Learning Python: Day 2-3 Progress

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

Day 18 revision done. Operators. If/Else. Match statements. While loops. For loops. Not just reading through notes this time actually writing the code out, making mistakes, fixing them and doing it again until it felt natural. And honestly? It's working. The things that confused me the first time around are starting to make sense now. I finally get why // and % are different. I understand why indentation is not optional in Python. I know when to use a while loop vs a for loop. Revision isn't glamorous. There's no big aha moment. It's just you sitting down, doing the work and trusting that repetition builds confidence. And slowly it is making sense It is finally sticking and guess what I'm happy. Because Python is one of the most amazing tools used in the data space and I'm out here learning it on my own. Day 19 is next. Let's keep going. #Python #100DaysOfCode #SelfTaught #GrowthMindset #DataAnalysis #W3schools

👋 Welcome back! 📅 Python Learning – Day 63 Today we move to a faster and more efficient sorting method: Quick Sort. Quick sort works by selecting a pivot element and dividing the list into two parts — smaller values on one side and larger on the other. This divide-and-conquer approach makes it much faster than basic sorting methods. 📘 In this lesson, I’ve explained: ⚡ How quick sort works using partitioning 🔀 How recursion helps sort the divided parts ⚠️ Common beginner mistakes when choosing pivot and handling recursion Quick sort is widely used because of its speed and efficiency. Once you understand how it breaks problems into smaller parts, your approach to problem-solving improves. 🔗 Tutorial link is in the comments. 💬 If you're following this learning journey and want to stay connected with more tutorials and discussions, you can join our LinkedIn community here: 👉👉 CodePractice Group: (https://lnkd.in/g3xbN4GJ) ⏭️ Tomorrow: Python Counting Sort #QuickSort #DivideAndConquer #LearnPythonDSA #SortingAlgorithms #CodingPractice #PythonProgramming #TechStudents #DeveloperSkills #python #learnpython #codepractice #softwaredevelopment #computerscience #pythondevelopment #pythonlearning

🚀 Learning Something New Every Day! Today I learned an important Python concept — *args and **kwargs. 🔹 *args allows a function to take multiple positional arguments (stored as a tuple) 🔹 **kwargs allows a function to take multiple keyword arguments (stored as a dictionary) 💡 This makes functions more flexible and reusable in real-world scenarios. Here’s a simple example: def demo(*args, **kwargs): print(args) print(kwargs) Step by step, I’m strengthening my Python fundamentals and building a strong base for data analytics. #Python #LearningJourney #Coding #DataAnalytics

👋 Welcome back! 📅 Python Learning – Day 58 Today we explore one of the simplest searching techniques: Linear Search. Linear search checks each element one by one until the target value is found. It may not be the fastest method, but it is easy to understand and works on any list. This is often the first step toward learning more advanced search algorithms. 📘 In this lesson, I’ve explained: 🔍 What linear search is and how it works 📋 How Python checks elements sequentially ⚠️ Common beginner mistakes when implementing search logic Linear search helps you understand the basics of how searching works in programming. Once this is clear, moving to faster algorithms becomes much easier. 🔗 Tutorial link is in the comments. 💬 If you're following this learning series and want to stay connected with more such content, discussions, and updates, you can join our LinkedIn community here: CodePractice Group - (https://lnkd.in/g3xbN4GJ) ⏭️ Tomorrow: Python Binary Search #LinearSearch #SearchAlgorithms #LearnPythonDSA #CodingPractice #AlgorithmBasics #PythonForStudents #TechLearning #DeveloperJourney #pythonlearning #python2026 #codepracticelearning #codepractice #codewithconfidence

🐍 Day 8 of Learning Python — and things are getting real! Today's lab was all about writing code that doesn't break (or at least fails gracefully 😄). Here's what I worked through: ✅ Exception Handling — try / except / else / finally • Caught ZeroDivisionError, FileNotFoundError, ValueError, and TypeError • Used `raise` to throw custom error messages • Built my own exception class: TooSmallError 🎉 ✅ Standard library deep dive: • math — calculated circle areas, factorials, GCD, and compound interest • random — shuffled lists, simulated 1000 coin flips, generated reproducible sequences with seed() • datetime — parsed date strings, added time deltas, sorted ISO dates, and printed 5-day schedules ✅ Introspection with dir() and help() The biggest lesson today? Real-life programs don't always get perfect input. Learning to handle errors gracefully is just as important as writing the happy path. Day by day, the pieces are coming together. 💪 #Python #100DaysOfCode #LearningToCode #PythonProgramming #CodingJourney #Day8

👋 Welcome back! 📅 Python Learning – Day 60 Today we look at one of the simplest sorting techniques: Bubble Sort. Bubble sort works by repeatedly comparing adjacent elements and swapping them if they are in the wrong order. With each pass, the largest element “bubbles up” to its correct position. 📘 In this lesson, I’ve explained: 🔁 How bubble sort works step by step 🔄 How swapping helps arrange elements ⚠️ Common beginner mistakes like unnecessary iterations Bubble sort is not the fastest algorithm, but it is very useful for understanding how sorting actually works. Once this concept is clear, learning advanced sorting becomes easier. 🔗 Tutorial link is in the comments. 💬 If you're following this learning journey and want to stay connected with more tutorials and discussions, you can join our LinkedIn community here: 👉👉 CodePractice Group: (https://lnkd.in/g3xbN4GJ) ⏭️ Tomorrow: Python Selection Sort #BubbleSort #SortingAlgorithms #LearnPythonDSA #CodingPractice #AlgorithmBasics #PythonForStudents #TechLearning #DeveloperJourney #python #learnpython #codepractice #softwaredevelopment #computerscience #pythondevelopment #pythonlearning

Day 18: Today i explored how Python handles memory efficiently using Generators 🔹 What I learned and practiced: ✔️ Generators Functions that return an iterator and produce values one at a time. Great for saving memory when working with large datasets. ✔️ yield Keyword Used to produce a value and pause the function execution. It resumes from the same point when called again, unlike a normal return. ✔️ next() Function Used to retrieve the next value from the generator. Automatically stops when no more values are left to produce. ✔️ Created a square_gen() function to generate squares of numbers one by one. Key takeaway: Generators and yield are powerful tools for writing smarter, more efficient code by only processing what we need, when we need it.and also push in github #Python #codegnan #LearningPython

Day 4/120 – I finally understood how Python actually “thinks” 🤯 For the past 3 days, I was learning concepts… But today, things started making sense. Because I learned this 👇 👉 Operators in Python Operators are what make your code “do something” Without them, Python is just… variables sitting idle 😅 Here’s what I explored today 👇 ➕ Arithmetic Operators → +, -, *, / Example: 10 + 5 = 15 📊 Comparison Operators → ==, !=, >, < Example: 10 > 5 → True 🧠 Logical Operators → and, or, not Example: (10 > 5) and (5 > 2) → True This is where logic begins 🔥 Now I can actually: ✔ Make decisions ✔ Compare values ✔ Build logic Feels like I unlocked a new level 🎮 Consistency > Perfection 💪 If you're learning, comment “LEVEL UP” 🚀 #Day4 #Python #DataAnalytics #LearningInPublic #CodingJourney #Consistency #Beginners