The Tao of tmux, available for free on the web, has been newly edited

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Hi, Last year I began a book for learning tmux called The Tao of tmux . It is based off a free resource originally part of the documentation [1] of tmuxp, a tmux session manager [2]. I made it available for free online at https://leanpub.com/the-tao-of-tmux/read . Since February of this year, I have incorporated suggestions and feedback from readers on quality and completeness of the book. For one, I have passed the book through a professional editor, as well as rounded out chapters with summaries and even added 3 new sections, including: - Sending keys to tmux, aka `send-keys` - Copying pane contents to the paste buffer programmatically, aka `capture-pane` - Building and using tmux-mem-cpu-load [3] Countless areas of the book have been rewritten for clarity. The process of editing alone fielded over 650 tweaks. New graphics have been added. The configuration chapter has been overhauled, and various new examples of usage for targets (`-t`) [4] and formats (`-F`) [5] have been added. The book is available for purchase on Leanpub, in DRM-free epub, mobi and pdf format at https://leanpub.com/the-tao-of-tmux . In addition, the book is available on Amazon Kindle at https://www.amazon.com/gp/product/B01MG342KU . The book will always be available for free on the web. P.S. If you found this book helpful, please review on Goodreads [6] and Amazon [7]. [1] https://tmuxp.git-pull.com/en/latest/about_tmux.html [2] https://tmuxp.git-pull.com [3] https://github.com/thewtex/tmux-mem-cpu-load [4] http://man.openbsd.org/OpenBSD-5.9/man1/tmux.1#COMMANDS [5] http://man.openbsd.org/OpenBSD-5.9/man1/tmux.1#FORMATS [6] https://www.goodreads.com/book/show/33246223-the-tao-of-tmux [7] https://www.amazon.com/gp/product/B01MG342KU

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

78%78% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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: way · Missing: mobile apps, ios, personal

27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% 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

13%13% 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.

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