Noor Ismot Ara’s Post

A small-but-mighty Python tip! I was finding the last-but-one value in an array, the runner-up score. My quick approach was : ➡️ Convert to a set to remove duplicates ➡️ Sort to get ascending order ➡️ Pick the second-to-last It worked. But the real win wasn’t just getting the answer. It was understanding why this approach works and when it doesn’t. Knowing the difference between simple data structures like sets and tuples pays dividends every day in Python. ➡️ Sets vs Tuples in the wild : 1. Set ↪️ Unordered, unique elements ↪️ Great for de-duplication and fast membership checks ↪️ Supports set algebra (union, intersection) 2. Tuple ↪️Ordered and immutable ↪️Stable position/indexing ↪️Can be used as dict keys if elements are hashable ➡️ Why that mattered here? ↪️I used a set to remove duplicates so the highest score doesn’t block the runner-up. ↪️Then I sorted the unique values to reliably grab the second-highest. This tiny choice embodies a bigger lesson : pick the structure that matches the job. #datastructures #python #datascience #coding #hackerrank #debug

Day 4 of My Python Journey — Playing with Conditional Statements! Today, I spent some time getting my hands dirty with Python’s if, elif, and else statements. It might sound simple, but understanding how to make decisions in code is the key to writing programs that actually do something meaningful. Here’s what I did today: Tried out different conditions and logical flows in Python ✅ Built a small project to see how conditional statements work in action ✅ Organized my project folder properly with all scripts and screenshots ✅ Updated my README to make it clear and easy to follow ✅ It’s exciting to see how small pieces of logic come together to create programs that can “think” a little. This is the foundation I’ll need for more complex AI and Machine Learning projects later. 📂 Project folder: Day4_Conditional_Statements/ 📌 Key files: https://lnkd.in/ebtxDiRE, README.md, screenshots 🔗 Check it out on GitHub: https://lnkd.in/eFiYbJh2 Every day I learn something new, and I’m seeing how these small steps add up. Day 4 is done — onto Day 5! #Python #CodingJourney #LearningByDoing #GitHub #DeveloperLife #AI #MachineLearning #Programming

Practicing Python by building 3 small projects I’ve been focusing on core Python concepts by shipping tiny command-line apps. Nothing fancy, just real reps. 1) Number Guessing Game Computer picks a number 1–100 → you guess. Feedback after each try: Too high / Too low / Correct. Concepts: input handling, random, loops, guardrails. 2) Rock–Paper–Scissors Play vs the computer; r/p/s inputs, q to quit. Keeps track of wins/losses/ties with clear prompts. Concepts: branching, simple state, replay loop. 3) Python Trivia Quiz 5 random questions from a small in-memory set. Case-insensitive answers, instant feedback, final score /5. Concepts: dicts, random sampling, string ops. I’ll post the GitHub link in the comments. If you have ideas for the next small project. I’m all ears. #Python #LearningInPublic #DevOps #Automation #BeginnerProjects #BuildNotWatch

🐍 Python isn’t hard — you just haven’t learned it the right way yet. Everyone says “learn Python,” but few explain how to build a solid foundation. If you want to grow from beginner ➜ advanced, here’s your blueprint 🔥 🚀 Master These 10 Python Concepts First: 1️⃣ Variables & Data Types → the building blocks. 2️⃣ Functions → reusable, clean, and modular code. 3️⃣ Libraries & Modules → stop reinventing the wheel. 4️⃣ Classes & Objects → think OOP, not just code. 5️⃣ Error Handling → your code shouldn’t crash. 6️⃣ Iterators & Generators → memory-efficient loops. 7️⃣ Map, Filter, Reduce → cleaner functional code. 8️⃣ Decorators → modify behavior without rewriting. 9️⃣ Regex → string superpowers. 🔟 Serialization (JSON) → move data between systems. 💡 Pro tip: You don’t need 100 tutorials. You need 20 concepts done deeply — and one real project to connect them all. #Python #Programming #DataEngineering #LearningInPublic #CareerGrowth #CodeNewbie

🐍 Python isn’t hard — you just haven’t learned it the right way yet. Everyone says “learn Python,” but few explain how to build a solid foundation. If you want to grow from beginner ➜ advanced, here’s your blueprint 🔥 🚀 Master These 10 Python Concepts First: 1️⃣ Variables & Data Types → the building blocks. 2️⃣ Functions → reusable, clean, and modular code. 3️⃣ Libraries & Modules → stop reinventing the wheel. 4️⃣ Classes & Objects → think OOP, not just code. 5️⃣ Error Handling → your code shouldn’t crash. 6️⃣ Iterators & Generators → memory-efficient loops. 7️⃣ Map, Filter, Reduce → cleaner functional code. 8️⃣ Decorators → modify behavior without rewriting. 9️⃣ Regex → string superpowers. 🔟 Serialization (JSON) → move data between systems. 💡 Pro tip: You don’t need 100 tutorials. You need 20 concepts done deeply — and one real project to connect them all. #Python #Programming #DataEngineering #LearningInPublic #CareerGrowth #CodeNewbie

🐍 Python isn’t hard — you just haven’t learned it the right way yet. Everyone says “learn Python,” but few explain how to build a solid foundation. If you want to grow from beginner ➜ advanced, here’s your blueprint 🔥 🚀 Master These 10 Python Concepts First: 1️⃣ Variables & Data Types → the building blocks. 2️⃣ Functions → reusable, clean, and modular code. 3️⃣ Libraries & Modules → stop reinventing the wheel. 4️⃣ Classes & Objects → think OOP, not just code. 5️⃣ Error Handling → your code shouldn’t crash. 6️⃣ Iterators & Generators → memory-efficient loops. 7️⃣ Map, Filter, Reduce → cleaner functional code. 8️⃣ Decorators → modify behavior without rewriting. 9️⃣ Regex → string superpowers. 🔟 Serialization (JSON) → move data between systems. 💡 Pro tip: You don’t need 100 tutorials. You need 20 concepts done deeply — and one real project to connect them all. #Python #Programming #DataEngineering #LearningInPublic #CareerGrowth #CodeNewbie

🐍 Day 03 of my #100DaysLogicChallenge Today’s topic: Python Keywords — Hard vs Soft Keywords 💡 Explored one of the most interesting parts of Python syntax — understanding how soft keywords differ from hard keywords, and how they make Python more flexible. 🧠 Key learnings & logic focus: Hard Keywords → fixed & reserved by Python (like if, for, class, etc.) Soft Keywords → context-dependent (like match, case, type, yield, etc.) Soft keywords don’t break identifiers and can be reused outside their specific context Used keyword and softkwlist modules to identify and analyze all soft keywords dynamically 🎯 Focus was on understanding why Python introduced soft keywords — to make new features (like structural pattern matching) backward-compatible and logically clean. Every day, a new concept — not just coding, but thinking in logic. 💭 #100DaysLogicChallenge #Python #LogicBuilding #Day03 #SoftKeywords #HardKeywords #ProblemSolving #LearnByBuilding #ProgrammingConcepts #CodingChallenge #PythonDeveloper

Day 52 of My Python Problem-Solving Journey! 🐍 Today’s #challenge was all about searching and inserting elements efficiently in a sorted #array. The task: Given a sorted array and a target value, return the index if found — otherwise, return the index where it should be inserted to maintain the sorted order. 🔹 Problem: Implement a function with O(log n) runtime complexity that determines the correct position of a target value within a sorted list. 🔹 Approach: ✅ Used try-except to handle direct search cases. ✅ Implemented conditional checks to find the correct insert position when the element isn’t present. ✅ Handled edge cases like target being smaller than the smallest element or larger than the largest. 💡 Key Learnings: Practiced binary search logic and index management in arrays. Understood how efficient algorithms can drastically improve performance. Strengthened my grasp of edge case handling in sorted data problems. 📁 Source Code: 🔗 https://lnkd.in/g2HA9WKb #Day52 #Python #100DaysOfCode #ProblemSolving #LearningInPublic #CodingChallenge #BinarySearch #AlgorithmicThinking #CodeEveryday

Day 17/120 of my Python Full Stack Journey Topic: Loop Control Statements – break, continue, pass Today I learned how to control the flow of loops using special keywords. #Python #BreakContinuePass #ProgrammingBasics #DailyLearning #FullStackDeveloperJourney #KeepGoing Pooja Chinthakayala mam Saketh Kallepu sir Uppugundla Sairam sir Codegnan #break #break statement is used to terminate the entire loop a=10 while a>1:   print(a)   a=a-1 a=10 while a>1:   a=a-1   print(a)     a=10 while a>1:   print(a)   a=a-1   if a==4:     break for i in range(10):   print(i) for i in range(10):   if i==8:     break   print(i) a="python" for i in a:   if i=="h":     break   print(i) #continue #the continue statement is used to skip the current iteration and rest of the code will continue a=20 while a>2:   print(a)   a=a-1 a=20 while a>2:   a=a-1   print(a) a=20 while a>2:   print(a)   a=a-1   if a==12:     continue a=20 while a>2:   a=a-1   if a==12:     continue   print(a) for i in range(15):   if i==9:     continue   print(i) a="code" for i in a:   if i=="o":     continue   print(i) #pass #pass statement is a null statement it does nothing but syntactically we need. a=30 while a>5:   print(a)   a=a-1   if a==15:     pass for i in range(14):   if i==10:     pass   print(i)