Devi Matta’s Post

CPython Unveils Chained Assignment Mechanics in Python Bytecode Execution 📌 Chained assignments in Python don’t create separate objects-they share the same underlying instance, a bytecode-level quirk that can silently break your code. A deep dive into CPython’s execution reveals how a = b = [] uses COPY and STORE_FAST to assign the same list to multiple variables, exposing a common pitfall for developers working with mutable data. 🔗 Read more: https://lnkd.in/dUfiAJ44 #Cpython #Pythonbytecode #Chainedassignment #Interpreterexecution #Variablebinding

I recently implemented the K-Medoids clustering algorithm from scratch in Python and visualized the clusters using graphs to understand how the algorithm groups data points. #MachineLearning #PythonProjects https://lnkd.in/gczybNGr

LeetCode #102 – Binary Tree Level Order Traversal | Python Implementation I implemented an iterative BFS approach using a queue to collect nodes level by level. Core Insight: The len(q) snapshot before the inner loop prevents mixing levels. New children added during iteration don't affect the current level's processing count, ensuring clean level separation. Time: O(n) | Space: O(w) where w = maximum tree width #LeetCode #DataStructures #Python #BinaryTree #BFS #LevelOrderTraversal #CodingInterview #SoftwareEngineering

LeetCode #104 – Maximum Depth of Binary Tree | Python Implementation I implemented a recursive DFS approach that calculates tree depth by taking the maximum of left and right subtree depths plus one for the current node. Core Insight: Depth calculation decomposes naturally into subproblems. Each node's depth is determined by its deepest child, making recursion the cleanest solution with minimal code. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering

🚀 Day 25 — DSA + Python Today I practiced Array Rotation problems. ✅ Learned: Left rotation Right rotation Rotation by K positions 💡 Understood the logic of shifting elements and how to think about better approaches instead of brute force. Practicing arrays is helping me build stronger problem-solving skills in DSA. #DSA #Python #CodingJourney #100DaysOfCode

Running concurrent workloads efficiently is critical in modern backend systems. I benchmarked Sync vs Threading vs Asyncio in Python to understand performance trade-offs and practical use cases. #python #Asyncio #Thread #Sync

Using Python, we create a histogram of the TDS distribution in each formation based on well data in area "X." All histograms are skewed. The strongest skewed is for the Hensell Sand formation. Data source: Alysa Suydam #python #datascience #machinelearning #geoscientist #geoscience #tds 

How many NaNs in a #Python #Pandas data frame? 1. Use isna, returning a data frame of booleans 2. Use sum, returning the number of NaNs in each column 3. Use sum again, adding those numbers df.isna().sum().sum()

#Pythoncoding 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻: 𝗪𝗿𝗶𝘁𝗲 𝗮 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗺𝗮𝗻𝘂𝗮𝗹𝗹𝘆 𝗿𝗲𝘃𝗲𝗿𝘀𝗲 𝗮 𝗴𝗶𝘃𝗲𝗻 𝗹𝗶𝘀𝘁 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗯𝘂𝗶𝗹𝘁-𝗶𝗻 𝗿𝗲𝘃𝗲𝗿𝘀𝗲() 𝗺𝗲𝘁𝗵𝗼𝗱 𝗼𝗿 𝘀𝗹𝗶𝗰𝗶𝗻𝗴 ([::-𝟭]). 𝗖𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀: -Do not use reverse() or [::-1]. -The function should work for both numbers and strings. -The input list may contain duplicates and should maintain their order in reverse. -The function should return a new reversed list (not modify the original list). #Python #PythonDeveloper #Coding #100DaysOfCode #LearnPython #DataScience #MachineLearning

LeetCode #98 – Validate Binary Search Tree | Python Implementation I implemented a recursive DFS approach with boundary tracking to validate BST properties. Core Insight: BST validation requires tracking allowable ranges, not just comparing immediate children. Each recursive call narrows the valid interval, ensuring global ordering throughout the entire subtree. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinarySearchTree #Recursion #DFS #CodingInterview #SoftwareEngineering