Mastering Python with Repetition and Practice

Day 5 of #30DaysOfPython ✅ Today I met two of Python's most powerful data structures. One of them already feels like home. The other? Slightly chaotic. Lists and dictionaries. Day 5. Lists made sense quickly — they're just ordered collections. I can store things, loop through them, sort them, slice them. Intuitive. Dictionaries? At first, the key-value pair concept felt abstract. The bug that got me today? I threw both strings and integers into the same list and tried to sort it. Python did not appreciate that. TypeError showed up like an old enemy. Day 5 done. 25 more to go! 👇 Lists vs dictionaries — when do you reach for one over the other? #Python #30DaysOfPython #DataStructures #StudentLife #AIML

Recursion confused me. So I built a visualizer for it. 🐍 Most beginners (including me) struggle with one thing: "What actually happens when a function calls itself?" So I wrote a Python program that shows you — step by step, with a delay so you can actually follow it. Watch it go DOWN the stack, hit the base case, then come back UP — adding numbers on the way. 👇 What I used: → Recursion — function calling itself → time.sleep() — to slow execution down visually → Print statements — to trace every step This isn't from a tutorial. I built this because I was confused. That's the best reason to build anything. 💡 Important: Dry run your code, It helps alot. #Python #Recursion #LearningInPublic #DataAnalytics #BBA #BuildInPublic

Ever tried to sort a list and ended up with None? The logic looks correct: nums = [3, 1, 2] sorted_nums = nums.sort() print(sorted_nums) 👉 Output: None Why did it fail? In Python, there is a big difference between a Method that modifies an object and a Function that returns a new one. 1️⃣ .sort() is a Method: It modifies the original list "in-place." It doesn't need to return anything because the work is done directly on the original variable. 2️⃣ sorted() is a Function: It creates a brand-new list and leaves the original one exactly as it was. Use .sort() when you want to save memory and don't need the original order anymore. Use sorted() when you need to keep your original data safe and want a new sorted version. #Python #30DaysOfCode #BCA #LearningInPublic #Day22 #JECRC

Day 3 of #30DaysOfPython ✅ Today Python started making decisions. So did I. 🔄 Control flow: if, elif, else, and loops (for and while). This is where code starts to *feel* like logic, not just instructions. Turns out, Python reads your if-elif chain from top to bottom and stops at the first True condition. I had my conditions backwards and everything was coming back😂 What I learned today: • elif is just a cleaner way to chain conditions • range() is weirdly intuitive once you stop fighting it • Infinite while loops are terrifying until you find the break statement • Indentation errors are my personal villain Day 3 done. Code is slowly starting to feel less like a foreign language. 👇 For loops or while loops — which do you use more day-to-day? #Python #30DaysOfPython #ControlFlow #CodeNewbie #MachineLearning

I used to think errors were just problems… now I’m learning they’re part of the design. Today’s Python MahaRevision ⚙️ Chapter 12: Advanced Python (Part 1) This chapter felt like moving from basics to writing more robust code: → Exception handling (try-except) → Raising exceptions → try with else & finally → global keyword → __name__ == __"main"__ → enumerate function → List comprehensions A lot of small concepts—but each one adds more control and clarity to how code behaves. Practice set done: Handled errors in programs, experimented with custom exceptions, used enumerate for cleaner loops, and practiced writing compact code using list comprehensions. Some parts were new, some a bit tricky… but overall it felt like leveling up from just writing code to writing better code. Still learning, still improving. #Python #LearningInPublic #CodingJourney #Programming #AdvancedPython

Day 2 of #30DaysOfPython ✅ Today's lesson: Python doesn't care how you label things — until it does. I spent today learning variables and data types. Sounds basic. It is basic. But here's what I didn't expect — Python's dynamic typing actually confused me at first. In theory, I knew that x = 5 and x = "five" are both valid. In practice, I accidentally added a string to an integer and got a TypeError I didn't understand for 10 whole minutes. The bug? I was reading user input and forgetting that input() always returns a string. So my "sum" was just two numbers glued together like "510" instead of 15. 🤦 What clicked today: • int, float, str, bool — the four I'll use constantly • type() is your best friend when debugging • Python is forgiving… until you mix types Lesson of the day: Read your error messages. The answer is usually right there. Resources I used: Python.org official docs + a great freeCodeCamp YouTube video. Day 2 done. The bugs are starting early — right on schedule. 😅 👇 What's the sneakiest beginner Python bug you ever ran into? Tell me so I can be prepared! #Python #30DaysOfPython #DataTypes #CodingJourney #TechLearning

𝗗𝗮𝘆 𝟮𝟬/𝟯𝟬  This week wasn't about learning new syntax. It was about noticing how Python actually behaves 𝗕𝘂𝗴𝘀 are rarely confusing because they are complex. They are confusing because they don't show up where they actually start 📍 𝗔 𝗹𝗶𝘀𝘁 changes… but the issue was three functions ago 📍 𝗔 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 runs fine… but your data is already different 📍 𝗧𝘄𝗼 𝘃𝗮𝗿𝗶𝗮𝗯𝗹𝗲𝘀 look the same… but behave differently That’s the tricky part. it might feel simple until you have to 𝗱𝗲𝗯𝘂𝗴  it. Still figuring it out, but now I know what to pay attention to. #Python #30DaysOfCode #LearningInPublic #Day20 #JECRC

Day 5/365: Checking Armstrong Numbers in Python 🔢🧠 Today I worked on a classic number theory problem: checking whether a number is an Armstrong number. A number is an Armstrong number if the sum of its own digits each raised to the power of the number of digits is equal to the original number. For example: 153 has 3 digits 1³ + 5³ + 3³ = 1 + 125 + 27 = 153 So 153 is an Armstrong number. What this function does: First, I store a copy of the original number so I can compare at the end. Then I find how many digits the number has using len(str(copy)). Inside the loop, I extract each digit, raise it to the power of the number of digits, and keep adding it to a running sum. Finally, I compare the sum with the original number: If they are equal, it’s an Armstrong number. Otherwise, it’s not. What I learned from this exercise: How to break a number down digit by digit using % 10 and // 10. How to combine math (powers) with loops and conditionals to implement a rule. The importance of keeping a copy of the original value when you are modifying it in a loop. Day 5 done ✅ 360 more to go. If you have any variations of this problem (like finding all Armstrong numbers in a range or handling user input with validation), share them—I’d love to try them out. #100DaysOfCode #365DaysOfCode #Python #LogicBuilding #ArmstrongNumber #NumberTheory #CodingJourney #LearnInPublic #AspiringDeveloper

Most implementations of the State pattern in Python look very “clean”. Lots of small classes. A base interface. One class per state. But if you’ve ever worked with one in a real project, you know the downside: transitions are scattered, behaviour is hard to see in one place, and adding new states often means touching multiple files. In today’s video, I rebuild the State pattern in a very different way. Instead of relying on inheritance, I make the state machine explicit as data and use decorators to define transitions. The result is a small, reusable engine where the entire flow becomes visible at a glance. If you’re interested in writing Python that’s easier to reason about and extend, this is a pattern worth understanding. 👉 Watch here: https://lnkd.in/eg22yEHR. #python #softwaredesign #designpatterns #statemachine #cleancode

Day 2 done. Today I sat down and learned about Variables and Data Types in Python. And okay... I get it now why people say "start with the basics." I used to skip this stuff. Thought it was too simple to matter. But here's what I realized today: Every single AI model, every dataset, every algorithm you see online it all starts with this. A variable is just a box where you store something. name = "Ali" age = 20 is_learning = True That's it. That's literally it. But when you understand WHAT you're storing - int, str, float, bool - suddenly your code starts making sense. I'm not where I want to be yet. But I'm not where I was yesterday either. Day 1 was print("Hello World") Day 2 is Variables & Data Types Day 3 let's see what happens. If you're also learning from scratch, just know - you're not alone. #Python #LearningInPublic #AIMLEngineering #Day2 #100DaysOfCode