elements. Here is how to implement binary trees using C++:

Linear Search:

A linear search is one of the most basic and useful algorithms, it moves sequentially through a data structure to find the corresponding value this is the reason why it is also known as the sequential search algorithm. Think of the linear search algorithm as a way to find your way through a contact list on your smartphone. A linear search begins at the beginning by reading each name until you find what you are looking for. Here is how to implement linear search or sequential search using Python:

Binary Search:

Binary search also called half-interval search, is an algorithm used in computers systems to find the position of a value in a sorted array. In a binary search algorithm, the list is split in half and then searched in each half. One thing to notice while implementing the binary search algorithm is that the list must be sorted before running the algorithm. Here is how to implement the binary search using Python:

Recursion:

In programming, recursion is a method call to the same method. In other words, a recursive method is a method that calls itself. In recursion, your only task is to simplify the original problem or to solve it directly when simplification is either unnecessary or impossible. Here is how to implement recursion using C++:

Recursive Binary Search:

Recursion means solving problems by breaking down a complex problem into smaller problems and then solving it step by step. Binary search means to find an item in a sorted array by repeatedly dividing the search interval into two halves and recursive binary search means to subdivide the entire binary search process into smaller problems. Simply put, the recursive solution to a binary search is known as a recursive binary search. Here is how to implement a recursive binary search using Python:

QuickSort:

Quicksort is a sorting algorithm that selects an item and rearranges the array forming two partitions so that all items below the item come before and all items above come after. The algorithm is then used recursively to the parts until it gets a sorted list. Here is how to implement the quicksort algorithm using C++:

Fizzzbuzz Algorithm:

The FizzBuzz algorithm is one of the favourite questions in coding interviews. Fizz and Buzz refer to any number that is a multiple of 3 and 5. This coding problem is popular among numbers 3 and 5, but you may be able to see more complex numbers, but the logic for solving the problem will remain the same. Here is how to implement the fizzbuzz algorithm using C++:

Count Sort:

The time complexity of count sort is better than the other sorting techniques. The count sort algorithm works by finding the number of each unique element in the array. Then it calculates the position of each element in a sorted array. The only limitation of the counting sort is that it is limited to small positive integers only. Here is how to implement the count sort algorithm using C++:

Merge Sort:

Merge sort is a sorting algorithm based on the divide and conquer technique. It works by dividing the arrays into two halves and then combines them in a sorted manner. Merge sort is a neat algorithm because it is the sort that sorts itself. This means that sorting by merge requires very few comparisons and exchanges; instead, it relies on a divide-to-win strategy that’s slightly different from that used by quicksort. Here is how to implement merge sort using C++:

Insertion Sort:

The insertion sort algorithm maintains a collection of sorted items and a collection of items to sort. When implementing insert sort in a program, the algorithm keeps both sorted and unsorted collections in the same sequence structure. Here is how to implement the insertion sort algorithm using C++:

Selection Sort:

Selection sort is a sorting algorithm, in particular an in-place comparison sort. The algorithm divides the input array into two parts: the sublist of items already sorted, which is built from left to right at the start (left) of the array, and the subarray of items remaining to be sorted which occupy the rest of the array. Here is how to implement the selection sort algorithm using C++:

Summary

Data Structures and algorithms are the most important concepts that you should know. In this article, I introduced you to some of the most important data structures and algorithms solved and explained using Python and C++. I hope you liked this article on a complete course on data structures and algorithms using Python and C++ programming languages. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder
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