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Stree”: Enabling Tree View for Your S3 Buckets Made Simple
Hacker NewsStree”: Enabling Tree View for Your S3 Buckets Made Simple
Hello AWS users, Allow me to introduce the CLI tool “stree”, facilitating a tree view of your S3 bucket structure. Available on Linux, Mac, and Windows. Features: - Easy file management through tree view visualization - Fast and lightweight - Open-source and community-driven development Feel free to download it from https://github.com/orangekame3/stree and share your feedback. Thank you!
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, user, visual · Missing: agents, macos, agent43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal28%28% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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