Most scrapers just grab everything and leave you to sort it. Moorelink is different: • State-aware fetching prevents redundant API calls and respects rate limits. • Asynchronous multi-platform ingestion lets you fetch X, Instagram, and Facebook in parallel. • Structured JSON output delivered directly to Telegram for actionable consumption.
It’s built with Python, Asyncio, PostgreSQL, and Telegram API, and is designed for personal or research use.
Demo & code: • GitHub: https://github.com/smintech/Moorelink-Socials • Video demo: LinkedIn
I’m curious how other developers approach reducing cognitive load while scraping or processing social media data. Any thoughts or alternative patterns you’ve found effective?
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