LeetCode 219: Contains Duplicate II with HashMap

Day 20/100 – #100DaysOfCode 🚀 Solved LeetCode #448 – Find All Numbers Disappeared in an Array (Python). Today I worked on an array problem to find all the numbers in the range [1, n] that are missing from the given array. Approach: 1) Convert the array into a set for quick lookup. 2) Traverse numbers from 1 to n. 3) Check if each number exists in the set. 4) If not present, add it to the result list. 5) Return the final list of missing numbers. Time Complexity: O(n) Space Complexity: O(n) Learning how sets help in fast lookup and simplify problems 💪 #LeetCode #Python #DSA #Arrays #HashSet #ProblemSolving #100DaysOfCode

Day 24/100 – #100DaysOfCode 🚀 Solved LeetCode #747 – Largest Number At Least Twice of Others (Dominant Index) (Python). Today I practiced array traversal and comparison logic to find the dominant index in the array. Approach: 1) Find the largest element in the array and its index. 2) Traverse through the array. 3) For every other element, check if the largest is at least twice of it. 4) If any element violates this condition, return -1. 5) If all conditions are satisfied, return the index of the largest element. Time Complexity: O(n) Space Complexity: O(1) Learning how simple comparisons can solve array problems efficiently 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode

Day 31/100 – #100DaysOfCode 🚀 Solved LeetCode #1346 – Check If N and Its Double Exist (Python). Today I practiced brute-force comparison to check whether there exist two indices i and j such that arr[i] = 2 * arr[j]. Approach: 1) Use two nested loops to check all possible pairs. 2) Ensure that i ≠ j. 3) For each pair, check if arr[i] == 2 * arr[j]. 4) If condition is satisfied, return True. 5) If no such pair is found, return False. Time Complexity: O(n²) Space Complexity: O(1) Starting with brute force helps build understanding before optimization 💪 #LeetCode #Python #DSA #Arrays #BruteForce #ProblemSolving #100DaysOfCode

Sorting is the pre-step that makes fast searches possible. In Python, use sorted() when you want a new list back, and .sort() when you want to sort the original list in place. Bonus: reverse=True flips to descending order—perfect prep for binary search and many other algorithms.#Python #Sorting #Algorithms #CodingTips

Simple way to understand vector search in RAG I made a small Python example using SentenceTransformers + FAISS to understand how retrieval works in RAG. What happens here: A few documents are converted into embeddings Those embeddings are stored in FAISS A user question is also converted into an embedding FAISS finds the most similar document chunks This is the basic idea behind RAG: store meaning as vectors, then retrieve the most relevant context before generation Very small code, but it explains a very important concept. Text → Embedding → Similarity Search → Relevant Chunks That is why vector databases are so important in RAG systems. #RAG #FAISS #Embeddings #AIEngineering #Python #LLM Code source: https://lnkd.in/g-cm4BB2

Day 30/100 – #100DaysOfCode 🚀 Solved LeetCode #1299 – Replace Elements with Greatest Element on Right Side (Python). Today I practiced reverse traversal to efficiently replace each element with the greatest element on its right. Approach: 1) Initialize max_right = -1. 2) Traverse the array from right to left. 3) Store the current element in a temporary variable. 4) Replace the current element with max_right. 5) Update max_right as the maximum of max_right and the stored value. 6) Continue until the entire array is processed. Time Complexity: O(n) Space Complexity: O(1) Learning how reverse traversal can simplify problems efficiently 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode

Learn in Public — Day 15 Today I studied Selection Sort and implemented it in Python. 🔹 Key Idea: Selection Sort repeatedly finds the minimum element from the unsorted part of the array and places it at the correct position in the sorted part. 🔹 How it works: 1️⃣ Start from the first element 2️⃣ Find the smallest element in the remaining array 3️⃣ Swap it with the current position 4️⃣ Repeat for the rest of the array 🔹 Complexity: Time Complexity: O(n²) Space Complexity: O(1) (in-place sorting) Even though Selection Sort is not efficient for large datasets, it’s a great algorithm for understanding how sorting works internally. Every small step builds the foundation for mastering algorithms. #LearnInPublic #100DaysOfCode #Python #Algorithms #DataStructures

Poll Insight: Which data type does not allow duplicate values? The correct answer is Set ✅ A Set stores only unique elements, meaning duplicate values are automatically removed. That’s why sets are useful when you want to keep only distinct values in Python. 👉 Example use cases include removing duplicates from a list or storing unique items. #Python #LearnPython #CodingQuiz #ProgrammingBasics

Learn in Public — Day 14 Today I solved the Subset Array Problem using three different approaches in Python. Problem: Check whether array b is a subset of array a. Approaches I implemented: 1️⃣ Brute Force Check each element of b in a Time Complexity: O(m × n) 2️⃣ Sorting + Two Pointers Sort both arrays and compare Time Complexity: O(m log m + n log n) 3️⃣ Hash Set (Optimal) Convert array a into a set Check membership in O(1) Time Complexity: O(m + n) Key Learning: Whenever fast lookup is needed, hashing is often the best approach. #LearnInPublic #Python #DSA #CodingJourney

6 Python Libraries To Boost Your Workflow 1. Tenacity: Offers retry strategies for script resilience. 2. Polars: A fast DataFrame library for large datasets. 3. Shelve: Creates persistent, file-backed dictionaries. 4. Rich: Beautifies terminal output with tables and progress bars. 5. Pendulum: Simplifies datetime management with UTC standards. 6. Inline-Snapshot: Records and updates test values in code. Small tools like these often make a big difference—sometimes it's the unexpected library that solves your biggest headache. New to Python? Learn the basics (nl) 👉 https://lnkd.in/emBgb9gf #GeoICT #Python #GIS #SpatialData #OpenSource