DSA IN PYTHON
DSA Tutorial Using Python – Complete Roadmap
Learn Data Structures and Algorithms using Python with this complete DSA tutorial roadmap. Covers arrays, stacks, queues, trees, graphs, sorting, searching, dynamic programming, greedy algorithms, and
What are Data Structures?
Explanation of data structures and their importance. Definition and Importance A data structure is a particular way of organizing and storing data in a computer so that it can be accessed an
Setting Up the Development Environment
Setting up your development environment properly is a crucial first step in learning Data Structures and Algorithms (DSA) with Python. This guide will help you install Python, choose and set up an Int
Arrays and Lists in Python
Arrays and lists are fundamental data structures used to store and manipulate collections of elements. They form the basis for many more complex data structures and algorithms. This guide will introdu
Stacks in Python
A stack is a linear data structure that follows the LIFO (Last In, First Out) principle. The last element inserted is the first one to be removed. Stacks are used in many real-world applications like
Queues in Python
A queue is a linear data structure that follows the FIFO (First In, First Out) principle. The first element added is the first one removed. Queues are essential in scheduling, buffering, and graph tra
Linked Lists in Python
A linked list is a linear data structure where elements are stored in nodes, and each node points (links) to the next node using references. Unlike Python lists (dynamic arrays), linked lists do not s
Trees in Python
A tree is a hierarchical data structure made of nodes connected by edges. Trees represent parent-child relationships and are used heavily in searching, parsing, databases, and hierarchical storage. Ke
Heaps in Python
A heap is a specialized tree-based structure that satisfies the heap property. Heaps are commonly used to implement priority queues, scheduling systems, and efficient selection problems (top-k). Intro
Graphs in Python
A graph is a non-linear data structure used to represent relationships between objects. Graphs are everywhere: social networks, road maps, computer networks, recommendation systems, dependency managem
Hashing (Hash Map) in Python
Hashing is a technique used to store and retrieve data efficiently using key-value pairs. Python’s dict is a built-in hash map that provides very fast average operations. A hash map is one of the most
Sorting Algorithms in Python
Sorting means arranging elements in a specific order (usually ascending or descending). It is one of the most important topics in DSA because many problems become much easier once the data is sorted—s
Searching Algorithms in Python
Searching is the process of finding whether an element exists in a collection and, if required, returning its position (index, node, or reference). Searching is a core operation used everywhere—databa
Dynamic Programming in Python
Dynamic Programming (DP) is a powerful problem-solving technique used to optimize problems that involve overlapping subproblems and optimal substructure. It is one of the most important topics in DSA
Greedy Algorithms in Python
Greedy algorithms solve problems by making the best choice at the current moment (a locally optimal choice), hoping it leads to a globally optimal solution. Greedy approaches are often simpler and fas
Recursion and Backtracking in Python
Recursion is a technique where a function calls itself to solve smaller instances of the same problem.Backtracking is a systematic problem-solving approach (usually implemented with recursion) that ex
Bit Manipulation in Python
Bit manipulation means working directly with the binary (base-2) representation of numbers using bitwise operators. Many problems become faster, cleaner, and more elegant when solved using bits—especi
Divide and Conquer in Python
Divide and Conquer is a fundamental algorithmic strategy that solves a problem by: This approach is powerful because it often reduces time complexity dramatically—commonly to O(n log n)—and it forms t
Advanced Graph Algorithms in Python
Advanced graph algorithms solve complex relationship, routing, and optimization problems. They are widely used in real-world systems such as: When Do We Need Advanced Graph Algorithms? Graphs become c
Problem-Solving Practice (LeetCode, HackerRank, Codeforces)
Learning Data Structures & Algorithms (DSA) is incomplete without consistent problem-solving. Real mastery comes from applying concepts to unfamiliar problems, recognizing patterns, handling edge