Conjugate, Golang CLI tool that converts YouTube Music to Spotify links

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I've started work on a tool that I envision will allow users to easily convert links from one music streaming service to another. The reason for it's existence is I was tired of opening Spotify to search a link to a song I'm trying to show someone, since nobody I know uses YouTube Music, and I really don't want to use Spotify. Right now it only supports converting Youtube Music links to Spotify, as that is my use case, but the framework is there for other streaming platforms that expose APIs. I made it because I'm envisioning a tool built on top of it that can port playlists between services, perhaps even in real time - so that collaborative playlists across platforms becomes possible. The biggest challenge I'm facing right now is the fact that YouTube Music does not have any public API at all as far as I can tell, limiting me to the YouTube Data API, which is not ideal. Spotify seems to have a lovely API though! It's very early stages, but if the idea interests you, let me know what you think! https://github.com/kn100/conjugate/

Visit product View on Hacker NewsOct 11, 2020

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, apis, open · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

38%38% 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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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