Merge Folders from the CLI

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Whenever moving folders with folders which have the same names I would always wince when seeing "directory not empty" or "destination already exists" and then immediately give up and use a GUI file manager. The existing solutions all have caveats: mv ./src/* ./dest/ oops no dotfiles ?! but also this will fail if any of the globbed subfolders have subfolder conflicts (and it will silently move globbed folders into subfolders of the same name--I can't imagine this is what most people assume it is doing) rsync --remove-sent-files rclone move rsync and rclone will copy the files to move them which can be very slow when renaming is all that is needed So I've created my own which uses BSD syntax: pip install xklb library merge-mv folder1 folder2/ # folder1 will go inside folder2 library merge-mv folder1/ folder2/ # folder1 will be merged with folder2 https://github.com/chapmanjacobd/library/blob/main/xklb/fold...

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

74%74% 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.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · 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.

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

23%23% 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

12%12% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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