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Beginners level Python guide for making a “Py-pet” tamagochi
Beginners level Python guide for making a “Py-pet” tamagochi
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Analyze your own launch →49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
26%26% predicted probability of success on BetaList, based on ML models trained on real launch data.
25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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