'git inject' – amend commits other than HEAD

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'git inject' is a git alias (see code at the bottom). It is similar to 'git commit --amend', but it allows you to 'inject' your changes into commits further back in history (using 'rebase'). If you're as pedantic as I am about the git history you're about to push into master (as far as I can control it, I strive to keep each commit conceptually coherent), you'll often come to a situation where you have a modification that really belongs in an older commit. It takes a few git commands to stash other changes away, commit the modification, then interactively rebase over some previous commit, move your commit into place, change to 'fixup', save, exit, and then unstash whatever else you had lying around. Not fun. Here's how 'git inject' makes it fun: >> git inject <commit-ref> <patch-ref> >> git inject HEAD^^ -a # inject all work-dir modifications >> git inject a28kd8 -p # interactively select patches to inject >> git inject HEAD~4 file1 # inject the modifications in file1 Just put this into your .gitconfig under 'aliases': inject = "!f() { set -e; HASH=`git show $1 --pretty=format:\"%H\" -q`; shift; git commit -m \"fixup! $HASH\" $*; [ -n \"$(git diff-files)\" ] && git stash && DIRTY=1; git rebase $HASH^^ -i --autosquash; [ -n \"$DIRTY\" ] && git stash pop;}; f"

Visit product View on Hacker NewsJun 12, 2015

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, code · Missing: mac, agents, macos

78%78% 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.

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

52%52% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% 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

45%45% 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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

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