I was tired of manually packing textures for UE5 material workflows, so I built a tool to do it for me. Batch Channel Packer: drop in a folder of textures, it finds the pairs automatically and outputs packed RGBA textures ready for your material graph. BCR pack → R/G/B = BaseColor, A = Roughness NOH pack → R/G = Normal XY, B = Occlusion, A = Height MEO pack → R = Metallic, G = Emissive, B = Opacity (if available based on the texture set, skip NOH packing for this instance) Built with Python, Pillow, and NumPy. No plugins, Easy to run I put the repo on GitHub, https://lnkd.in/gbX8EPM8 #UnrealEngine5 #Python #GameDev #Unreal_pipeline #Tools #OpenSource #Technical_art

The first version of my Task Manager CLI was a mess. One big file. Everything tangled together. It worked — barely. Then I refactored it into modular components. Debugging effort dropped by 40%. Not because I became smarter, but because I could finally isolate problems instead of hunting through 300 lines of spaghetti code. That refactor taught me something no tutorial spells out clearly: Clean code isn't about aesthetics. It's about reducing the cost of being wrong. When you write modular code: → Bugs are easier to find → Features are easier to add → Other people (or future you) can actually understand it I now think about modularity before I write a single function. It's the difference between a project that grows and one that collapses under its own weight. What's a coding habit you wish you'd developed earlier in your journey? #CleanCode #SoftwareEngineering #Python #BackendDevelopment #CodingBestPractices

🚀 Day 92 of #100DaysOfLeetCode 🔥 Solved: 120. Triangle (Medium) Today’s problem was all about finding the minimum path sum from top to bottom in a triangle. At each step, you can move to adjacent numbers in the next row. 💡 Key Insight: Instead of exploring all paths (which is costly), I used Dynamic Programming (Bottom-Up approach): - Start from the second row - Update each element by adding the minimum of the two possible parents - Final answer = minimum value in the last row 🧠 Why this works: We reuse previously computed results, reducing time complexity significantly. ⚡ Complexity: - Time: O(n²) - Space: O(1) (in-place modification) 💻 What I learned: - How to optimize recursive problems using DP - Importance of in-place updates for space efficiency - Clear understanding of adjacent state transitions 📈 Result: ✅ Accepted ⏱ Runtime: 3 ms 💾 Memory: 20.13 MB Consistency > Motivation. Showing up daily 💪 #Day92 #LeetCode #DynamicProgramming #CodingJourney #100DaysOfCode #DSA #Python #ProblemSolving

Selva-Canopy is out—the first extension plugin for Selva. Canopy is a standalone Plotly wrapper that lets you build and display interactive charts directly in the Grasshopper canvas. It integrates directly with Selva (v0.8.0+), meaning Plotly charts can now be used inside the UI-Builder to put together full dashboards. For more advanced control, you can also create charts using Python. Available on Food4Rhino: https://lnkd.in/evxEC955 or the package manager Runs on Mac and Windows. Mac viewer stability is still getting some improvements—for now the HTML output gives the most robust viewing experience. #Grasshopper #ComputationalDesign #DataVisualization #Plotly

OOP clicks a lot faster when you actually build something with it. In this project, you’ll create a text-based garden simulator using Python classes, where you forage, plant, grow, and harvest while learning concepts like inheritance, methods, and class design along the way. If OOP has felt confusing to you, this is a hands-on way to make it stick: https://buff.ly/aUoWN87

Automate away the boring and repetitive, if you can. This post is brought to you by automating some of the little tasks around drawing package prep, using Python with Rhino for view titles, and Grasshopper for sheet lists and hardware schedules.

More adventures in #Claude ... We're constantly improving our automation stack here at Eikon and our latest experiment was to see if we could combine our claude agent automation stack to build out a completely de novo way to control a Bravo. After sniffing out the basic instructions for all the primitive tasks on the Bravo we set Claude loose. The result is a brand new frontend/backend stack that controls a Bravo and enables scripting in Python (or any language you want to plugin). Now it's on to integrating it into our DMTA framework so it'll help accelerate our more important work of finding cures for diseases.

🐍 Built something fun this weekend — Python Tug of War! Two teams. 45 Python MCQs. One rope. Only one winner. Instead of the usual quiz format, I wanted learning to feel competitive and alive. So I built a real-time tug-of-war game where every correct answer pulls the rope toward your opponent — and every wrong one pulls it back. ⚡ What's packed inside a single HTML file: → Canvas-animated tug-of-war with stick figures → 45 Python MCQs across Easy / Medium / Hard → 30-second countdown timer per question → 3-answer streak = ⚡ POWER PULL (2× rope movement) → Hard questions = double rope pull → 50/50 lifeline + Skip lifeline per team → Keyboard shortcuts (A/B/C/D) → Confetti on win 🎉 #Python #WebDevelopment #JavaScript #BuildInPublic #GameDevelopment #LearnPython #SideProject #Developer #TechIndia #100DaysOfCode

Glad to share a new local tool I have been developing for use at Pivotal Environmental: BGS-Pro. It is a Python data visualization app built with Kitware Inc. and Trame. The graphic here shows a 3D model of a subsurface contaminant plume. BGS-Pro allows for rotation, zooming, and other interactive functions that help me evaluate data, better understand site conditions, and communicate technical information more clearly. Always good to keep building practical tools that improve project work. #EnvironmentalEngineering #DataVisualization #3DModeling #Python #Kitware #Trame

🚀 Day 60/60 of #60DaysOfCode Completed the problem “Buildings with Sunlight” from . 🌇 Problem: Given heights of buildings, count how many receive sunlight from the left side. A building gets sunlight only if no taller building exists before it. 💡 Approach: Traverse from left and track the maximum height so far: - If current height ≥ max → it gets sunlight - Update max height 🧠 Key Learning: A simple greedy approach can solve this efficiently in one pass. 💻 Code: class Solution: def visibleBuildings(self, arr): max_height = 0 count = 0 for h in arr: if h >= max_height: count += 1 max_height = h return count ⚡ Complexity: - Time: O(n) - Space: O(1) Consistency paid off — 60 days strong 💪 Next target: bigger challenges 🚀 #Day60 #60DaysOfCode #Python #DSA #Greedy #ProblemSolving #CodingJourney #GeeksforGeeks Feedback for GeeksforGeeks POTD: A very good problem to test stack-based simulation and careful implementation. The statement looks simple, but repeated reductions create multiple hidden edge cases. ✔️ Helped improve logical tracing ✔️ Good for understanding chain reaction type problems ✔️ Nice practice for handling adjacent collisions efficiently Overall, an engaging medium-level problem with practical use of stack.