Redis Lua Development and Debugging with ZeroBrane Studio

Hacker News

A new plugin for ZeroBrane Studio that enables developing and remotely debugging Redis Lua scripts. More details at: * Short video overview: https://www.youtube.com/watch?v=7mlajCj4QPw * Blog post: https://redislabs.com/blog/zerobrane-studio-plugin-for-redis-lua-scripts * The Redis plugin's repository: https://github.com/pkulchenko/ZeroBranePackage/blob/master/redis.lua * ZeroBrane Studio website: http://studio.zerobrane.com

Visit product View on Hacker NewsJan 4, 2016

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released

79%79% 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 · Missing: plus, platform, intuitive

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

21%21% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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

12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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