Explicit API Ecosystem
A concise breakdown of the specific libraries and paradigms powering our integrations across eight platforms. We prioritize reverse-engineered and battle-tested unofficial avenues where Official Graph APIs enact massive friction.
⬇️ Download Full Developer Implementation Reference (.MD)Telegram Telethon
The native Telegram Bot API suffers massive limitations regarding file sizes (20MB) and cannot natively scrape historical channel messages easily. We use Telethon, a fully asynchronous MTProto Python wrapper, to impersonate native User-Bot sessions. This achieves unlimited historical extraction and file downloads up to 2GB directly to local disk.
Instagram instagrapi
The official Instagram Graph API requires a complex Facebook Business account linkage that ruins indie scaling. Instead, we use instagrapi, which perfectly spoofs iPhone/Android HTTP traffic. By saving session token files locally, we avoid Challenge-Required logic while natively iterating user nodes.
Twitter / X twitterapi.io
Because Elon Musk disabled the free API tiers, web scraping X via Selenium is the only free technical method, but it is constantly met with Captcha walls. We pay a fractionally microscopic cost via the twitterapi.io un-official REST abstraction. It returns purely clean JSON covering tweets, comments, and CDN MP4 links.
Reddit PRAW
Reddit remains developer-friendly. We use the official PRAW wrapper tied natively to OAuth. It excels tremendously at unrolling deeply nested comment trees instantly via replace_more operations. However, it cannot natively extract raw video binaries easily due to DASH fragmentation.
Hostile DOMs Playwright
For Facebook (impossible graph approvals), Medium (strips API text formatting), and YouTube (blocks automated bot uploads), we enforce a purely visual headless browser layer using Python Playwright. Playwright simulates physically scrolling DOM nodes to trigger lazy-loads, scraping comments iteratively without API limits.
Video Core yt-dlp
Playwright cannot save intercepted DASH streams efficiently. We explicitly delegate 100% of global video downloading (from YouTube to Reddit) to the highly robust yt-dlp. Invoking it via Python subprocess, we parse its real-time stdout to pipe percentage completion natively into our UI.