Here you can find solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures.
Also, this repo will be updated with new solutions from time to time.
Note that this repo is meant to be used for learning and researching purposes only and it is not meant to be used for production.
All solutions are written in Python (more precisely, Python 3), using the Built-in Functions (print, len, range, sorted, sum, min, max, etc...) and a few modules from the Python Standard Library like:
- math (used for constants like math.pi, math.inf and functions like math.ceil, math.floor, math.gcd, math.log, math.pow, math.sqrt, etc)
- collections (used for collections.deque when there is a need for Stack or Queue data structures)
- heapq (used when there is a need for Priority Queue data structure).
So, to execute these solutions there is no need from installing any external packages.
Coding style and name conventions are described in this file PEP8.
Note that I'm not the author of these problems, they are from sites like LeetCode (you can find more than 40 sites like this in the Training Sites section). Only the solutions and explanations are mine.
For easier navigation into the solutions, each file with a solution in this repo will have the following template:
'''
Problem Name
Problem explanation.
Input: XXX
Output: XXX
Output explanation: XXX
=========================================
Solution 1 explanation.
Time Complexity: O(X)
Space Complexity: O(X)
Solution 2 explanation.
(some of the problems are solved in more than one way)
Time Complexity: O(X)
Space Complexity: O(X)
'''
##############
# Solution 1 #
##############
def name_of_solution_1(params):
# description of code
pass
##############
# Solution 2 #
##############
def name_of_solution_2(params):
# description of code
pass
###########
# Testing #
###########
# Test 1
# Correct result => 'result1'
test_val = 'example1'
print(name_of_solution_1(test_val))
print(name_of_solution_2(test_val))
# Test 2
# Correct result => 'result2'
test_val = 'example2'
print(name_of_solution_1(test_val))
print(name_of_solution_2(test_val))
Each solution/problem in this repo belongs to one of these categories:
- Arrays - Array Manipulations, Sorting, Binary Search, Divide and Conquer, Sliding Window, etc.
- Linked Lists - Linked List Searching, Pointer Manipulations, etc.
- Trees - Binary Search Trees, Tree Traversals: Breadth-First (Level Order) Traversal, Depth-First Traversal (Inorder, Preorder, Postorder), etc.
- Dynamic Programming - 2D and 1D Dynamic Programming, LCS, LIS, Knapsack, etc.
- Strings - String Manipulations, Reversing, Encodings/Decodings, etc.
- Math - GCD, LCM, Prime Factors, Math Formulas, etc.
- Other - Backtracking, BFS, DFS, Queues, Stacks, Matrices, etc.
The learning resources are divided into 4 categories: Courses, Books, Training Sites, Other Resources.
Collection of free courses from one of the best CS universities.
-
Princeton University (Coursera)
-
MIT University (YouTube)
-
Harvard University (YouTube)
-
UC Berkeley
Several books that have made an impression on me:
- Grokking Algorithms by Aditya Bhargava - The best book for complete beginners in algorithms! I wish this book existed when I started learning algorithms.
- Introduction to Algorithms by CLRS - This book is called "bible textbook of algorithms" by many programmers.
- Algorithms by Robert Sedgewick & Kevin Wayne - These authors are instructors of the previously mentioned coursera courses: Algorithms Part 1 and Algorithms Part 2. Also this book has excellent and free site with exercises, presentations, and examples.
- The Algorithm Design Manual by Steven Skiena - The book describes many advanced topics and algorithms and it focuses on real life practical examples. This book has one of the best site with resources (solutions, algorithms and data structures, python implementations).
- Algorithms by S. Dasgupta, C. Papadimitriou, and U. Vazirani - This book is an official book for algorithm and data structure classes in several famous universities.
- Competitive Programming 3 by Steven Halim & Felix Halim - A great book that prepares you for competitive programming (not for complete beginners). You can learn many things and tricks about competitive programming.
If the problems from LeetCode are not enough and you need more problems like those, you can find much more on these platforms:
- HackerRank
- CodeChef
- HackerEarth
- CodeForces
- Topcoder
- Project Euler
- SPOJ
- A2OJ
- PEG
- Online Judge
- E-Olymp
- VJudge
- USA CO
- CodeAbbey
- CS Academy
- CodingBat
- AtCoder
- Russian Code Cup
- Wolfram Challenges
- Google's Coding Competitions
- Codility
- CoderByte
- Rosetta Code
- Daily Coding Problem
- Daily Interview Pro
- Codewars
- LintCode
- DevPost
- Exercism
- CodeFu
- Mendo
- Z-Training
- Edabit
- Cyber-dojo
- CodeKata
- Advent of Code
- Kattis
- Brilliant
- AlgoExpert
- Codingame
- CheckiO
- FightCode
- Kaggle
- Rosalind
- Geeks For Geeks - The site which all interested in algorithms (no matter if beginners or experts) should know!
- The Algorithms - Python - Great GitHub repo with many algorithms written in Python (Link from the same repo written in other programming languages).
- KhanAcademy - Algorithms - Good explanations for some basic algorithms.
- HackerRank - YouTube tutorials