Generating Unique Identifiers with UUIDs in Python

🚀 Day 4 – DSA Daily Series Move Zeroes (LeetCode 283) using Python. 🧠 Problem Given an integer array nums, move all 0’s to the end of the array while maintaining the relative order of the non-zero elements. Important constraints: • The operation must be done in-place • No extra array should be created Example: Input: nums = [0,1,0,3,12] Output: [1,3,12,0,0] 💡 Approach Used the Two Pointer technique. • Maintain a pointer k to track the position for the next non-zero element • Traverse the array using index i • Whenever a non-zero element is found, swap it with the element at position k • Increment k This ensures: • Non-zero elements move to the front • Zeros automatically shift toward the end ⏱ Complexity Time Complexity: O(n) – single pass through the array Space Complexity: O(1) – in-place modification 🔎 Key Learning This problem helps strengthen: • Two Pointer pattern • In-place array manipulation • Maintaining relative order while rearranging elements Consistency is key when practicing DSA — solving one problem at a time. 🚀 #DSA #LeetCode #Python #Algorithms #ProblemSolving #CodingJourney

Python Clarity Series – Episode 11 Topic: global Keyword Confusion x = 10 def change():   x = 20 change() print(x) **Output: 10 Students expect 20. But Python doesn’t work like that. Inside a function, variables are LOCAL by default. To modify global variable: x = 10 def change():   global x   x = 20 change() print(x) **Output: 20 **Clarity Rule: No global → Local copy With global → Modify original Exams love scope-based questions. Have you ever misunderstood variable scope? #PythonClarity #CBSEClass12 #FunctionConcepts

💡 Do you really understand what *args does in Python? Many developers use ( *args ) without thinking about what’s actually happening under the hood. 🔹 args is just a variable name (short for arguments) 🔹 The real magic is in the * When you write: def func(*args): You're telling Python: “Collect any number of positional arguments and pack them into one variable.” 📦 The result? All passed values are stored inside a tuple. Example: func(1, 2, 3) Internally becomes args = (1, 2, 3) 📌 * in function definition → Packing 📌 * in function call → Unpacking Small detail. Big difference in understanding Python deeply. #Python #Programming #AI #DataAnalysis #SoftwareEngineering #Backend #Learning #Instant

Weekly Challenge 4: Binary Search (Iterative). Why search harder when you can search smarter? Use Binary Search. Imagine looking for a word in a dictionary. Do you read every page from the beginning? No. You open it in the middle and decide: "Left or Right?". That is the essence of Binary Search, and it's the focus of my coding challenge for Week 4. The Implementation: I wrote a Python script (using NumPy) that generates a random environment to test the algorithm. Key Takeaway: While a simple loop (Linear Search) checks elements one by one ($O(n)$), Binary Search cuts the problem in half with every step ($O(\log n)$). Check out the trace in the console output below to see how few attempts it takes to find the target! 👇 📂 Full code on GitHub: https://lnkd.in/ezPaaiDM #Python #BinarySearch #Algorithms #CodingChallenge #DataStructures #Engineering

LeetCode Problem 83: Given the head of a sorted linked list, delete all duplicates such that each element appears only once. Return the linked list sorted as well. The below implementation in Python successfully resolves this in time complexity of O(n) where n is length of the list with constant space complexity. The approach is simple, handle the base case first like list having 0 or 1 number of nodes and then write the logic of handling lists of length greater than one. Maintain two pointers, one to keep track of present node and other to keep track of previous node. Check if the value of both nodes match or not, if match update the pointing of previous node, point its next to the present.next. #LeetCode #LinkedList #Python #CompetitiveProgramming #Algorithms #DataStructures #ProblemSolving

LeetCode #217 – Contains Duplicate | Python Solution Iterating through nums, each element is checked against a HashSet — if it already exists, return True immediately; otherwise, insert it and continue. No nested loops, no redundant comparisons — just a single pass with instant lookups. 💡 Key Takeaway: Trading space for time is a core algorithmic principle. A set eliminates the need for brute-force O(n²) comparisons by giving constant-time lookups. ⏱ Time: O(n)  💾 Space: O(n) #LeetCode #DataStructures #Python #HashSet #CodingInterview #ProblemSolving #SoftwareEngineering

Binary search is a pretty simple algorithm, but it can sometimes cause problems, especially with off-by-one index errors. If possible, we should use the language's built-in methods, for example, `bisect` in Python. However, in some cases, we have to implement it ourselves. While an iterative approach is pretty straightforward, sometimes switching to recursion would produce simpler code. Thus, if we already use additional space, and the call stack won't affect the space complexity, it's reasonable to use recursion. The post: https://lnkd.in/dTttqaCW The problem: https://lnkd.in/dTCzj5Qc #LeetCode #DSATips #DSA #ThinkDSA #ProblemSolving

Day 25 – divmod() print(divmod(10, 3)) Use: Quotient & remainder Content: Used divmod() to get quotient and remainder. Useful in math logic. #Python generate like a cartoon style image Image created Generated image Generated image Generated image Share Gulive description to post in. Linked in Here’s a clean LinkedIn-ready description for your post: 🚀 Day 25 of #30DaysOfCode – Learning divmod() in Python Today I explored the divmod() function in Python. print(divmod(10, 3)) 🔹 divmod() returns both the quotient and remainder in a single step. 🔹 Output: (3, 1) 🔹 It combines the functionality of // (floor division) and % (modulus). This function is especially useful in mathematical logic, time calculations, and problem-solving scenarios where both values are needed together. Small functions, big impact! 💡 #Python #PythonBasics #CodingJourney #LearnToCode #Programming #30DaysOfCode

🚀 Day-38 of #100DaysOfCode 🐍 Python Sorting Algorithm Challenge Today I implemented Selection Sort from scratch to sort a list of numbers provided by the user—without using any built-in sorting methods. 🔹 What is Selection Sort? Selection Sort repeatedly selects the smallest element from the unsorted portion of the list and places it at the correct position. 🔹 Concepts Practiced: ✔ Nested loops ✔ Minimum element selection logic ✔ Index tracking ✔ In-place swapping 🔹 Approach: Iterate through the list Find the minimum element in the remaining unsorted part Swap it with the current index Repeat until the list is fully sorted 🔹 Key Insight: Selection Sort has a time complexity of O(n²), making it useful for understanding sorting fundamentals rather than large datasets. Working through such algorithms builds strong foundational knowledge of sorting and array manipulation 💡 #Python #SelectionSort #SortingAlgorithms #CorePython #100DaysOfCode #Day38 #LearnPython #CodingPractice #PythonDeveloper

🚀 Day-39 of #100DaysOfCode 🐍 Python Sorting Algorithm Challenge Today I implemented Insertion Sort from scratch to sort a list of numbers entered by the user—without using any built-in sorting functions. 🔹 What is Insertion Sort? Insertion Sort builds the sorted list one element at a time, similar to how we sort playing cards in our hands. 🔹 Concepts Practiced: ✔ Nested loops ✔ Element shifting logic ✔ In-place sorting ✔ Understanding algorithm flow 🔹 Approach: Start from the second element Compare it with the elements before it Shift larger elements one position ahead Insert the element at its correct position 🔹 Key Insight: Insertion Sort performs efficiently on small or nearly sorted datasets and helps understand how sorting works internally. Working through such algorithms strengthens core logic, array manipulation, and problem-solving skills 💡 #Python #InsertionSort #SortingAlgorithms #CorePython #100DaysOfCode #Day39 #LearnPython #CodingPractice #PythonDeveloper