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Listak – Save lists from IMDB and Letterboxd as CSV files

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Listak – Save lists from IMDB and Letterboxd as CSV files

I love movies, and I'm always on the lookout for interesting ones that I don't know about. Lists from users on IMDB and Letterboxd seem to quench that curiosity, but I often prefer to keep things offline for the sake of posterity and portability. I made a simple website that takes a link of a user's list and gives you back a CSV file of that list. Some Caveats: – The IMDB API used is rate-limited to 100 daily requests. – Letterboxd denied me access to their API, so I went scraping, which takes some time (approx. 120 entries per minute.) I hope others find this useful; any feedback is welcome.

Visit productView on Hacker NewsJun 25, 2023
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Indie HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, users, way · Missing: mobile apps, personal, entrepreneurs
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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