Automate Internet Speed Monitoring with Python Bot & Google Sheets

Automate Internet Speed Monitoring with Python Bot & Google SheetsAutomate Internet Speed Monitoring with Python Bot & Google Sheets

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Ali Ahmed Dar

• Feb 2

I developed a Python-based automation bot that monitors internet speed and logs download/upload values every 15 minutes. The data is saved in real-time to a Google Spreadsheet, along with timestamps and direct result links from Speedtest.net. The bot can run silently or display a GUI countdown. It helps remote teams, IT professionals, and analysts track internet stability over time.

Automation Engineering Data Engineering pandas Python Selenium AI Automation

Sonu Kumar

• Feb 22

Building something exciting 🐶🚀

Just launched Pawsy AI an AI-powered dog behavior coach that helps pet parents fix barking, biting, anxiety, and more in just 7 days.

Instead of expensive trainers or random YouTube advice, Pawsy AI creates personalized training plans using intelligent behavior analysis.

• AI diagnosis

• Custom daily exercises

• Progress tracking

• Adaptive coaching

$29/month subscription model

Design + product + positioning built from scratch.

Try it: https://powsai-app.bubbleapps.io/version-test/index?debug_mode=true

Would love feedback from fellow builders. 👇

Bubble AI Automation profitwithbubble

Sonu Kumar

• Feb 22

Pawsy AI an AI-powered dog behavior coach

NoCodeMinute LLC

• Feb 23

🚀 I built AutoPilot by NoCodeMinute on Bubble to help businesses automatically generate and schedule social media content across platforms in minutes instead of hours. It uses a simple subscription model where customers pay monthly to automate posting, save time, and scale their marketing with AI-powered workflows.

Bubble Development AI Development OpenAI Bubble profitwithbubble

Theo Goldberg

• Feb 23

This is awesome Jason!!

Agustin Peri

• Feb 23

When I joined the team, social media metadata and posts were being uploaded manually. The process was repetitive, time-consuming, and not scalable. It limited the volume of data we could handle and increased the risk of inconsistencies and human error.

I proposed replacing the manual workflow with an automated ETL pipeline. Using Python and version-controlled workflows in GitHub, I built a system to extract data directly from social media APIs, transform and standardize the datasets, and load them into BigQuery.

The result was a fully automated, scalable pipeline with validation controls and traceability. What used to require daily manual intervention became a reliable production process capable of handling large volumes of data efficiently.

Data Engineering data etl