🚀 𝗗𝗮𝘆 𝟮𝟳/𝟯𝟬 — 𝗗𝗦𝗔 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Day 27 and continuing with dynamic programming. If Day 26 was about understanding the idea of DP, today was about applying it more confidently. The challenge is no longer just solving the problem — it’s identifying that it is a DP problem in the first place. 🔎 𝗗𝗮𝘆 𝟮𝟳 𝗙𝗼𝗰𝘂𝘀 • Recognizing DP patterns • Building solutions using subproblem relationships • Solved: ✅ Unique Paths ✅ Word Break ✅ Longest Increasing Subsequence Dynamic programming still feels challenging, but it’s starting to feel less intimidating and more structured with practice. Almost at the finish line. On to Day 28 #DSA #Python #LeetCode #SoftwareEngineering #ProblemSolving #Consistency
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Easy to test -> easy to change. Tests are arguably as important as the code. Hard-to-test code reveals design issues. Dependency that’s a pain to mock? Expose a parameter. Separate creation from use. Does the test require heroic effort to set up preconditions? Probably have a coupling problem. I’m running a hands-on intro at PyCon US that gets into this. 📚🐍
Join Paul Zuradzki at #PyConUS 2026 for the tutorial "Practical Software Testing with #Python" on May 13th and learn to write tests that let you code with confidence 🧪 https://lnkd.in/g657iXQw Register now: https://lnkd.in/gabMaqwX
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🚀 𝗗𝗮𝘆 𝟮𝟴/𝟯𝟬 — 𝗗𝗦𝗔 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Day 28 and today was all about revisiting and strengthening the tougher concepts from the past few days. Instead of jumping into new topics, I focused on reinforcing dynamic programming and graph patterns — going back to problems that felt challenging and solving them again with a clearer approach. 🔎 𝗗𝗮𝘆 𝟮𝟴 𝗙𝗼𝗰𝘂𝘀 • Revisiting dynamic programming patterns • Strengthening problem-solving without relying on hints • Re-solved selected problems from recent topics It’s interesting to see how problems that felt complex earlier start to make more sense with repetition. That’s probably the biggest lesson from this challenge so far. Almost there. On to Day 29 #DSA #Python #LeetCode #SoftwareEngineering #ProblemSolving #Consistency
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🚀 Day 23 of #100DaysOfCode Today I built a Turtle Crossing Game 🐢🚗 using Python and OOP concepts! 🎯 What I implemented: Player movement using keyboard controls Random car generation with increasing difficulty Collision detection system Level progression with speed increase Scoreboard to track levels 💡 Key Learning: This project helped me understand how to structure a game using Object-Oriented Programming (OOP). Breaking the code into classes like Player, CarManager, and Scoreboard made it more organized and scalable. ⚡ Challenge: Handling collision detection and increasing difficulty dynamically as levels progress. 📈 Next Step: Add sound effects, better UI, and maybe multiple lives! 🔗 GitHub Repo: https://lnkd.in/gP2fVATR #Python #100DaysOfCode #CodingJourney #GameDevelopment #OOP #BeginnerProjects
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🐞 Day 13 of #100DaysOfCode Today I focused on one of the most important skills in programming — DEBUGGING 🔍 💡 What I learned: - How to identify and describe problems clearly - Reproducing bugs step by step - Tracing code line by line - Using print statements for debugging - Introduction to using a debugger tool 🧠 Key Learning: Writing code is only half the job — finding and fixing errors is what makes you a better developer. Debugging improved my problem-solving skills and helped me understand my code more deeply. Small bugs → Big learning 🚀 #100DaysOfCode #Python #Debugging #CodingJourney #ProblemSolving #Learning #BuildInPublic
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🚀 Day 6 – Functions in Python Today I learned one of the most important concepts in programming — Functions. Instead of writing the same code again and again, functions allow us to reuse logic efficiently. 🔹 A function is a reusable block of code 🔹 Defined using the def keyword 🔹 Can take inputs and return outputs 💡 Example: def add(a, b): return a + b print(add(10, 20)) # 30 🧠 Key Learning: Functions make code cleaner, scalable, and easy to maintain. This is where programming starts feeling powerful. Ajay Miryala 10000 Coders #Python #CodingJourney #Functions #100DaysOfCode #Developer
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Day 64 – Coding Challenge 🚀 Today’s problem focused on greedy observation and traversal. 🔹 Problem Statement: Given heights of buildings in a row, count how many buildings can see sunlight from the left. A building can see sunlight only if no taller building blocks it from the left. 🔹 Approach: Traversed the array from left to right Kept track of the maximum height seen so far If the current building’s height is greater than or equal to max, it receives sunlight Updated the max height accordingly This problem highlights how simple greedy logic can efficiently solve visibility-type problems. Day 65 next — consistency continues 💪 #geekstreak60 #npci #day64 #dsa #python #codingchallenge #problemSolving #learningjourney #consistency
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A client wanted to use LLMs for C# code generation, but LLMs tend to struggle with C# compared to Python or C — producing more syntax errors and language-specific logic mistakes. They asked if we could help close the gap. We combined long-context LLMs with a targeted retrieval system to give the model better grounding in C# conventions. The approach delivered a 5.7% accuracy improvement over zero-shot prompting. For more details, see our full post: https://lnkd.in/e3wrX2pn
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Conquering LeetCode one problem at a time! 🚀 Today, let's break down a classic: Problem #53 - Maximum Subarray. Understanding Kadane's Algorithm is an absolute game-changer when diving into Dynamic Programming. To make it easier to digest, I've put together this quick cheat sheet covering: ✅ The core theory behind the algorithm ✅ A step-by-step logical flow ✅ Clean code solutions in both Java and Python Whether you're prepping for upcoming interviews or just sharpening your problem-solving skills, this \bm{O(N)} time complexity approach is a must-know. Which language is your go-to for cracking DSA problems? Let me know in the comments! 👇 #VaruncodeX #LeetCode #DataStructures #Algorithms #Java #Python #SoftwareEngineering #TechCommunity #Coding #Programming
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The whole Claude code src leak is quite fun to watch, people are refactoring the entire codebase to other languages like python rust using Claude code. Many found hidden unreleased features like heartbeat similar to openclaw, so that Claude code can run 24/7
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Day 20 of #100DaysOfLearning Today, I explored Operator Overloading in Python with a real-world example Instead of using operators like + only for numbers, we can redefine their behavior for our own classes. -Example: Bank Account System I created a class where adding two accounts combines their balances: a1 + a2 → total balance This makes the code more intuitive and readable, just like real-world logic! Key Learning: __add__() lets us customize the + operator Operator overloading improves code readability It brings real-world meaning into programming concepts Small concept, but powerful in building clean and smart applications. Consistency is the real game changer On to Day 21 #Python #OOP #OperatorOverloading #CodingJourney #100DaysChallenge #LearnByDoing #SkillShikshya
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