Streamlit Image Compressor Web App Built with Python

🚀 Built a Unit Converter App with Python & Streamlit! From meters to miles, Celsius to Fahrenheit, kg to pounds — all in one clean interface. ✅ 7 conversion categories (Length, Weight, Temperature, Time, Speed, Area, Volume) ✅ Built with Python + Streamlit ✅ Clean, intuitive UI — no clutter ✅ Instant results with one click This is the power of Python 🐍 — a fully functional web app in under 150 lines of code! Currently learning and building with AI assistance. More projects coming soon! 💡 #Python #Streamlit #WebApp #100DaysOfCode #AI #TechPakistan #Programming #BuildInPublic

One of the best ways to truly understand an algorithm is not just to read it—but to see it and interact with it. So I built a tool around that idea. 👉 https://lnkd.in/dHzW7tjW You can: - write Python code - attach visuals directly to it - step through execution and watch the state evolve For example, you can visualize a balanced binary search tree—one of those structures that looks simple on paper but is tricky to truly internalize—and watch how it balances itself step by step. But more importantly, you're not just watching. You can make the visualization interactive: click nodes, manipulate the structure, and even try to balance the tree yourself—so you don't just see what the algorithm does, but start to feel why it works. I've been exploring several algorithms with it — including the A* attached video. 🙏 If you'd like to try it, I'd love feedback: - bugs or rough edges - feature ideas - examples you'd want to build You can reach out here or through the app directly. Built with Claude Code. #algorithms #python #webdev #buildinpublic

This is such a cool idea! Instead of just reading about algorithms, you can actually interact with them, step through execution, and visualize what’s happening. What makes it even more interesting is how AI is being used here not just to generate code, but to create a much more intuitive way to learn and explore complex concepts. Super useful for understanding things that are usually hard to really “feel” from static code alone. Great work on this 👏 definitely worth a look

🚀 Excited to share my latest project! I built a Weather Prediction Web App using Python, Flask, and Machine Learning. 🌦️ 💡 What it does: Users can input weather parameters (like temperature, humidity, etc.) The app predicts the weather using a trained ML model Built with a simple and clean Flask web interface 🔧 Tech Stack: Python, Flask scikit-learn (for ML model) Joblib (to load the trained model) HTML for web interface 📂 GitHub Repository: https://lnkd.in/gG2erzRQ 👀 Highlights: Learned how to integrate ML models into a web app Hands-on experience with Flask routing, deployment, and debugging Would love to hear your feedback! 💬 #MachineLearning #Python #Flask #WebDevelopment #DataScience #Project

Day 3/30 – NumPy operations with image I developed an Image Editor web app where most of the image processing is powered by NumPy. 🌐 Live App: https://lnkd.in/gBf2rK7U GitHub: https://lnkd.in/gxENJ_3C Key things I learned: 🔹 NumPy for Image Processing – Images are just arrays (pixels) – Applied operations like brightness, contrast, negative using array math – Used slicing for crop, flip, rotate – Created effects like grayscale, sepia, vignette using matrix operations 🔹 Real-time Transformations – Converted images (Base64 ↔ NumPy array) – Applied filters and returned processed images through APIs 🔹 Advanced Processing – Blur (Gaussian filter), edge detection (Sobel) – Sharpening using array differences This project helped me understand how powerful NumPy is for real-world image manipulation. #NumPy #Python #Flask #ImageProcessing #WebDevelopment #LearningByDoing

🚀 Day 1 of My Machine Learning Journey — Built My First Web App! Today wasn’t about watching tutorials. It was about execution. I built a Student Marks Analyzer Web App using: Python 🐍 Flask 🌐 HTML + CSS 🎨 💡 What it does: Takes student name & marks Calculates total, average Assigns grade Shows pass/fail result ⚡ What I learned today: Basics of Python (loops, functions, logic) How backend connects with frontend Real debugging (and yes… errors taught me a lot 😄) How to turn an idea into a working system 🔥 Biggest realization: “Learning doesn’t count. Building does.” This is just Day 1. No perfection. Just consistency + execution. 📈 Goal: Become a Machine Learning Engineer by building real projects. If you're also on a similar journey, let’s connect 🤝 #Python #Flask #WebDevelopment #LearningInPublic #100DaysOfCode #BuildInPublic #AIJourney

I built a Python automation engine that can hit 11ms reaction times. ⚡ To put that in perspective, the average human reaction time is about 250ms. Macro Studio is responding to screen changes before a human brain could even register that something happened. If you've ever tried building a high-speed desktop bot in Python, you know the struggle. Standard libraries are great for simple tasks, but the moment you try to scale up, time.sleep() bottlenecks your logic, and managing OS threads usually ends up freezing your UI thanks to the Global Interpreter Lock (GIL). I wanted an engine that actually respected Python's capabilities while providing ultimate control, so I built it myself. I’m excited to share Macro Studio. It’s a free, open-source automation framework I developed that bridges the gap between simple macro recorders and complex software development. Instead of heavy OS threads, it uses a cooperative multitasking yield architecture and direct GDI polling. The result? High-frequency pixel retrieval that easily averages superhuman reaction times on the Human Benchmark, while keeping the UI and subsequent tasks completely responsive. Because it runs pure Python, the possibilities are infinite. You can hook in OpenCV, ping external APIs, or integrate LLMs directly into your automation loop. Check out the full showcase below demonstrating how it flawlessly navigates complex game environments (like Roblox). Building this architecture from the ground up has been an incredible month-long side project. I'm keeping it 100% free and open-source under GPLv3 for anyone who wants to build high-performance macros without the paywalls. I've dropped a link to the YouTube showcase, the GitHub repository, and the documentation in the comments below. 👇 Drop a star, build something ridiculous, and let me know what you think of the architecture! #Python #SoftwareDevelopment #OpenSource #Automation #ComputerScience

Yesterday, I built something small… but it taught me a LOT. I created a Typing Speed Test desktop app using Python ⌨️ At first, it sounded simple: “Just display some words and calculate speed, right?” Yeah… not quite 😅 I quickly ran into questions like: How do I update the UI after 30 seconds automatically? How do I remove widgets and replace them with results? How do I make sure words don’t repeat randomly? And how do I actually calculate WPM correctly? That’s when things got interesting. I ended up building it entirely with Tkinter — and honestly, I feel like people sleep on it. It’s not flashy, but it forces you to really understand how GUIs and event-driven systems work under the hood. Here’s what the app does: → Generates 40 random words (no duplicates) → Starts a 30-second timer → Tracks how many words you type → Calculates your WPM → Saves your high score (so you can try to beat yourself 👀) The biggest lesson for me wasn’t even the code… It was realizing how “simple projects” quickly become complex when you try to make them feel real. That’s where the real learning happens. Next, I want to improve the accuracy system, polish the UI, and maybe turn it into something more interactive. If you’ve ever built something that looked easy at first but humbled you halfway through… you know the feeling 😄 You can check out how it works in the video below. #Python #Tkinter #BuildInPublic #CodingJourney #SoftwareDevelopment #100DaysOfCode

Nested loops aren’t “double the confusion”—they’re just one rule: For **each** outer step, the **inner** loop runs **completely**. That’s why total work is **outer × inner** (and why grids/patterns finally make sense). I wrote a beginner-friendly Python guide covering: ✅ Outer vs inner execution order (trace in your head in 30 seconds) ✅ `(i, j)` pairs + why 3×3 → 9 prints ✅ `print(..., end=" ")` + `print()` for row/column layouts ✅ Star blocks + `j <= i` triangles ✅ Nested loops over strings (cartesian product intuition) ~4 min read. Copy-paste demos included. https://lnkd.in/gmB9Cn2q #Python #Programming #Coding #Beginners #LearnToCode #NestedLoops #ForLoop #Algorithms #Patterns #Practice #Tech #SoftwareDevelopment

🚀 Streamlit Full Course: From Beginner to Advanced Want to master Streamlit and build interactive data apps with ease? I've put together a comprehensive, free course covering everything from basic widgets to advanced dashboard techniques. 📚 Explore the full course: https://lnkd.in/gTSBpuvi 🔹 What you will learn • Streamlit Installation & Setup • Core display methods (st.write, st.title, st.header) • Interactive widgets (text_input, slider, checkbox, toggle) • Data visualization with charts and tables • Layouts, sidebars, and multi-page apps • Real-world project examples Happy Learning! 🚀 #Streamlit #Python #DataScience #WebDevelopment #DataApps #MachineLearning