Implementing Linear Search Algorithm in Python

Day 4 of building my skills in IT Automation with Python. 🐍 Today was the most packed day so far; and honestly the one where everything started connecting. Here's what I covered: 🔹 Strings ; what they are, how indexing and slicing works, string methods and formatting. Small tools; powerful results. 🔹 Lists ; storing and modifying collections of data, working with tuples, knowing when to use which. This is where you start thinking in groups not just individual values. 🔹 Dictionaries ; key-value pairs that give your data structure. The moment this clicked; everything about how Python handles data made sense. 🔹 Loops & Recursion ; loops remove repetition, recursion breaks big problems into smaller ones. Combine these with lists and dictionaries and you start seeing how real automation works. 🔹 OOP (bonus) ; classes, methods, constructors. Code as objects that interact rather than just instructions. Deep rabbit hole; worth every minute. This quote from Margarita, Site Reliability Engineer @ Google hit different today: "My 'good enough' solution was really as good as it could get." Sometimes functional beats perfect. 💡 It's not separate topics anymore. It's one language. And that's when you know the foundation is holding. Dropping the docs for anyone following along 👇 📌 Mapping Types - dict ; python.org 📌 Python Dictionaries ; w3schools.com 📌 Common Sequence Operations ; python.org 📌 Lists & Tuples ; python.org Grateful to Mentor Me Collective and Chanel Power 💡🌍 for the structure, access and mentorship making this possible. 🙏 Let's keep going. 🚀 #Python #ITAutomation #BuildInPublic #LearningInPublic #MentorMeCollective #ChanelPower #TechJourney #Cameroon

🚀 Excited to share something we’ve been working on for quite some time… After months of writing, refining, and building real examples, our book is now live: Python Beyond the Basics From Beginner to Advanced with Real Projects 🔗 Read it here: https://a.co/d/0elxazKZ Co-authored with Prakriti Yadav — this has been a collaborative effort driven by a shared goal: to create a resource that actually helps people move beyond just “learning syntax” to building real-world solutions. 💡 Why we wrote this book Over the years, one thing became very clear: Most Python resources either simplify things too much or make them unnecessarily complex. Very few actually connect: ➡ fundamentals ➡ real-world applications ➡ industry-level thinking This book is our attempt to bridge that gap. 📘 What you can expect inside • Clear, structured Python fundamentals • Core concepts explained with practical clarity • Advanced topics like decorators, generators, async • Real-world development using Flask & FastAPI • Working with data using NumPy & Pandas • Hands-on projects to reinforce learning • A strong foundation for AI/ML applications 🎯 Who this is for Whether you’re: • just starting out • self-learning and stuck in tutorials • preparing for interviews • or transitioning into AI/ML This book is designed to guide you step by step - without overwhelming you. This isn’t just a book about Python. It’s about building the ability to think, solve, and create using Python. If you get a chance to check it out, we’d love your feedback. And if you find it useful, feel free to share it with someone who might benefit from it. #Python #AI #MachineLearning #DataScience #SoftwareEngineering #Developers #Learning #Tech #Programming

🚀 Python Series – Day 12: List Comprehension (Write Short & Smart Code!) Till now, we used loops to create lists. But what if you can do it in one clean line? 🤔 👉 That’s where List Comprehension comes in! 🧠 What is List Comprehension? List comprehension is a short and powerful way to create lists. 👉 It replaces loops with a single line of code 🔧 Basic Syntax: [expression for item in iterable] ▶️ Example (Using Loop): numbers = [] for i in range(5): numbers.append(i) print(numbers) ⚡ Same Using List Comprehension: numbers = [i for i in range(5)] print(numbers) 👉 Output: [0, 1, 2, 3, 4] 🔥 With Condition: even = [i for i in range(10) if i % 2 == 0] print(even) 👉 Output: [0, 2, 4, 6, 8] 🎯 Why Use List Comprehension? ✔️ Short & clean code ✔️ Faster than loops ✔️ Easy to read (once you practice) 🔥 Pro Tip: Don’t overuse it 😄 👉 Use it when it makes code simple, not confusing ⚡ Quick Challenge: What will be the output? x = [i*i for i in range(4)] print(x) 👇 Comment your answer! 📌 Tomorrow: Lambda Functions (Anonymous Functions in Python) Follow me to learn Python step-by-step from basics to advanced 🚀 #Python #DataScience #Coding #Programming #LearnPython #Beginners #Tech #MustaqeemSiddiqui

*Day 3 of my 21-day consistency challenge 🚀* *One thing I struggled with while learning Python…* I am still learning Python, and honestly… it humbled me 😅 At first, I thought it was just about writing simple lines of code. But when I started, I quickly realized it was more than that. My biggest struggles? 👉 Understanding the syntax 👉 And importing libraries I’d see things like: import pandas as pd import numpy as np And I’d wonder… “What exactly am I importing?” “Why do I need this?” Then came the errors… Sometimes I’d miss a small detail—like a colon, indentation, or bracket—and everything would stop working. Other times, I’d forget to import a library, and my code wouldn’t run at all. It was frustrating. There were moments I just stared at my screen thinking, “What am I doing wrong?” But over time, I started to understand something: Python isn’t just about typing code… It’s about thinking logically and paying attention to details. And libraries? They’re like tools that make your work easier and more powerful—you just have to learn how to use them. So I changed my approach: – I started practicing small codes – I paid attention to error messages – I focused on understanding, not rushing I’m still a beginner. Still making mistakes. But I’m no longer afraid of errors or confused by libraries. Because now I know—it’s all part of the process. If you’re learning Python and it feels hard, you’re not alone. What’s something that confused you when you were starting out? Yabatech Digital Technology Academy Ibraheem Adedotun Abdul #Day3 #Python #DataAnalytics #LearningJourney #GrowthMindset #LearningInPublic

You can vibe code almost everything in 2026 🚀 But when it comes to client data, sensitive logic, and production-ready code, would you really trust AI to do everything on its own? 🤔 That is exactly where blind vibe coding starts to fall short. I always say this: ask AI for the logic, verify it properly, understand what it is doing, and then integrate it into your main codebase with confidence. That is why knowing a programming language is still not optional — it is essential. And in this AI era, one skill has become even more valuable and almost non-negotiable: Python. 🐍 The reason is pretty clear by now — Python is simple, powerful, versatile, AI friendly and one of the best languages to actually build with. So yes, in contrast to the first paragraph 😂 I vibe coded this entire repo in just 24 hours and made it public for anyone who wants to get better hands-on practice. Introducing PythonVx — a Python coding platform with continuous animation of code flow, designed to help beginners understand Python in a more visual and interactive way. If you are someone who is just starting out and wants to feel more familiar with how Python actually works, this might be useful for you. Check it out here: https://lnkd.in/gCZ26mep Always welcome for contributions 🙌 Leave a star ⭐️ It is much appreciated. ❤️ Btw, have you ever solved this question in this way? 😅 #Python #Coding #Programming #SoftwareDevelopment #Developer #CodeNewbie #LearnToCode #CodingLife #ArtificialIntelligence #AI #MachineLearning #GenerativeAI #TechLearning #Upskill #CareerGrowth #OpenSource #GitHub #BuildInPublic #DevCommunity #TechContent #Innovation #TechTrends #100DaysOfCode #PythonProjects #LearnPython #PythonBeginner #InteractiveLearning

🚀 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧 𝐃𝐨𝐞𝐬𝐧’𝐭 𝐇𝐚𝐯𝐞 𝐭𝐨 𝐁𝐞 𝐎𝐯𝐞𝐫𝐰𝐡𝐞𝐥𝐦𝐢𝐧𝐠 Most beginners quit programming not because it’s hard… But because it’s taught the wrong way. While going through Python Basics: A Practical Introduction to Python 3, one thing stood out clearly: 👉 Simplicity wins. This book doesn’t try to impress you with jargon. It focuses on what actually matters: ✅ Breaking complex concepts into bite-sized lessons ✅ Learning by doing with real-world examples ✅ Building practical skills—not just theory ✅ Following the 80/20 rule to focus on what truly matters 💡 Why Python is a Game-Changer Python isn’t just beginner-friendly… It’s powerful enough to build real-world applications. From a simple: print("Hello, World") To: 🌐 Fetching data from websites 📊 Automating repetitive tasks 📁 Handling files and data That’s why companies like Instagram, YouTube, and Spotify rely on it 🔥 The Real Insight You don’t need to be a computer science expert to start. Even basic Python skills can: • Save hours of manual work • Automate daily tasks • Open doors to new career opportunities Programming today is not just a skill. It’s a personal superpower. 📌 If you’re starting your Python journey: Don’t chase everything. Focus on fundamentals. Practice consistently. Build small, real projects. 👉🏻 follow Alisha Surabhi for more such content 👉🏻 PDF credit goes to the respected owners #Python #LearnPython #CodingForBeginners #Programming #TechSkills #AI #CareerGrowth #Automation #DataScience

🚀 From Writing Code… to Understanding How It Works Internally Most people learn Python by just writing code. But this week, I focused on something deeper — understanding how Python actually behaves behind the scenes. As someone already working in a technical environment, I realized: 👉 Strengthening fundamentals is what truly unlocks growth. 📚 What I Learned I explored core Object-Oriented Programming (OOP) concepts and practical utilities: Static methods — writing cleaner utility functions Instance vs Class variables — understanding data scope Class methods — modifying shared data properly super() — connecting parent & child classes Magic methods (__len__, __init__) — how Python behaves internally Method overriding — customizing behavior File handling — cleaning cluttered directories PDF merging using PyPDF — real-world automation 💡 Key Takeaways Clean structure > messy code OOP is not just theory — it models real-world systems Python has powerful built-in capabilities (we just need to explore them) Small automation scripts can save hours of manual work 🌍 Real-World Impact Instead of just learning syntax, I can now: ✔ Organize large codebases better ✔ Automate repetitive tasks (like file cleanup & PDF merging) ✔ Understand how scalable systems are designed 📈 Growth Mindset This journey reminded me: “You don’t grow by jumping ahead. You grow by strengthening your basics.” 🤔 Question for You What concept in Python or programming completely changed your understanding when you first learned it? 👉 If you're also on a journey to improve your tech skills, let's connect and grow together. #Python #OOP #LearningJourney #Coding #CareerGrowth #100DaysOfCode #WebDevelopment #Automation

🚀 DSA Day 5 — Recursion (Core Problems) Today I focused on strengthening my recursion fundamentals by solving some classic problems from scratch. 🔹 Topics Covered: • Printing numbers (1 → 10 and 10 → 1 using recursion) • Factorial using recursion • Sum of digits (two approaches: accumulator & return-based) • Reverse a number (recursive approach) • Palindrome check using recursion 🔹 Key Learnings: Recursion is not about memorizing patterns — it’s about understanding: Base condition (where to stop) State change (how the problem reduces) If you don’t get these right, recursion will break. 🔹 Two practical insights I learned: • Example 1: In factorial, missing the correct base case (n == 1 or n == 0) leads to infinite recursion. • Example 2: In reverse number, carrying state (rev) properly is critical — otherwise, you lose digits. 🔹 What I improved today: • Writing cleaner recursive functions • Avoiding unnecessary parameters • Thinking in terms of smaller subproblems 📌 Code available here: [🚀 DSA Day 5 — Recursion (Core Problems) Today I focused on strengthening my recursion fundamentals by solving some classic problems from scratch. 🔹 Topics Covered: • Printing numbers (1 → 10 and 10 → 1 using recursion) • Factorial using recursion • Sum of digits (two approaches: accumulator & return-based) • Reverse a number (recursive approach) • Palindrome check using recursion 🔹 Key Learnings: Recursion is not about memorizing patterns — it’s about understanding: Base condition (where to stop) State change (how the problem reduces) If you don’t get these right, recursion will break. 🔹 Two practical insights I learned: • Example 1: In factorial, missing the correct base case (n == 1 or n == 0) leads to infinite recursion. • Example 2: In reverse number, carrying state (rev) properly is critical — otherwise, you lose digits. 🔹 What I improved today: • Writing cleaner recursive functions • Avoiding unnecessary parameters • Thinking in terms of smaller subproblems 📌 Code available here: [Add your GitHub link] #DSA #Recursion #Python #CodingJourney #ProblemSolving #100DaysOfCode] #DSA #Recursion #Python #CodingJourney #ProblemSolving #100DaysOfCode 10000 Coders sanjeev ch

Day 5 of my coding journey 🚀 A simple mistake, but very common for beginners. Today I made a small mistake in functions...😅 # Functions to add two numbers def add(a, b) return a + b print(add(2, 3)) I expected the output 5, but nothing happened. The print() statement was written after return, so it never executed. Fix ✅ def add(a, b) return a + b print(add(2, 3)) Output: 5 ✅ small mistake, but a good lesson. #Python #AI #MachineLearning

I spent weeks writing Python without truly understanding OOP. I knew what a class was. I could copy the syntax. But I didn't really get it. Then one session at StemLink changed how I see it. 🧬 Here's the honest story of how OOP finally made sense to me 👇 --- Before OOP, my code looked like this: name = "Abiya" age = 20 course = "CS" def greet(name):   print(f"Hi, I'm {name}") Just variables and functions floating everywhere. No structure. No connection between them. --- Then I learned: a Class is just a blueprint. class Student:   def __init__(self, name, age):     self.name = name     self.age = age   def greet(self):     print(f"Hi, I'm {self.name}") me = Student("Abiya", 20) me.greet() Now the data and the behavior belong together. That's it. That's OOP. --- The 4 pillars — simplified: 🔷 Encapsulation → keep data and methods inside one class 🔷 Inheritance → one class can extend another 🔷 Polymorphism → same method, different behavior 🔷 Abstraction → hide complexity, show only what matters I used to memorize these definitions for exams. Now I actually use them when writing code. --- The mindset shift: Stop thinking in steps. Start thinking in objects — what things exist, what they know, and what they can do. That shift made me a better programmer. What OOP concept took you the longest to understand? 👇 #Python #OOP #ObjectOrientedProgramming #StemLink #IITColombo #CS #LearnToCode #StudentDeveloper #BuildInPublic