qme: simple utility for queueing long-running commands

Hacker News

I keep needing a way to run long-running resource intensive tasks after one another. Normally, I'd write a script which loops over the items, but not knowing what needs to run (I pick files as I go through a folder), I knew it's time I create something to scratch my own itch. So, I've created this utility to queue up commands. It captures command, args, env and working directory and puts it in a queue, and runs it when it's time. At the same time, it spins up an RPC server to receive commands from other instances. If there's no server available, it becomes a server itself and waits for commands or shuts itself down after idling for some time. This is my first (published) Golang project, so guidance & review would be appreciated.

Visit product View on Hacker NewsJan 21, 2022

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

70%70% 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.

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

49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

29%29% 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

22%22% predicted probability of success on AppSumo, 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

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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