GitHub - LeetCode-in-Python/LeetCode-in-Python: Python-based LeetCode algorithm problem solutions, regularly updated. Cannot retrieve latest commit at this time. Python-based LeetCode algorithm problem solutions, regularly updated. "For coding interview preparation, LeetCode is one of the best online resource providing a rich library of more than 300 real coding interview questions for you to practice from using one of the 7 supported languages - C, C++, Java, Python, C#, JavaScript, Ruby." Top_100_Liked_Questions, Top_Interview_Questions, Array, Backtracking, Big_O_Time_O (n*n!)_Space_O (n+n!) Top_100_Liked_Questions, Top_Interview_Questions, Array, Backtracking, Big_O_Time_O (n*n!)_Space_O (n+n!) Top_100_Liked_Questions, Top_Interview_Questions, Array, Backtracking, Big_O_Time_O (n*n!)_Space_O (n+n!) Top_100_Liked_Questions, Top_Interview_Questions, Array, Backtracking, Big_O_Time_O (n*n!)_Space_O (n+n!) Top_100_Liked_Questions, Top_Interview_Questions, Array, Backtracking, Algorithm_I_Day_11_Recursion_Backtracking, Level_2_Day_20_Brute_Force/Backtracking, Udemy_Backtracking/Recursion, Top_Interview_150_Backtracking, Big_O_Time_O (n*n!)_Space_O (n+n!) Your ideas/fixes/algorithms are more than welcome!

Level up your coding skills and quickly land a job. This is the best place to expand your knowledge and get prepared for your next interview.

LeetCode is a popular platform for practicing and honing your programming skills through a wide range of algorithmic problems. Python, with its simplicity and versatility, is one of the most widely used languages on LeetCode. Whether you are a beginner looking to learn the basics of algorithms or an experienced developer aiming to brush up your skills, understanding Python on LeetCode is essential. This blog will take you through the fundamental concepts, usage methods, common practices, and best practices when using Python on LeetCode. Python has a simple and intuitive syntax. For example, to print a statement in Python, you use the print() function: print("Hello, LeetCode!") Variables in Python are dynamically typed. You can assign a value to a variable without specifying its type explicitly: Lists: Lists are mutable sequences in Python. They can store elements of different types. You can access elements using indexing and perform operations like appending, inserting, and removing elements. Tuples: Tuples are immutable sequences. Once created, their elements cannot be changed. Dictionaries: Dictionaries are used to store key - value pairs. They are unordered and provide fast access to values based on keys. If - Else: Used for conditional execution. print("x is greater than 5") print("x is less than or equal to 5") For Loop: Used for iterating over a sequence (like a list or a string). print(num) While Loop: Executes a block of code as long as a certain condition is true. print(count) count += 1 LeetCode provides an in - built code editor with Python support. However, if you prefer to work locally, you need to have Python installed on your machine. You can use popular code editors like Visual Studio Code or PyCharm.

This repository includes my solutions to all Leetcode algorithm questions. This problems mostly consist of real interview questions that are asked on big companies like Facebook, Amazon, Netflix, Google etc. If you find my solutions hard to comprehend, give yourself a time to solve easier questions or check discussion section to problem on LeetCode. Feel free to contact me for improvements 😃 Some problems may need premium subscription on LeetCode to unlock it! Is Graph Bipartite? Python ❤️ where simple is better than complex. Please open a pull request if you need! This project is licensed under the MIT License - see the LICENSE.md file for details All Python solutions for Leetcode. Contribute to cnkyrpsgl/leetcode development by creating an account on GitHub.

In this course, you'll have a detailed, step by step explanation of hand-picked LeetCode questions where you'll learn about the most popular techniques and problems used in the coding interview, This is the course I wish I had when I was doing my interviews. and it comes with a 30-day money-back guarantee What is LeetCode? LeetCode is essentially a huge repository of real interview questions asked by the most popular tech companies ( Google, Amazon, Facebook, Microsoft, and more ). The problem with LeetCode is also its advantage, IT'S HUGE, so huge in fact that interviewers from the most popular companies often directly ask questions they find on LeetCode, So it's hard to navigate through the huge amount of problems to find those that really matter, this is what this course is for. I spent countless hours on LeetCode and I'm telling you that you don't have to do the same and still be able to get a job at a major tech company. In this course, I compiled the most important and the most popular interview questions asked by these major companies and I explain them, in a true STEP BY STEP fashion to help you understand exactly how to solve these types of questions. The problems are handpicked to ensure complete coverage of the most popular techniques, data structures, and algorithms used in interviews so you can generalize the patterns you learn here on other problems. Each problem gets multiple videos : Explanation and intuition video (s): we do a detailed explanation of the problems and its solution, this video will be longer because we will do a step by step explanation for the problems. Coding video (s): where we code the solution discussed in the explanation video together. We will use basic python for this course to code our solutions, previous knowledge in python is preferred but NOT required for the coding part of the course. The problems are categorised for easier navigation and will be regularly updated with more popular and interesting problems. Some of the stuff this course will cover are : Arrays and Strings interview questions. Searching interview questions and algorithms. Dynamic Programming interview questions. Backtracking interview questions ( With step by step visualisation ). Trees and Graphs interview questions and algorithms. Data structures Like Stacks, Queues, Maps, Linked Lists, and more. In other words, this course is your one-stop-shop for your dream job. People who want to develop their problem solving skills.

This repository contains a categorized list of LeetCode problems, organized by problem-solving techniques. Use this cheat sheet as a quick reference for different problem types and corresponding LeetCode problems. 1. Heap/Sorting Used for problems involving finding the k-th smallest/largest elements or sorting. 215. Kth Largest Element in an Array 347. Top K Frequent Elements 378. Kth Smallest Element in a Sorted Matrix 75. Sort Colors 2. Two Pointers (Linked Lists) Involves problems where two pointers or a two-pointer technique is used to solve linked list problems. 21. Merge Two Sorted Lists 19. Remove Nth Node From End of List Typically involves optimizing a value while managing two criteria simultaneously with a sorted array. 948. Bag of Tokens Characteristics: Maximization/Minimization, Sorted Input, Dynamic Adjustment, Resource Management. 3. Brute Force/Backtracking Suitable for problems where constraints are small and brute force is fast enough. 4. Dynamic Programming (Small Constraint Bounds) Used when brute force is too slow, but constraints are small. 5. Prefix Sums Deals with problems involving subarrays or substrings with sums or additive operations. 6. Sliding Window Involves problems with subarrays or substrings where the sliding window technique is used but does not involve additive sums. 7. Binary Search (Monotonic Condition) Used for problems involving calculating max/min with a monotonic condition. 8. Dynamic Programming (Non-Monotonic Condition) For problems where dynamic programming is used to calculate max/min but without a monotonic condition. 9. Dynamic Programming (Splittable Sub-Problems) For problems that can be split into smaller sub-problems. 10. Greedy Algorithms Used when a problem can be solved with a greedy approach to calculate the answer. 11. Brute Force/Backtracking (Number of Ways) For problems asking for the number of ways and brute force is efficient enough.

LeetCode is a popular platform for practicing coding problems and preparing for technical interviews. It offers a wide range of algorithmic challenges that can be solved using various programming languages, including Python. This tutorial will guide you through the process of using LeetCode algorithms in Python, providing examples and code snippets to help you understand the concepts better. LeetCode problems are categorized into different types, such as: Array and Strings: Problems that involve manipulating arrays and strings. Linked Lists: Challenges that require working with linked list data structures. Trees and Graphs: Problems that involve traversing and manipulating tree and graph structures. Dynamic Programming: Challenges that require optimizing solutions using dynamic programming techniques. Each problem typically includes a description, input and output specifications, and examples. Understanding these components is crucial for effectively solving the problems. Before diving into solving LeetCode problems, ensure you have Python installed on your machine. You can download the latest version from the official Python website. Additionally, using an Integrated Development Environment (IDE) like PyCharm or Visual Studio Code can enhance your coding experience. Let’s take a look at a classic LeetCode problem: Two Sum. The problem statement is as follows: Given an array of integers, return indices of the two numbers such that they add up to a specific target. You may assume that each input would have exactly one solution, and you may not use the same element twice. Here’s how you can solve this problem using Python: num_map = {} for index, num in enumerate(nums): complement = target - num if complement in num_map: return [num_map[complement], index]

Introduction to Data Structures & Algorithms with Leetcode Algorithms GitHub repo is here: https://github.com/bee-san/Algorithms Welcome to Bee's guide to datastructures and algorithms! This is based on https://github.com/guyinatuxedo/nightmare What you need to know Learn why it works, not just how. The problems are mostly medium - hards, I try to not include easy problems unless they are the first problem in a category. This is a course on datastructures and algorithms based around leetcode problems. Learn DS&A via problems, with lengthy explanations. This guide is ordered by how likely it is for that datastructure / algorithm to show up in an interview and how vital that knowledge is to understanding other data structures / algorithms. Each section will lead with a leetcode style problem, and end with problems you can do on your own. This way, you only ever learn what is relevant. All code will be in Python due to how easy it is to read. If you want to contribute more code, feel free to. This is on GitHub after all! If you're okay with Python, but want to learn the advanced stuff check out my other book https://github.com/bee-san/Python-Zero-to-Hero I also have my own blog, https://skerritt.blog that you may enjoy. You should roughly know these things. I have linked to some of my own resources for you to learn them: For other resources you should see: Look through my Not Done Yet section and complete / improve them! Why Leetcode and not X, Y, Z platform? AlgoExpert is not paying me to tell you that the scariest thing in the world is not knowing how to invert a binary tree in a coding interview yet. HackerRank's problems are too wordy for me to copy & paste. Honestly if any other coding company came along and paid me to advertise their product I would it's just I used Leetcode. Deciding on what the best platform to use is another form of procrastination.

Learn and understand how to solve coding problems using different algorithms and data structures to crack IT interviews Solve 150+ coding exercises to ace DSA interviews with confidence. Master data structures—linked lists, trees, heaps, graphs—for practical use. Analyze time and space complexity to optimize your coding solutions. Apply DSA to solve LeetCode challenges and practical coding problems. Think like a pro coder to tackle complex problems efficiently. Grasp DSA concepts faster with animated examples for deeper insight. Boost your developer skills to excel in technical interviews confidently. Why Purchase "Data Structures and Algorithms: Using Python"? Master Key Data Structures and Algorithms: Learners will gain a deep understanding of essential data structures (like arrays, linked lists, stacks, queues, trees, graphs) and algorithms (such as sorting, searching, dynamic programming, and backtracking) through hands-on practice with Leetcode’s top 150 questions. Enhance Problem-Solving Skills: By tackling a variety of coding challenges, learners will develop strong problem-solving skills, learning how to approach and break down complex problems into manageable parts, and implement efficient solutions in Python. Prepare for Technical Interviews: Learners will be well-prepared for technical interviews at top tech companies. They will become familiar with common interview questions and scenarios, and learn how to articulate their thought process and solutions effectively during interviews. Improve Code Efficiency and Optimization: Learners will learn to write clean, efficient, and optimized code. They will understand the importance of time and space complexity, and how to improve the performance of their solutions by analyzing and optimizing their code. Develop Debugging and Testing Skills: Gain proficiency in debugging and testing your code, learning to identify and fix errors, and ensure your solutions are robust and reliable. Build Confidence in Coding Competitions: Increase your confidence in participating in coding competitions and hackathons by practicing with real-world problems and learning strategies to approach competitive programming. Foster a Growth Mindset: Cultivate a growth mindset by embracing challenges, learning from mistakes, and continuously improving your coding skills through persistent practice and feedback. These objectives will help learners build a solid foundation in coding and algorithmic thinking, making them more confident and competent in their technical skills Computer Engineer, polyglot working on multiple technologies.

Learn level order traversal, a BFS application for binary trees. Explore its algorithm, time/space complexity, and a related problem! Master Dynamic Programming with memoization! Learn recurrence relations through Fibonacci and apply DP to solve complex problems efficiently Introduction In the fast-paced world of coding competitions and technical interviews, speed is crucial. With companies expecting swift... Learn how to implement stacks using global variables. Discover the magic of binary search in Python! Sliding window technique in Python for efficient subarray problem-solving. Permutation is a classic interview question. Message... Message Sent! Master coding challenges with our comprehensive LeetCode solutions in Python. Find step-by-step explanations, optimized code, and tips to enhance your problem-solving skills. Ideal for coding enthusiasts and professionals preparing for tech interviews