data-scraper-agent

Automate web scraping without hosting fees by running Python scripts via GitHub Actions, then exporting the collected data directly into a Notion workspace. This approach uses free cloud infrastructure to schedule and execute data collection tasks.

Yes, you can scrape public websites on a schedule using Playwright and BeautifulSoup within GitHub Actions. These Python libraries parse HTML and render dynamic content, allowing automated collection at scheduled intervals without a dedicated server.

Enrich scraped web data by processing the raw information collected from public sources with free AI tools like Gemini Flash. This enhances the dataset automatically, adding context or categorization before saving it to your storage platform.

Yes, this data collection method supports exporting results to both Google Sheets and Supabase. It uses specific client libraries to format and push the scraped and AI-enriched data directly into these cloud storage platforms.

The best way to track competitor prices and job listings automatically is to configure a Python scraper to monitor public sources at scheduled intervals. The script collects the data, enriches it with AI, and stores it in your chosen database.

Yes, you need Python and cloud storage access to use this automated data collection agent. The workflow requires configuring Python scripts, setting up GitHub Actions for execution, and connecting to platforms like Supabase or Google Sheets.