Implement Trie (Prefix Tree) for Efficient String Search

✅ Day 43 of 100 Days LeetCode Challenge Problem: 🔹 #684 – Redundant Connection 🔗 https://lnkd.in/gWtKJ-FA Learning Journey: 🔹 Today’s problem focused on detecting an extra edge that creates a cycle in an undirected graph. 🔹 I used the Union-Find (Disjoint Set Union) data structure to track connected components. 🔹 For each edge, I checked whether both nodes already belong to the same set. 🔹 If they do, adding that edge forms a cycle, making it the redundant connection. Concepts Used: 🔹 Union-Find (Disjoint Set) 🔹 Path Compression 🔹 Graph Cycle Detection 🔹 Connected Components Key Insight: 🔹 Union-Find provides an efficient way to detect cycles during edge additions. 🔹 Path compression optimizes repeated parent lookups. 🔹 Incrementally building connectivity helps quickly identify redundant edges. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 39 of 100 Days LeetCode Challenge Problem: 🔹 #114 – Flatten Binary Tree to Linked List 🔗 https://lnkd.in/g6xn2K3g Learning Journey: 🔹 Today’s problem focused on transforming a binary tree into a flattened linked list in-place. 🔹 I used an iterative approach, modifying pointers while traversing the tree. 🔹 For each node with a left subtree, I found the rightmost node of that subtree and connected it to the current node’s right subtree. 🔹 Then, I moved the left subtree to the right and continued traversal. Concepts Used: 🔹 Binary Trees 🔹 Tree Traversal 🔹 Pointer Manipulation 🔹 In-place Modification Key Insight: 🔹 Tree restructuring problems often rely on careful pointer adjustments. 🔹 Finding the predecessor (rightmost node of left subtree) helps preserve traversal order. 🔹 Iterative solutions can avoid recursion and reduce extra space usage. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

DSA Daily — Hashing Pattern LeetCode 349: Intersection of Two Arrays Day 14 of staying consistent with problem solving Today’s problem was a simple but important example of how sets simplify array problems when uniqueness is a requirement. We’re given two arrays and asked to return their intersection — with no duplicate elements in the result. This problem clearly signals the use of hashing. Key observations: - The result must contain unique elements only - Order does not matter - Fast lookup is more important than maintaining positions Core idea: - Convert one array into a set to remove duplicates and enable O(1) lookup - Traverse the second array - If an element exists in the set, add it to the result set - Using a set for the result automatically ensures uniqueness. Complexity: Time: O(n + m) Space: O(n + m) (sets for lookup and result) Sets are especially useful for intersection-type problems on arrays. This problem fits well with earlier hashing-based questions and reinforces how choosing the right data structure can make solutions both cleaner and more efficient. On to the next one 🚀 #DSADaily #Hashing #LeetCode #ProblemSolving #Python

✅ Day 28 of 100 Days LeetCode Challenge Problem: 🔹 #133 – Clone Graph 🔗 https://lnkd.in/gsciP4qv Learning Journey: 🔹 Today’s problem focused on creating a deep copy of a connected graph. 🔹 I used Depth-First Search (DFS) to traverse the graph and clone each node. 🔹 A hashmap stores the mapping between original nodes and their cloned counterparts to avoid duplicate copies. 🔹 This approach also handles cycles gracefully by returning already-cloned nodes when revisited. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Graph Traversal 🔹 Hash Map 🔹 Deep Copy Key Insight: 🔹 Graph cloning requires tracking visited nodes to prevent infinite loops. 🔹 DFS provides a clean recursive way to clone nodes and their neighbors. 🔹 Maintaining a reference map is essential for handling cyclic graphs correctly. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 22 of 100 Days LeetCode Challenge Problem: 🔹 #17 – Letter Combinations of a Phone Number 🔗 https://lnkd.in/gmUqqEEf Learning Journey: 🔹 Today’s problem focused on generating all possible letter combinations from a digit string based on a phone keypad mapping. 🔹 I used a mapping of digits to characters and built combinations iteratively by merging results from previous digits. 🔹 Each step combines the existing set of strings with the characters of the next digit, gradually expanding the result space. 🔹 This approach avoids deep recursion and clearly demonstrates how combinatorial growth works step by step. Concepts Used: 🔹 Hash Maps 🔹 Iterative Combination Building 🔹 String Manipulation 🔹 Cartesian Product Logic Key Insight: 🔹 Phone keypad problems are classic examples of combinatorial explosion. 🔹 Breaking the problem into incremental combination steps makes it easier to reason about and implement. 🔹 Understanding how intermediate results grow is crucial for mastering combination-based problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

🎉 New DPK Release: Version 1.1.7 We’re excited to share the latest release of Data Prep Kit, packed with fresh transform capabilities, performance boosts, and expanded compatibility. Here’s a look at what’s new in v1.1.7: ⚙️ Enhancements Python 3.13 Compatibility - Expanded version compatibility to support Python 3.13 Faster Installation with uv -Migrated the repo to use uv, significantly speeding up environment setup and dependency installation. Rich Logging - A new Rich-based log handler offers cleaner, colorized, and more structured console output. 🔁 Transform Updates Folder-to-Parquet Transform - A brand new transform that converts an entire folder of files into a unified Parquet dataset—making it easier to batch-process large document collections. Text Encoder Upgrade - The Text Encoder now uses LanceDB for improved vector storage and retrieval performance. Spark Support for docling2parquet and doc_quality - Both doc_quality and docling2parquet transforms now support Spark execution, enabling scalable distributed processing. 📄 Explore the full release notes: 👉 https://lnkd.in/eZufxzv4 ⭐ Support the project by starring the repo and following our updates! #DataPrepKit #OpenSource #Python #MLOps #RAG #LLM #DataEngineering #AItools

✅ Day 44 of 100 Days LeetCode Challenge Problem: 🔹 #3713 – Longest Balanced Substring 🔗 https://lnkd.in/gfryNgam Learning Journey: 🔹 Today’s problem focused on finding the longest substring where all characters appear with equal frequency. 🔹 I explored all possible substrings by fixing a starting index and expanding the window step by step. 🔹 A frequency array helped track character counts along with the number of distinct characters and maximum frequency. 🔹 By validating whether all active characters share the same count, I identified balanced substrings efficiently. Concepts Used: 🔹 String Processing 🔹 Frequency Counting 🔹 Nested Traversal 🔹 Sliding Window Concepts Key Insight: 🔹 Balanced substring problems rely on maintaining strict frequency conditions. 🔹 Tracking distinct characters and maximum frequency simplifies validation logic. 🔹 Smart bookkeeping can make brute-force approaches effective for constrained problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 38 of 100 Days LeetCode Challenge Problem: 🔹 #323 – Number of Connected Components in an Undirected Graph 🔗 https://lnkd.in/gRVWsWgZ Learning Journey: 🔹 Today’s problem focused on counting connected components in an undirected graph. 🔹 I represented the graph using an adjacency list built from the edge list. 🔹 Using Depth-First Search (DFS), I explored all nodes reachable from a starting node. 🔹 Each new DFS traversal from an unvisited node indicates a new connected component. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Graph Representation (Adjacency List) 🔹 Connected Components 🔹 Graph Traversal Key Insight: 🔹 Graph problems often reduce to exploring connectivity between nodes. 🔹 Tracking visited nodes prevents redundant traversals. 🔹 Iterative DFS using a stack provides a clean and efficient solution. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

The DNA of Data: Mastering Logic Before Tools 🧠🐍 My transition into Data Analytics at Datamatics has begun with a deep dive into the building blocks of Python. Before handling large-scale databases, I am focusing on the "micro-logic" of programming. This week was all about translating mathematical concepts into clean, executable code: Geometry in Code: Moving beyond manual calculations to program formulas for a circle’s area and perimeter. Number Deconstruction: Learning to "break into" numbers. I’ve been practicing how to isolate the first, middle, and last digits of 4-digit numbers using Python operators. The Power of Modulo & Floor Division: Mastering % and // to find divisors and remainders The essential logic for identifying patterns in any sequence of numbers. I am building the mental muscle required to manipulate data at its most basic level. Understanding these foundational steps is making the transition to Python feel natural and structured. 🌱 #PythonBasics #DataAnalytics #Datamatics #CodingJourney #LogicFirst #LearningInPublic #AbinithiSrinivasan

🚀 #100DaysOfLeetCode – Day 19 ✅ Problem: LeetCode 50 – Pow(x, n) Today’s challenge focused on efficiently computing xⁿ (power function), especially when n is very large or negative. A naive multiplication approach would be too slow, so the key idea is using Binary Exponentiation (Fast Power) to reduce the time complexity. 💡 Key Learning: Break the exponent into halves repeatedly. If n is even → (x²)^(n/2) If n is odd → x × (x²)^(n/2) Handle negative powers by computing the reciprocal. ⏱️ Time Complexity: O(log n) 📦 Space Complexity: O(1) This problem reinforced how mathematical observations can dramatically improve performance compared to brute-force solutions. #LeetCode #DSA #ProblemSolving #CodingJourney #Python #BinaryExponentiation