Searching & Sorting Algorithms power almost everything we build - from search features to ranked lists. I just published a complete, practical guide covering: • Linear & Binary Search • Bubble, Merge, Quick Sort • Big-O explained simply • Real-world use cases • Code in Python, JavaScript, Java, C++ & C If you’re preparing for interviews or strengthening your DSA foundation, this will help. 👉 Read here: https://lnkd.in/g2kJhgKc #DSA #Algorithms #Programming #SoftwareDevelopment #Python #JavaScript #Coding
Mastering Search & Sorting Algorithms with Python, JavaScript, Java, C++, C
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🚀 DSA Consistency – Day 2 Today I solved the Binary Watch problem on LeetCode. The idea was simple but interesting — iterate through all valid hours (0–11) and minutes (0–59), count the number of set bits in their binary representation, and collect the times where the total equals the given number of LEDs turned on. This problem reinforced: * Bit manipulation fundamentals * Clean iteration over constrained ranges * Proper formatting of edge cases (like leading zeros in minutes) Sometimes the goal isn’t solving something extremely complex — it’s about showing up daily and sharpening fundamentals. Consistency > Intensity. Here’s my solution (Python, Java & C++): 🔗 https://lnkd.in/dArp73Cd #DSA #LeetCode #Consistency #ProblemSolving #CodingJourney #SoftwareEngineering #BitManipulation
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Just published a detailed solution breakdown on LeetCode I recently wrote an explanation for the “Prime Number of Set Bits” problem, covering: • Intuition and brute-force approach • Bit counting optimization • Bitmask compression trick (storing prime checks inside a single integer) • Multi-language implementations (C++, Java, Python, C#, C) One part I enjoyed exploring was replacing repeated prime checks with a compact bitmask: (1 << bitCount) & 665772 Small problem — but great practice in thinking about constraints and constant-time optimizations. Here’s the full explanation: https://lnkd.in/gAjX6MMt Always trying to get better at writing clean explanations, not just solving problems. #Algorithms #DataStructures #BitManipulation #LeetCode #ProblemSolving
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Day 54 of 365 Days of code 1) Capacity to Ship Packages Within D Days Approach: Binary search 1)set low = max(weights) 2) high= low*sum(weights) 3) perform the below steps until low<=high condition fails i) mid=low+(high-low)//2;res=0 ii) set w = mid and initialize day=1 iii) iterate through the loop and perform the stuff i put in screenshot (ahh life hurts :") ) iv) if the day <= days: set res=mid ; set high=mid-1 v) else low=mid+1 4) return res #365daysOfCode #NeetCode #leetcode #DSA #python #LeetCode #ProblemSolving #Algorithms #365dayschallenge
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WHAT IS THE ARRAY SIZE? I have seen a lot of confusion in the poll reactions about Array size, so let me clarify. ✅ Fixed (Correct) Array size is usually fixed at the time of creation and cannot be changed later. This is the standard definition of arrays in Data Structures. ⚠️ Dynamic (Partly correct idea) Some languages like Python or Java allow arrays (lists/ArrayList) to grow automatically, but internally they are resized arrays, not true dynamic arrays. ❌ Infinite (Incorrect) Arrays cannot store unlimited elements because memory in a computer is always limited. ❌ Random (Incorrect) Array size is not random; it is clearly defined when the array is created. So in DSA theory, Array size is Fixed. #DSA #Arrays #LearnCoding #ProgrammingBasics #Students
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The simplest and coolest explanation for pure functions: Pure functions minds it's business>>>>"Just give me the data, I will not change you😅, I will just make a copy of it and hands off"... In python: global_list = [1, 2, 3, 4] def add_to_list(lst, item): function_list = lst.copy() function_list.append(item) return function_list print(add_to_list(global_list, 5)) ##[1, 2, 3, 4, 5] print(global_list) ## REMAINS THE SAME #softwaredeveloper #reactjs #purefunctions #python #programming #software #def #components
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🔥 Day 49 of #75DaysOfDSA - Today’s Focus: -> Topic: Dynamic Programming -> Language: Python - What I Worked On Today: -> Solved 1 DSA medium problems - Decode Ways - Key Learnings / Takeaways: -> Uses DP where dp[i] represents the number of ways to decode the substring up to index i. At each step, consider both single-digit and two-digit valid decodings and build the solution bottom-up. -> Time Complexity : O(n) - The string is traversed once, and each index performs constant-time checks. -> Space Complexity : O(n) - An auxiliary DP array of size n + 1 is used to store decoding counts. 📈 Progress So Far: -> Day: 49/75 -> Consistency > Motivation On to Day 50 🚀 #75DaysOfDSAChallenge #Day49 #DSA #Python #ProblemSolving #LearnInPublic #SoftwareEngineering #CareerGrowth #TechJourney #HR
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Understanding C++ pointers isn’t about syntax — it’s about understanding memory. I’ve written a Medium article explaining: • How stack and heap memory differ • What a pointer represents at the hardware level • How dynamic memory allocation works • Why improper ownership leads to leaks and undefined behavior • When to use smart pointers and why These concepts are foundational for systems programming, performance engineering, and quant infrastructure. The article explores C, C++ and a bit of Python. If you’re strengthening your C++ fundamentals, I’d appreciate your thoughts. Link below. #Cpp #C #Python #pointers #malloc
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The programming world just shifted-and you need to see this. Python still dominates at 21.81%, but it's bleeding market share. C# posted the biggest gain (+2.71%). R and Perl are staging comebacks. Java, C++, and JavaScript all declined. The era of one language ruling everything? It's over. Specialists are challenging generalists. Evolution is beating hype. The question isn't what's popular-it's what's next for YOUR career. Swipe to see the full breakdown 👉 #Programming #TechTrends #SoftwareDevelopment #Python #CSharp #TechCareers #AI #CareerGrowth #Technology #Innovation #LearnToCode
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Python is the New Excel, But C++ is the New Assembly "Python is unbeatable for prototyping. But production HFT is still a C++ game. If your tick-to-trade latency is above 500 nanoseconds, you're losing. Understanding cache locality, branch prediction, and avoiding virtual functions in the hot path separates the 'quants' from the 'quant developers'. Can you explain why your strategy underperforms due to garbage collection pauses? No? Time to learn SIMD instructions. #Quant #python #C++ #HFT #QUANTDEVELOPER #RISK
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Browsers have evolved into immensely powerful computational environments and are quietly becoming the default layer for modern engineering and R&D. Without leaving the browser you can now initialize a Python environment, select libraries (numpy, matplotlib, scisuit), and run the exact deterministic code generated by the platform. From Web UI → to Python code → to exploration #engineering #web #statistics #dataanalysis #python #reproducibility
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