Save and Restore Window Layout on Mac

Hacker News

I recently started experimenting with using my 45in 4k TV as a monitor for my Mac. Having all of the apps I use open and visible at the same time had been great for productivity, but I noticed mac doesn't consistently save and restore the window layouts I configured, so I often had to spend a lot of time rearranging windows. I was't able to find a better solution via a quick search so I decided to write this script. It's a simple python3 script with no external dependencies that runs apple scripts to save and apply layouts. You can have multiple layouts for the same resolution saved under different names. Currently it only tracks one window per app since that covered my needs. Feel free to make a PR if you'd like to help add support multiple windows. I'd love to hear your thoughts. Please leave a comment below and let me know if you've found it helpful!

Visit product View on Hacker NewsJul 14, 2023

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

86%86% 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.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

35%35% 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

35%35% 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

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% 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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