Scrape TikTok data at scale, including videos, captions, hashtags, stats, sounds, and user profiles. Perfect for trend analysis, influencer research, marketing insights, and dataset creation. Fast, accurate, and ideal for automated TikTok intelligence.
0.2 — Base finalize (trust-bug fixes + labeled fields)
⚠️ followers category now logs an honest, explicit warning when the underlying data source returns 0 results (previously a silent empty result with no explanation). following is unaffected.
🧹 Removed the dead user_playlists category from the schema and code (it never called any endpoint).
🧹 Removed the marketing/contact line from the input description.
🕒 Added publishedAt (ISO-8601) and scrapedAt to every output record.
🔗 Added canonical deep-link URLs to every applicable record: videoUrl, profileUrl, hashtagUrl, musicUrl.
🖼️ Promoted previously-unlabeled fields to dataset-view columns: HD no-watermark video link (hdplay), all 3 cover-image variants, the full music_info sound object, the commenter's bio/region/verified/follower-count snapshot, and the user_info profile's stats block + bio link + cross-platform handles (Instagram/Twitter/YouTube).
🔒 Scrubbed 11 internal log lines that leaked raw exception text / full tracebacks (exc_info=True) into the buyer-visible run log; replaced with neutral, non-leaking messages.
📄 Rewrote README.md for accuracy (matches the current schema exactly, no more user_playlists) and SEO.
0.1 — Initial release
🎬 Scrape public TikTok user data: videos, favourite videos, followers, following, user info and in-profile search.
💬 Scrape video comments with optional nested replies.
#️⃣ Scrape videos by hashtag (with region localization).
🎵 Scrape videos by music / sound.
▶️ Scrape videos by playlist (mix).
📹 Retrieve full single-video detail records.
🛡️ Automatic proxy escalation ladder: direct → datacenter → residential (sticks with residential once engaged, 3 residential retries).
💾 Live, per-record saving to the dataset with retry + backoff on every request.
