Turn Scripts into Shareable Apps with Windmill

So I was making a VS Code extension and made a request that apparently isn't supported. Instead of saying "no" the agent spent half an hour writing Python code and dig the guts of the IDE to find how exactly it works to give me what I asked for! I mean, I appreciate the effort but one of my code principals is to "Never fight the tool" (the tool being the VS Code Extension API in this case). Thought it was fun to share but don't worry for me. I'll tighten it up. While you're here, don't forget to set the "Chat: Font Size" to something readable. It's easy to ignore what the agent is doing (and if you're not an engineer it's totally fine) but for an engineer, it's important to understand the tool and what's going on.

Python Async vs Threading (Truth) ⚡ Async or Threading… which one is better? 🤔 Most developers are confused here ❌ Content: Let’s break it simply 👇 ⚡ Threading → Multiple threads run at the same time → Good for I/O tasks (API calls, file read) → But limited by GIL in Python ⚡ Async (async/await) → Runs tasks without blocking → Best for high-concurrency apps → Used in FastAPI, modern backends 🚀 Simple difference: 👉 Threading = Multiple workers 👉 Async = One smart worker handling many tasks What beginners do: ❌ Use threading everywhere ❌ Don’t understand blocking What smart devs do: ✅ Use async for APIs ✅ Use threading for simple tasks ✅ Choose based on problem Why this matters: Right approach = better performance 💯 Reality: There is no “best”… Only what fits your use case Pro Tip: If you're building APIs → learn async first 🚀 CTA: Follow me for real backend knowledge 🚀 Save this post for revision 💾 Comment "ASYNC" or "THREAD" 👇 #Python #Async #Threading #Backend #Programming #Developer #FastAPI #Coding #SoftwareEngineer #Tech

I have been thinking less about agents and more about paths. A lot of software still assumes execution is: - an app flow - an async mesh - or an agent stack But human work usually looks messier and more real: you carry something, fork, test, return, defer, resume, and only sometimes settle. So I have been exploring a path-style runtime where: - push opens a fork - pop rejoins or abandons a fork - skills attach to the path - memory keeps residue - repeated signals reinforce instead of just duplicating noise The interesting question is not “what is the next token?” It is more like: - what is still being carried? - what changed direction? - what can be deferred? - what actually needs to settle? I may post a tiny Python demo of path execution next. https://lnkd.in/eairkdJK #runtime #systems #paths #softwarearchitecture

Standard Python debuggers are great—until your app freezes, a child process hangs, or the whole thing crashes before it can even spit out a traceback. 📉 When the process you're debugging "flatlines," you usually lose all visibility. That’s why I built Flatline. It’s an open-source debugger designed for the failures that normal workflows handle poorly: GUI freezes, startup failures, and silent crashes. Instead of relying on the child process to report its own death, Flatline uses an external watchdog to keep you in control. Core Features: Heartbeat Monitoring: Detect freezes in real-time. Child-Process Supervision: Parent-side oversight for subprocess-heavy tools. Crash Console Access: Inspect what happened even when the target is unstable. Force-Kill & Restart Workflow: Clean up and iterate without manual PID hunting. Whether you're building desktop apps or complex subprocess-heavy systems, Flatline gives you the "parent-side" perspective you’ve been missing. Check it out & give me your feedback: 🚀 TrentonTompkins.com #Python #OpenSource #Debugging #SoftwareEngineering #Flatline #BuildInPublic

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

Most developers think clean code is enough. It’s not. You can have beautiful code... And still crash under real traffic. Because production doesn’t care about readability alone. It cares about: • Concurrency • Timeouts • Memory usage • Database locks • Retry storms • Load spikes Clean code matters. But resilient systems require more than clean code. Software that reads well is useful. Software that survives is valuable. #BackendDevelopment #SoftwareEngineering #SystemDesign #Python #Scalability

Debugging didn’t make me slower — guessing did. The moment I started automating my debugging workflow, everything changed. Small habits like validating inputs, retrying failures, and logging execution time quietly saved me hours every week. Speed in development isn’t about typing faster — it’s about finding problems earlier. Automation doesn’t just scale systems. It scales developers. #Python #Debugging #Automation #SoftwareDevelopment #Productivity #Developers

Streamlit aids operations, not just B.I. This Python framework builds data-centric apps. While most people use it for dashboards and predictive model interfaces, clever backend development transforms it into a workflow management platform. Here, I demonstrate an I.T. ticket management system. It shows the current status of all tickets and has a dashboard for team performance tracking. The backend is an event log - a data structure that enables time-aware analytics, transfer tracking, and more. Thankfully, Streamlit's syntax is simple, which made development quick and easy. In short, you can build fully custom workflow tools in just a few hours. How do you use Streamlit? #Operations #BuildVsBuy #Python

🚀 LAUNCH ALERT: Mega-Net BuildBuddy is LIVE You don’t need to struggle with code anymore. Meet Mega-Net BuildBuddy — your AI-powered Senior Python Developer on demand. Stuck on a bug? Confused about logic? Tired of jumping between Google, StackOverflow, and YouTube? BuildBuddy steps in like a real mentor 👇 ⚡ Explains code clearly ⚡ Helps you debug faster ⚡ Writes clean, production-level Python ⚡ Guides you like a senior dev beside you No fluff. No noise. Just real help when you need it. Whether you're: • A beginner trying to understand Python • A student working on projects • A developer tired of wasting time This changes how you build. 💥 Stop searching. Start building. Get it now 👉 https://lnkd.in/er2F6YiC — If you're serious about leveling up your Python skills, this is for you. #Python #BuildInPublic #AItools #Developers #MegaNet #TechNigeria

Debugging Python Like a Pro 🔥 Stuck in a bug for hours? You’re debugging WRONG ❌ Content: Most developers panic when code breaks… But smart developers follow a process 👇 Here’s how pros debug Python: 🔍 Read the error carefully → Python already tells you what’s wrong 🔍 Use print() smartly → Check values step by step 🔍 Break the problem → Don’t debug whole code at once 🔍 Use a debugger (VS Code / PyCharm) → Track execution line by line 🔍 Google the exact error → Someone already faced it 😄 What beginners do: ❌ Guess the problem ❌ Change random code ❌ Get frustrated What smart devs do: ✅ Follow a step-by-step approach ✅ Stay calm ✅ Solve logically Why this matters: Debugging is 50% of a developer’s job 💯 Reality: Good developers are not those who don’t make bugs… They are the ones who fix bugs faster Pro Tip: Don’t fear bugs… They are your best teachers 🚀 CTA: Follow me for real coding skills 🚀 Save this post for debugging 💾 Comment "DEBUG" if you relate 👇 #Python #Debugging #Programming #Developer #Coding #PythonTips #SoftwareEngineer #Developers #Tech #LearnPython