Working on a new project now that I've always wanted to do. Hope it works! 🤞

Just released Prism — a simple way to bridge your social presence. Built with #FastAPI and #Python, it’s designed for those who want to stay active on both Bluesky and Mastodon without the double effort. Check it out: https://github.com/cmodi306/prism-app

Hello from #Prism!

Posting from #docker deployment. Its working !!

test again from #docker

test in docker

This is a test message from my #Prism app, developed in #python.

Test 2 from my self-hosted #python app.

Test from my self-host #python app.

Test post 2.

Test post.

[test]This is a sample post of #parallelposting to test posting from #python script on #mastodon and #bluesky. To test, I am including links like example.com and google.com. Happy coding!

[Test]This is another example of adding links and #hashtags like google.com, yahoo.com from my #python script. Adding a third link, here is microsoft.com.

[Test]This is another example of adding links and hashtags like google.com, yahoo.com from my python script. Adding a third link, here is microsoft.com.

[Test]This is another example of adding links like google.com, yahoo.com from my Python script. Adding a third link, here is microsoft.com.

[Test]Testing inclusion of links example.com and further otherexample.com in the post from my #python script.

[Test]Testing inclusion of links example.com and further otherexample.com in the post from my #python script.otherexample.com

[Test]Testing inclusion of links example.com and further otherexample.com

[Test]Testing inclusion of links example.com and further otherexample.com in the post from my #python script.

[Test]Testing inclusion of links example.com and further otherexample.com in the post from my #python script.

Hello World from Python SDK

[Test]Testing inclusion of links example.com and further otherexample.com in the post from my #python script.

P.S.: please excuse the name as it does not send any alert, just analyses the market price.

GitHub - cmodi306/stock_market_alert Contribute to cmodi306/stock_market_alert development by creating an account on GitHub.

I recently created a lightweight web app that analyzes a stock portfolio against recent market performance using FastAPI and yfinance. It pulls real-time data and compares the current value of each position to its highest price over the last 30 days. Here's the link:
github.com/cmodi306/sto...

One of the many reasons why you shouldn't blindly accept the results that an LLM gives you.

Wanted to make a #Python web app that monitors the stock market price. Yeah there are number of them out there but want to build something by myself. There is still some work to be done but this is how it currently looks like... Feel free to clone and modify the code:
github.com/cmodi306/sto...

Adding More Sensors Won’t Fix Your System—Here’s What I Learned the Hard Way Many automotive brands argue about the usage of sensor for driving assistance systems, claiming that theirs is the best. The question is, is theirs really flawless? If not, what is actually the perfect sensor system? You know, the magical combination of LiDAR, radar, cameras, GNSS, IMU, ultrasonic, thermal, probably a ToF sensor duct-taped somewhere, that will finally make perception flawless. No edge cases. No missed detections. No weird false positives in foggy industrial zones. Just clean point clouds, crisp images, and perfectly aligned timestamps flowing through ROS2 like a garden of messages.

Adding LiDAR, IMU, GNSS… I thought more sensors would fix everything. It didn’t. Here’s what really matters in sensor systems.

#sensors #robotics #ros2 #RoboticsCommunity #SelfDrivingCars #AutonomousVehicles #AutonomousDriving #SensorFusion

Believing that with enough sensors, you can eliminate all problems in your robotics application is a myth. It’s a linear mindset applied to a non-linear system.

#robotics #ros2 #python #sensors

chatgpt, python

This artificial intelligence is getting a little too intelligent now.

I quit writing Docstrings. ChatGPT is my new Documentation Intern. If there’s one thing Python developers collectively agree on, besides PEP 8 and the fact that "import this" is a fun Easter egg nobody uses, it’s this: writing documentation is that one task we all procrastinate harder than cleaning the lint filter in a shared apartment dryer. We all want clean, readable docstrings and user guides. We also want to keep shipping features, fixing bugs, and pretending that “I’ll document it later” is a real plan. Spoiler: it never is. But we’re in a pretty interesting era now. Large language models—ChatGPT included—aren’t just toys for generating fantasy world lore or “explain quantum physics like I’m five.” They’ve quietly become extremely competent at turning your messy Python source tree into documentation that won’t embarrass you in front of other developers.

Devs, I've stopped manually documenting my Python code. I'm letting ChatGPT handle the mess.

I break down exactly how to use ChatGPT to generate docstrings, module overviews, and even README content — without losing control of your code or style. Check out my new blog on using #ChatGPT for #Python.