โโโ โโโโโโโโโโโโโโโโโโโโโโโโโ โโโโโโโ โโโโโโโ โโโโโโโ โโโโโโโโ
โโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโ โโโโโโ โโโโโโ โโโ โโโ โโโ โโโโโโ โโโโโโโโโ
โโโ โโโโโโ โโโโโโ โโโ โโโ โโโ โโโโโโ โโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโ โโโ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโ โโโ โโโโโโโ โโโโโโโ โโโโโโโ โโโโโโโโ
class Developer:
Name = "Durga Prasad Kota"
Mission = "Build the mindset of a problem solver"
Language = "Python"
Philosophy = ["Think before you code", "Patterns over memorization", "Optimize everything"]
def daily_routine(self):
return ["Learn โฆ Practice โฆ Improve โฆ Repeat"]This isn't just a solutions repo.
It's a documented war against mediocre thinking โ every problem solved with intent, every pattern internalized, every complexity analyzed.
| Tool | Purpose |
|---|---|
| Primary language โ readable, fast, interview-friendly | |
| Practice platform | |
| Progress tracking & documentation |
| ๐งฉ Topic | ๐งฉ Topic | ๐งฉ Topic |
|---|---|---|
| ๐ฆ Arrays & Strings | ๐ซต Two Pointers | ๐ช Sliding Window |
| ๐๏ธ Hashing | ๐ Stack | ๐ถ Queue |
| ๐ Recursion | ๐ Binary Search | ๐ Linked List |
| ๐ณ Trees | ๐ธ๏ธ Graphs | ๐งฎ Dynamic Programming |
| ๐ง Greedy | โ Backtracking | ๐ Problem Solving |
Each topic is practiced with a focus on patterns, edge cases, and optimization.
Each topic is practiced until the pattern becomes instinct.
โ
Arrays & Strings โโโโ Master in/out, traversal, manipulation
โ
Hashing โโโโ Maps, sets, frequency counting
โ
Two Pointers โโโโ Opposite ends, sliding window prep
โก Sliding Window โโโโ Fixed & variable window problems
โก Stack & Queue โโโโ Monotonic stacks, BFS foundations
โก Binary Search โโโโ On answer, rotated arrays, search space
๐ Linked Lists โโโโ Fast/slow pointer, reversal, merging
๐ Trees โโโโ DFS, BFS, LCA, diameter, path sum
๐ Graphs โโโโ Traversals, topological sort, union find
โณ Dynamic Programming โโโโ Memoization, tabulation, 1D/2D DP
โณ Backtracking โโโโ Permutations, combinations, N-Queens
โณ Greedy โโโโ Interval scheduling, activity selection