Bytephilosopher

Happy Monday, have a productive week❤️ @byte_philosopher

Are you ready for tomorrow it's Monday plus sep 1? @byte_philosopher

Psalms 14:1 "The fool says in his heart, ‘There is no God.’" 2017 Reflections 2. I almost went insane... https://telegra.ph/I-Almost-Went-Insane-08-31

This is insane guys read it

#August_30_LeetCode_Grid 📌 Graphs in DSA A Graph = 🟢 Nodes (called vertices) + 🔗 Connections (called edges). They’re everywhere — social networks, maps, recommendations, even computer networks! Types of Graphs: Directed vs Undirected ➡️ / ↔️ Weighted vs Unweighted ⚖️ Cyclic vs Acyclic 🔄 / 🚫 Ways to Store Graphs: Adjacency List ✅ (efficient) Adjacency Matrix 🔲 (easy but heavy) Popular Graph Algorithms: BFS (Breadth-First Search) 🔍 level by level DFS (Depth-First Search) 🌊 go deep first Dijkstra 🛣️ shortest path Kruskal & Prim 🌐 minimum spanning tree 👉 Mastering graphs = mastering real-world problem solving. @byte_philosopher

Happy Sunday y'all 😊 @byte_philosopher

#August_27_28_29_LeetCode_Grind HashMaps (Python dict) Recap A HashMap stores data in key–value pairs for super-fast access ⚡. Think of it like a dictionary 📖: words = keys, meanings = values. ✅ Key Features: Fast lookups, inserts, deletes → O(1) average Keys are unique Perfect for counting, mapping & caching

hashmap = {"apple": 2, "banana": 5}

print(hashmap["apple"])  # 2
hashmap["banana"] = 10   # update
hashmap["grape"] = 7     # insert
del hashmap["apple"]     # delete

🔥 Use Cases: ✔️ Word frequency counters ✔️ Caching results ✔️ Graph adjacency lists @byte_philosopher

“Let us acquire reverence, dignity, and meekness towards all people, as well as precise knowledge of them. so that we may be able to avoid familiarity, which is the mother of all evils.” +Abba Moses

ሀሙስ የቀን ቅዱስ😉 @byte_philosopher

Introducing ExyRead – your all in one AI powered reading companion After months of building, I’m excited to share that 90% of the core features are now complete! ExyRead is designed to support students and anyone who wants to make their reading and studying smarter and easier. Key Features: AI Chat – ask questions, get instant support One-click PDF summaries – save time, grasp key points faster Note-taking – write down ideas while studying AI note summaries – turn long notes into short takeaways Instant explanations – highlight text and get AI-powered clarity Progress tracking – stay motivated as you read Smart organization – create folders to manage files easily Study reminders – never miss your next session Your feedback will play a big role in shaping the future of the app. 💡 Be one of the first to try it here. #my_project @kintechno

#August_26_LeetCode_Grid 👑 Heap: The King of Efficiency 👑 Ever wondered how to always grab the biggest or smallest number FAST? ⚡ That’s where Heaps come in! 🔥 What’s a Heap? A tree-like structure 📚 Min-Heap → smallest on top (root). Max-Heap → largest on top (with a trick in Python 😉). ⚡ Why are they cool? 📍 Always gives you the top element in O(1) time. ➕ Insert / ❌ Remove in O(log n). Used in priority queues, scheduling, Dijkstra’s algorithm, and finding kth largest/smallest element! 🐍 Python Example:

import heapq

nums = [5, 2, 8, 3, 1]

heapq.heapify(nums)   # min-heap
print(nums[0])        # 👉 1 (smallest)

# max-heap trick
nums = [-x for x in nums]
heapq.heapify(nums)
print(-nums[0])       # 👉 8 (largest)

💡 Remember: Heaps don’t fully sort data, they just keep the top element ready at all times 🚀. ⚔️ Next time you need efficiency → Just call the Heap King 👑 @byte_philosopher

This days what I understand from solving leetcode is, you always have to think in the reverse way. (ገልብጦ ማሰብ😁 ) is the better way. For ex: if your first thought for the solution was addition then use substraction boom it works😁 @byte_philosopher

#August_25_LeetCode_Grid 🚀 Backtracking in DSA – Quick Recap Backtracking is like exploring all paths in a maze. You try options, go forward, and undo your choices if they don’t work. How it works: Choose: Pick a possible option. Explore: Move forward recursively with that choice. Backtrack: Undo the choice to try other possibilities. ✅ Key idea: Explore all possibilities systematically, but prune paths that fail early. ✅ Use cases: Subsets & permutations Combination sum problems Sudoku & N-Queens Maze & pathfinding problems 💡 Tips: Always have a base case to stop recursion. Make sure to undo changes before returning to explore other options. Example in LeetCode: Combination Sum, Subsets, N-Queens @byte_philosopher

Have a productive week❤ @byte_philosopher

This is cool guys🔥 Let's show her some love guys go and star her repo on github. @byte_philosopher

Finally i deployed lesson of the day bot on python anywhere. 🔎 What can Lesson Of The Day Bot do: 📘 Show today’s lesson instantly. 🕰 Browse through past lessons easily. 🔖 Bookmark and revisit lessons you like. 📅 Search by date. 👉 @lesson_of_day_bot here is the Github repo https://github.com/Lidiya-Bokona/Lesson_of_the_day_bot.git #project

መልካም ዕለተ ሰንበት 💛 Have a blessed sunday @byte_philosopher

ደህና እደሩ🫶 @byte_philosopher

#August_21_22_23LeetCode_Grid

I finished my study on trees here is the short summery

🌳 Trees in Data Structures 🌳 Think of a Tree like a family tree or folder system: 🌱 Root → the starting point 🌿 Branches (children) → connect to other nodes 🍂 Leaves → end nodes with no children ✨ Popular Trees: 🌲 Binary Tree → max 2 children per node 🔎 Binary Search Tree (BST) → left < root < right 🏗 Heaps & Balanced Trees → used in priority queues, databases ⚡ Why Learn Trees? ✔ Organize data efficiently ✔ Fast search & sorting ✔ Used in file systems, AI, compilers, HTML DOM 📌 Next time you open folders on your PC… you’re walking through a tree 🌳😉 @byte_philosopher

እንኳን ለእናታችን ለእመቤታችን ቅድስት ድንግል ማርያም በዓለ ዕርገት እና ትንሳኤ አደረሳችሁ አደረሰን 💛 📸ሐመረ ኖህ እንጦጦ ኪዳነምህረት @byte_philosopher