Welcome to the Dojo

Data Structures & Algorithms

• Introduction to Data Structures
• Introduction to Algorithms
• What is a brute-force method?
• Big-O Notation

Important

For each data structure, algorithm and technique, do the following: learn the theory and concepts, then implement it in code and finally solve 5 easy problems.

	Data Structures: way of organizing data for easier processing	Theory & Implementation	Exercices
	Dynamic Arrays: order is important, fast read, fast back insert	C - Python	Leetcode
	Linked-List: order not important, sequence matters, fast front/mid insert	C - Python	Leetcode
	Stack: frequent insert and remove at end = LIFO	Python	Leetcode
	Queues: frequent insert at end and remove from front = FIFO	Python	Leetcode
	Hash Tables: order not important, no duplicates, fast read/write/search	Notes	Leetcode
	Sets: order not important, no duplicates, fast read/write/search, great to compare groups
	Algorithms: step by step instructions for completing a task	Theory & Implementation	Exercices
	Selection Sort, Bubble Sort, Insertion Sort O(n^2)	Notes	Leetcode
	Merge Sort, Quick Sort O(nlogn)	Notes	Leetcode
	Counting Sort [2] O(n) for limited range!	Notes	Leetcode
	Bucket Sort [2]		Leetcode
	Binary Search	Python	Leetcode
	Techniques: common ways of approaching common problems	Theory & Implementation	Exercices
	Two Pointers		Leetcode
	Prefix Sum		Leetcode
	Sliding Window		Leetcode
	Concepts	Theory & Concepts	Exercices
	Recursion: function calling itself, required for trees, backtracking and dynamic programming		Exercices
	Bit Manipulation: fast operates without extra space required		Exercices
	Regular Expressions / 2: quick match of complex patterns		Exercices

Neetcode's Roadmap

Codeforces

Topics per rating

	Title	Rating	Topics	Notes	Exercices
	Newbie	0 - 1199	- Modular Arithmetic - Basic knowledge of primes, multiples, divisors - Euclidean algorithm - Sieve of eatosthenes - Binary modular eponentiation - Combinatorics		Exercices
	Pupil	1200 - 1399
	Specialist	1400 - 1599
	Expert	>= 1600

Reminders in Python

Converting list to dictionnary counter

from collections import Counter

array = [1, 2, 3, 4, 2, 2, 1, 4]
count = Counter(arr)
# Counter({2: 3, 1: 2, 4: 2, 3: 1})

Declaring 2D array filled with zeros

mat = [[0] * m for _ in range(n)]

Sorting tuples by key

data.sort(key=lambda x: x[0])

Walrus operator

import time

def do_something() -> int:
    sleep(1)
    return 42

# slow
if do_something() == 42:
    return do_something()

# much better
x = do_something()
if x == 42:
    return x

# more concise, better? maybe
if (x := do_something()) == 42:
    return x

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