Valid Parentheses: HashMap + Stack for Clean Bracket Matching Nested if-else chains for each bracket type create messy code. HashMap maps closing brackets to required opening brackets. Stack tracks unmatched openers. On closing bracket, verify stack top matches via HashMap — extensible, clean solution. HashMap Simplification: Replacing conditional chains with HashMap lookup makes code extensible — new bracket types need one dict entry, not multiple conditionals. Generalizes to any multi-case validation. Time: O(n) | Space: O(n) #Stack #HashMap #BracketMatching #CodeCleanup #Python #AlgorithmDesign #SoftwareEngineering
Clean Bracket Matching with HashMap and Stack
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🚀 Day 32 – LeetCode Journey Today’s problem: Reverse String II ✔️ Implemented in-place string reversal using two pointers ✔️ Efficiently processed the string in chunks of 2k ✔️ Optimized approach with minimal extra space 💡 Key Insight: Instead of reversing the entire string, we only reverse the first k characters in every 2k block. Using the two-pointer technique makes this both simple and efficient. This problem strengthened my understanding of string manipulation, indexing, and in-place operations. Step by step, becoming a better problem solver 🔥💪 #LeetCode #Day32 #Strings #TwoPointers #Python #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 48 – LeetCode Journey Today’s challenge: Substring with Concatenation of All Words ✔️ Solved using sliding window + hashmap ✔️ Processed string in fixed-length chunks ✔️ Tracked word frequency efficiently 💡 Key Insight: Instead of checking every substring blindly, splitting the string into word-sized pieces and using a hashmap helps validate matches efficiently. Sliding window keeps the solution optimized. This problem was a great exercise in string manipulation, hashing, and window techniques 🧠 Consistency is the real game changer 🚀 #LeetCode #Day48 #SlidingWindow #HashMap #Strings #Python #ProblemSolving #CodingJourney #100DaysOfCode https://lnkd.in/gxf4RBT6
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🚀 Day 37 – LeetCode Journey Today’s problem: Container With Most Water ✔️ Solved using two-pointer technique ✔️ Optimized from brute force to O(n) time complexity ✔️ Efficiently calculated maximum area 💡 Key Insight: Instead of checking all pairs, moving the pointer with the smaller height helps in maximizing the area efficiently. This reduces unnecessary comparisons and improves performance significantly. This problem strengthened my understanding of greedy approach and two-pointer strategies. Consistency + Smart Thinking = Growth 🔥💪 #LeetCode #Day37 #TwoPointers #Greedy #Python #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 41 – LeetCode Journey Today’s problem: Add Binary ✔️ Implemented binary addition manually ✔️ Handled carry propagation efficiently ✔️ Worked with string manipulation and indexing 💡 Key Insight: Binary addition follows the same rules as decimal addition, but with base 2. Managing the carry correctly is the key to building the final result. This problem improved my understanding of bit-level operations and string handling. Step by step, mastering the fundamentals 🔥💪 #LeetCode #Day41 #Binary #Strings #Python #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 33 – LeetCode Journey Today’s problem: Move Zeroes ✔️ Used two-pointer technique for in-place modification ✔️ Moved all non-zero elements forward efficiently ✔️ Maintained relative order of elements 💡 Key Insight: By keeping a pointer for non-zero elements, we can swap values in a single pass and avoid extra space — making the solution both clean and optimal. This problem improved my understanding of array manipulation and in-place algorithms. Consistency is building confidence day by day 💪🔥 #LeetCode #Day33 #Arrays #TwoPointers #Python #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 62 of #100DaysOfCode Solved “Remove Nth Node From End of List” 🔗 💡 Today’s focus: Two Pointer Technique (Fast & Slow pointers) Instead of calculating length, I used an efficient one-pass approach to remove the target node. 🧠 Key Learnings: Dummy node helps handle edge cases (like removing head) Fast pointer moves n steps ahead Then move both pointers until fast reaches the end Slow pointer lands just before the node to delete ⚡ Clean, efficient & optimal solution (O(n) time, O(1) space) Consistency is starting to feel powerful now 💪 #DSA #LeetCode #CodingJourney #LinkedInLearning #100DaysOfCode #Day62 #Python #ProblemSolving
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🚀 Day 40 – LeetCode Journey Today’s problem: Linked List Cycle ✔️ Solved using Floyd’s Cycle Detection Algorithm (Tortoise & Hare) ✔️ Used two pointers (slow & fast) ✔️ Efficient cycle detection without extra space 💡 Key Insight: If a cycle exists, the fast pointer will eventually meet the slow pointer. This approach avoids using extra memory and works in O(n) time. This problem strengthened my understanding of linked lists and pointer techniques. 40 days of consistency — getting stronger every day 💪🔥 #LeetCode #Day40 #LinkedList #TwoPointers #Python #ProblemSolving #CodingJourney #100DaysOfCode
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Did you dig our latest work on enzyme inmobilization with Fernando López Gallego? We created workflows for you! Now available as a Python package and in Collab, from the great Juan C. Jiménez García https://lnkd.in/ep9QdBEa https://lnkd.in/ec2h9-6x
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Day 37 & 38 complete! 🚀 Finding Minimum and Maximum in an Array: Practiced single-pass iterations to identify the extreme values in a dataset, focusing on minimizing comparisons. Count Each Vowel in a String: Used a dictionary to map and count the frequency of vowels. This was great practice for handling case sensitivity and string traversal. First Unique Character in a String: Implemented a two-pass approach—first using a Hash Map to store character frequencies, and then iterating to find the first character with a count of one. Sometimes going back to the basics is the best way to ensure your logic is bulletproof! 📈 #100DaysOfCode #Python #DSA #LeetCode #ProblemSolving
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Find Minimum in Rotated Sorted Array: Binary Search with Rotation Point Rotation breaks global sorting but one half is always properly sorted. Compare mid with right endpoint — if mid > right, minimum is in right half (rotation point there). Otherwise, minimum is in left half or at mid. Track minimum seen while narrowing. Rotation Point Detection: Comparing mid with endpoint (not left neighbor) determines which half contains rotation. This preserved partial ordering enables O(log n) despite global disruption. Time: O(log n) | Space: O(1) #BinarySearch #RotatedArray #MinimumFinding #RotationPoint #Python #AlgorithmDesign #SoftwareEngineering
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