Week 3 of 100DaysOfCode: Classes & Objects in Python

Thinking in Blueprints (Classes & Constructors) Focus: Introduction to OOP and the __init__ method. Day 9(06-04-2026): Today, my perspective on coding shifted. I moved away from just writing "steps" and started thinking in Objects. In Python, everything can be modeled after the real world using Classes. The big breakthrough today: Classes vs. Objects: A Class is the blueprint (like a drawing of a car), and the Object is the actual thing (the car you can drive). The Constructor (__init__): I learned how to use the "dunder init" method to give my objects their initial data the moment they are created. The self Keyword It’s a bit more abstract than what I’ve done before, but it makes the code so much more organized and powerful. #OOP #PythonProgramming #Day9 #ObjectOriented #CodingConcepts

At first, I thought creating classes was enough… but then I realized—real power comes from building on top of them. Today’s Python MahaRevision 🧬 Chapter 11: Inheritance & More in OOP This chapter took things a step deeper: → Inheritance (reusing and extending existing classes) → Types of inheritance → Method overriding → Using super() → Exploring more OOP concepts It actually felt like connecting pieces together instead of starting from scratch every time. Practice set done: Worked on creating parent-child classes, modifying behaviors, and experimenting with inherited properties and methods. Biggest takeaway You don’t always need to build everything new—sometimes the smartest approach is to reuse and improve what already exists. Slowly understanding how real-world applications are structured. One step at a time. #Python #LearningInPublic #CodingJourney #Programming #OOP

I’ve put together a quick reference guide covering essential Python Dictionary and Set methods! 🐍 Whether you are just starting out with Python or need a quick refresher, this document walks through everything from basic dictionary operations like .get() and .update(), to mathematical set operations like .intersection() and .symmetric_difference(). It includes brief explanations and simple code snippets for each method to help you write cleaner, more efficient code. Check out the document below, and let me know your favorite or most-used method in the comments! 👇 #Python #Programming #Coding #DataStructures #PythonDeveloper #Cheatsheet

Today’s Python topic felt like the point where code stops being one-time work and starts becoming reusable. 🐍 Day 11 of my #30DaysOfPython journey was all about the basics of function, and this one was a big reminder that good code is not just about writing more — it is about writing smarter. A function is a reusable block of code designed to do a specific task, and in Python, we define it using the def keyword. Today I explored: 1. How functions are created and called 2. How return sends values back from a function and return None when nothing is returned 3. Passing parameters and arguments 4. Passing arguments using key-value style 5. Default parameters 6. Arbitrary arguments with *args 7. Arbitrary named arguments with **kwargs What stood out to me today was how functions make code feel organized, reusable, and much easier to scale. Instead of repeating the same logic again and again, you write it once and use it wherever needed. One more day, one more topic, one more step toward writing code that is cleaner, smarter, and actually built to last. Github Link - https://lnkd.in/gUhhaW_y #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

Today’s Python lesson felt like the moment code started moving on its own. 🐍 Day 10 of my #30DaysOfPython journey was all about loops, and this topic made one thing very clear: repetition is not boring in programming — it is powerful. Loops help us repeat tasks without writing the same code again and again. Today I explored: 1. while loop — repeats as long as a condition stays true 2. for loop — runs through each item in a collection 3. else with loops — runs only when the loop ends normally 4. break — exits the loop early 5. continue — skips the current step and moves to the next one 6. range() — generates numbers with start, end, and step 7. pass — a placeholder when we do not want to execute anything yet 8. nested for loops What stood out to me today was how loops make Python feel more efficient and more alive. Instead of doing one thing at a time manually, you let the program handle repetition with logic. One more day, one more topic, one more step toward writing code that does more with less. Which loop concept made the most sense to you first: for, while, break, or continue? Github Link - https://lnkd.in/gbzDtx6f #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

𝗪𝗵𝘆 𝗜 𝗟𝗼𝘃𝗲 𝘁𝗵𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗠𝗮𝗱𝗲 𝗘𝗮𝘀𝘆 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁 When learning Python, it’s easy to get overwhelmed by tutorials, syntax, and scattered notes. That’s why I built a Python Made Easy Cheat Sheet — a one-page guide to help learners understand Python faster and better. It summarizes all the essentials — from variables and loops to libraries and OOP concepts — so you can code confidently without flipping between tabs. Perfect for anyone diving into data science, automation, or web development. Simple. Practical. Beginner-friendly. 🎯 Learn smarter, not harder. #Python #LearningJourney #Programming #TechCommunity #DataScience #PythonCheatSheet #CareerGrowth

𝗪𝗵𝘆 𝗜 𝗟𝗼𝘃𝗲 𝘁𝗵𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗠𝗮𝗱𝗲 𝗘𝗮𝘀𝘆 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁 When learning Python, it’s easy to get overwhelmed by tutorials, syntax, and scattered notes. That’s why I built a Python Made Easy Cheat Sheet — a one-page guide to help learners understand Python faster and better. It summarizes all the essentials — from variables and loops to libraries and OOP concepts — so you can code confidently without flipping between tabs. Perfect for anyone diving into data science, automation, or web development. Simple. Practical. Beginner-friendly. 🎯 Learn smarter, not harder. #Python #LearningJourney #Programming #TechCommunity #DataScience #PythonCheatSheet #CareerGrowth

Hi guys, I know it’s delayed—now let’s dig into Python again for this post! 💭 Day 3 with Python… something finally clicked. The errors didn’t stop. The confusion didn’t magically disappear. But today… I wrote something that actually worked. Not just print("Hello, World!") Not just fixing errors… 👉 I made decisions in my code. Using if...else, my program could finally think (at least a little 😄) “IF this happens → do this” “ELSE → do something else” And suddenly, coding didn’t feel like typing… It felt like logic coming to life. 💡 That’s when I realized: Programming isn’t about memorizing syntax. It’s about teaching a machine how to think step by step. Every small concept—conditions, loops, functions— They’re not just topics… They’re building blocks of something bigger. Today it’s simple decisions. Tomorrow? Maybe something powerful. ✨ Step by step… line by line… growth is happening. #Python #CodingJourney #Day3 #LearnToCode #Programming #DeveloperLife #LogicBuilding #TechGrowth 🚀

Today’s Python lesson made the whole language feel more connected. 🐍 Day 12 of my #30DaysOfPython journey was all about modules, and this one felt like learning how Python organizes its tools behind the scenes. A module is basically a file that contains code, functions, or variables that you can reuse in another file. Instead of writing everything from scratch, you can create something once and bring it into your main program whenever needed. Today I explored: 1. What modules are and why they matter 2. Creating a separate file and importing it into another file 3. Importing only specific parts instead of the whole file 4. Renaming something while importing it 5. Built-in modules like os, statistics, math, string, and random What stood out to me today was how modules make Python feel less like a single script and more like a system of connected pieces. That shift matters because it is what makes code easier to reuse, organize, and scale. One more day, one more topic, one more step toward writing code that is cleaner, smarter, and more modular. Which felt more useful to you first: creating your own module or using built-in ones like math and os? Github Link - https://lnkd.in/gVPWQWiS #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

Today’s Python lesson was a quiet reminder that time is one of the most useful things code can help us handle. 🐍 Day 16 of my #30DaysOfPython journey was all about date and time. Python’s date and time module helps us work with: 1. current date and time 2. formatted date strings 3. converting strings into datetime objects 4. time objects 5. time differences and time spans A few things I explored today: 1. dir() and help() to check what a module offers 2. datetime.now() for current date, time, and timestamp 3. strftime() for formatting dates and time 4. strptime() for converting string dates into datetime objects 5. date() to get only day, month, and year 6. subtraction to find the difference between two time points 7. timedelta() to work with time intervals What stood out to me today was how Python does not just store time — it helps you shape it, compare it, and format it in ways that actually make sense for real projects. One more day, one more topic, one more layer of Python making everyday things easier to manage. Github Link - https://lnkd.in/gMy-QseU #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney