Dockerized – Run CLI tools without installation

Hacker News

Dockerized is like npx for unix tools: Run popular cli tools without installation. Example: dockerized npm init dockerized python2 somescript.py Run an older version of a tool: NODE_VERSION=15.0 dockerized node Use cases: - Maintaining multiple versions of an app - Installing without polluting host machine - Quickly run some commands you may not have installed Features: - intuitive use. Just the original command, but with 'dockerized' in front. - dockerized apps can access the current directory and read/modify files, just like native apps. - no need to know which docker image this package comes from. - support for tools which don't have an official docker image. - container cleaned up after use. - ability to specify the version. - version specification per directory (share exact versions with your team mates). The inner workings are pretty simple, it's just a docker-compose file. As expected with dockerization, there are limitations related to networking, and file persistence (outside current dir), but it can make life easy for simple scenarios. Pull requests welcome!

Visit product View on Hacker NewsMar 10, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, dock · Missing: agents, macos, agent

58%58% 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.

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

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

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

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

15%15% 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.

Incorrect prediction on native model

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