Learned recursion for problem-solving in Python today

💻 Day 5 of 365 – DSA in Python 🐍 Today’s focus was on Recursion 🌀 📚 What I learned: • The concept of a function calling itself • Understanding base case and recursive case • Tracing recursive calls using examples like factorial and Fibonacci sequence 💡 Key takeaway: Recursion simplifies complex problems by breaking them down into smaller subproblems — but it’s essential to handle base conditions to avoid infinite loops! Feeling more confident with each day of DSA learning 🚀 #Day5 #365DaysOfDSA #Python #Recursion #Algorithms #LearningInPublic #KeepCoding #ProblemSolving

🚀 Problem Solving Day 51: Mastering Recursion! Today, I explored recursion to reverse strings and lists in Python. Recursion allows a function to call itself, breaking complex problems into smaller, manageable parts. Example Inputs & Outputs: String: "hello" → "olleh" String: "recursion" → "noisrucer" List: [1, 2, 3, 4, 5, 6, 7] → [7, 6, 5, 4, 3, 2, 1] Key Learnings: ✅ Recursion simplifies repetitive tasks elegantly. ✅ Helps in understanding problem decomposition. ✅ Strengthens logical thinking and Python fundamentals. #Python #Recursion #ProblemSolving #Coding #DataStructures #100DaysOfCode #PythonProgramming #LogicBuilding

Many ask: Can non-programmers learn Agentic AI? Answer: Yes — but you need Python basics. The good news: coding in Agentic AI is simpler than you think. 🎁 Free roadmap 👉 https://zurl.co/84y2e #AgenticAI #Python #CareerGrowth

Many ask: Can non-programmers learn Agentic AI? Answer: Yes — but you need Python basics. The good news: coding in Agentic AI is simpler than you think. 🎁 Free roadmap 👉 https://zurl.co/84y2e #AgenticAI #Python #CareerGrowth

💡 Struggling to understand how Async in Python is different from threading or multiprocessing? Async isn’t about raw speed - it is about smarter waiting. When used right, it makes your apps more responsive, scalable, and efficient. Start coding smarter, not harder—your career in data, AI, or automation begins here. 👉 Interest? Here is our Python Masterclass : https://lnkd.in/eMPRNGms 📲 Join the free python newsletter: https://lnkd.in/eWG4WyPZ #Pythoncourse #programming #pythonprogramming #pythoncourse #pythondev #CodingJourney #Zerotoknowing

Do you ever wonder 𝐰𝐡𝐲 𝐏𝐲𝐭𝐡𝐨𝐧 𝐬𝐥𝐢𝐜𝐢𝐧𝐠 𝐝𝐨𝐞𝐬 𝐧𝐨𝐭 𝐢𝐧𝐜𝐥𝐮𝐝𝐞 𝐭𝐡𝐞 𝐥𝐚𝐬𝐭 𝐞𝐥𝐞𝐦𝐞𝐧𝐭? It’s because Python uses a 𝒉𝒂𝒍𝒇-𝒐𝒑𝒆𝒏 𝒊𝒏𝒕𝒆𝒓𝒗𝒂𝒍. In math, a closed interval like [1, 10] means 1 ≤ 𝒙 ≤ 10, including both ends. A half-open interval like [1, 10) means 1 ≤ 𝒙 < 10, including the start but stopping before the end. In Python, numbers[1:4] works the same way. It includes indexes 1, 2, 3 but not 4. This makes counting easy (end - start = length) and keeps slices clean when joining or looping. Next time you slice, remember you are following the same rule mathematicians use.📐 #Python #MathsBehindCode

👨💻 Day 31 of my Python learning journey Today, I revisited Polymorphism - one of the most flexible and powerful principles in Object-Oriented Programming. 🔍 What I learned: ✅ Polymorphism means “many forms” - the same function or method can behave differently depending on the object it is acting upon. ✅ It allows one interface to be used for different data types or classes. ✅ In Python, it makes code more dynamic, scalable, and easy to maintain. 💡 Real-World Analogy: Think of the word “run”: A person can run 🏃♂️ A car engine can run 🚗 A program can run 💻 The same action, but different meanings - that’s Polymorphism! ⚙️ Key Takeaways: Promotes flexibility and reusability. Makes systems adaptable to future changes. Reduces code duplication and increases maintainability. 🚀 Learning Insight: Polymorphism isn’t just about shared methods - it’s about designing code that can adapt without breaking. #Python #Day31 #OOP #Polymorphism #LearningPython #AI #ML #FresherInTech #CodingJourney #LinkedInLearning #TechWithSuhit #100DaysOfCode

🧠 𝗧𝗼𝗱𝗮𝘆’𝘀 𝗣𝘆𝘁𝗵𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗦𝗰𝗼𝗽𝗲 𝘄𝗶𝘁𝗵 𝗟𝗘𝗚𝗕 I spent some time exploring how Python decides which variable to use when the same name appears in different places. This is all about the 𝗟𝗘𝗚𝗕 𝗿𝘂𝗹𝗲 — Local → Enclosing → Global → Built-in. Through my practice, I explored variables at different levels of scope and learned how Python searches from the innermost scope outward. Using techniques like globals()['x'] helped me clearly see how global variables can be accessed even inside nested functions. Small exercises like this sharpen my understanding of Python’s core behavior and make me more confident in writing clean, predictable code. #Python #coding #CodeLearning #DeveloperJourney #AIEngineer #CreativeAlchemist

⚡️ Cracked “Pow(x, n)” in Python: Fast Power FTW! ⚡️ Learned to solve the classic exponentiation problem using binary exponentiation (a.k.a. fast power). The key ideas: Handle negative exponents via reciprocal Square-and-multiply using the exponent’s bits Achieves O(log n) time and O(1) space for scalable performance Loved how math meets engineering here—turning repeated multiplication into a sleek, bit-wise strategy. On to more math-heavy patterns next! #LeetCode #PowXN #BinaryExponentiation #Python #DSA #Algorithms #CodingChallenge #TimeComplexity #InterviewPrep #ProblemSolving