Creator Scripts’ Post

Day 1 of my Daily DSA Real World Projects series! Today I built a Browser History System using Stack Data Structure from scratch! 1.Stack implemented using Linked List 2. Push → navigates to Gmail pages in Chrome 3. Pop → goes back to previous page 4. Automated using Python + Selenium This is exactly how your browser's Back button works internally — powered by a Stack! Every day I'll be building one real world project using Data Structures — no boring theory, just pure practical code! Day 2 coming tomorrow 👀 #DataStructures #Python #Selenium #Stack #100DaysOfCode #Programming #RealWorldProjects #LinkedList #WebAutomation #LearningInPublic

🚀 Day 11 of #111DaysOfLearningForChange – Code for Change Built a GitHub Trending CLI Tool to discover popular repositories 🌐💻 📌 What I learned today: • Advanced API usage with query parameters • Building flexible CLI tools using argparse • Filtering data based on time (day, week, month, year) • Handling API responses and errors effectively 🛠️ What I built: A CLI tool that: • Fetches trending GitHub repositories 📈 • Filters results by duration (day/week/month/year) • Displays repo details (name, stars, language, link) ✨ Example usage: python trending.py --duration week --limit 5 ✨ Key takeaway: Combining APIs with CLI tools can create powerful and practical developer utilities ⚡ Challenge faced: Constructing correct API queries and handling different response cases #111DaysOfLearningForChange #CodeForChange #Python #CLI #API #GitHub #LearningInPublic https://lnkd.in/gNBy3eiN

𝙂𝙞𝙩 𝙘𝙤𝙢𝙢𝙖𝙣𝙙𝙨 𝙖𝙧𝙚 𝙚𝙖𝙨𝙮. 𝙂𝙞𝙩 𝙥𝙧𝙤𝙗𝙡𝙚𝙢𝙨 𝙖𝙧𝙚 𝙣𝙤𝙩. Everything works fine… until it breaks. And that’s where most developers get stuck. You can clone, commit, and push. But real challenges look like this: ➥ How do you pull without losing your work? ➥ How do you commit only what matters? ➥ How do you undo mistakes safely? ➥ How do you resolve conflicts cleanly? ➥ What do you do when your push gets rejected? This guide focuses on real Git problems you face daily and shows exactly what to do in each situation. Git isn’t about memorizing commands. It’s about knowing what to do when things go wrong. Doc Credit - Respective Owner ♻️ Repost if you found this useful 🤝 Follow Sattari Sateesh Kumar for more  👨💻 For 1:1 guidance → https://topmate.io/sateesh #python #pyspark #pysparklearning #dataengineering #sqllearning #dataengineeringinterview #azuredataengineer #bigdata #spark #datalearning #datacareer #azuredataengineering #dataengineeringjobs #linkedinlearning #dataengineeringlearning

From "It Works on My Machine" to Shipping Code That Works Everywhere! Most data projects don't fail because of bad code. They fail because of broken environments. Library version mismatches. Pipelines that break overnight. Onboarding that takes days instead of minutes. Docker solves all of that by packaging your code, Python version, and dependencies into a single container that runs identically anywhere. I wrote a full breakdown of the business and technical impact, and what it looks like in a real data project: 👉 https://lnkd.in/gh8-r3Bj #Docker #BusinessIntelligence #BI #DataScience #Python

💡 What I learned from this project: How to use requests to fetch data from a website How to parse HTML using BeautifulSoup How to extract and clean song data from real web pages How to use the Spotify API with Spotipy How to automate playlist creation using Python 🔗 GitHub Project: https://lnkd.in/g9T-YP23 This is part of my journey of learning data science step by step and building projects along the way. Small projects like this are helping me stay consistent and actually understand how things work, instead of just watching tutorials. #Python #DataScience #WebScraping #APIs #Automation

Write code that doesn't break in production...! When building end-to-end pipelines, reading data from GitHub or external URLs is common. But relying on a "happy path" is a mistake. For robust development, always implement: Logging: To track the flow and capture specific error details. Exception Handling: To prevent the entire app from crashing and get clear "Unable to load" alerts. It’s a simple habit, but it’s what separates a beginner from a Pro Developer. #Python #MLOps #CleanCode #SoftwareEngineering #DataScience #CodingTips

🚀 Just built a simple yet useful Python script! The idea is straightforward: 📂 Read files from a directory 🔍 Scan for errors inside those files 🖥️ Print detected errors on the screen This is a small step towards building automation tools for log analysis and debugging — something really important in DevOps workflows. Currently away from my laptop, but soon I’ll: ✅ Push the complete code to GitHub ✅ Share screenshots and detailed explanation Stay tuned! 👨💻 #Python #DevOps #Automation #Learning #CodingJourney

🚀 Finished a Python Bootcamp. Now the real work begins. Here’s the practical reality of where I stand: What I can do: Build small, useful tools (automation + utilities) Work with APIs to fetch real-world data Create basic web apps using Flask Use Git, GitHub & Git Bash for version control Work with different Python libraries & modules What I’ve built so far: PDF Merger File Organizer News App (API-based) QR Generator & other small tools Where I’m not strong yet: Building complex projects completely on my own Turning ideas into full-scale applications without guidance And that’s the gap I’m focused on closing. Because I’ve realized something important: Courses don’t make you skilled. Building, failing, and improving does. So instead of jumping to another course, I’m focusing on what actually moves the needle now: → Practicing by building → Improving my current skills → Exploring different areas where I can apply what I’ve learned Turning knowledge into real, usable skills — step by step. If you’re learning to code, don’t ask “Which course should I take next?” Ask: “What can I build with what I already know?” #BuildInPublic #Python #Flask #CodingJourney #LearningInPublic #Tech #Consistency

🚀 Problem Hunter Challenge – #KodeCampBuilds Many businesses struggle with turning raw data into meaningful reports. Manual reporting is time-consuming, error-prone, and slows down decision-making. 💡 My solution direction: Building a Report Generation API using Python and FastAPI that automatically transforms raw data into insights and structured reports in KodeCamp 6.0. #KodeCampBuilds #kodecamp #kodehauz

Day 2/30 – Building with Python Recently, I worked on a Vehicle Feedback System using Python The idea behind this project was to create a simple system where users can: 📝 Submit feedback about vehicles 📊 Store and manage responses efficiently Through this project, I learned: ✨ How to handle user input and data ✨ Basic logic building and structuring a program ✨ The importance of user-friendly systems This is just the beginning — I’m planning to improve it further by adding: OTP-based authentication for better security Database integration for scalability Possibly a simple UI for better user experience Building projects like this is helping me understand how real-world systems evolve step by step Would love your suggestions or ideas to improve this further! #Day2 #PythonProject #LearningInPublic #StudentDeveloper #BuildInPublic #TechJourney