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Quick install script for self-hosted Forgejo (Git+CI) server

Hacker News

Quick install script for self-hosted Forgejo (Git+CI) server

I wanted to get Forgejo on my VM on a local NAS fast, and I realized that getting everything running with Git and CI working was ... harder than I anticipated. After spending more time than I wanted, and bugging lovely people at Forgejo's matrix, I came up with this: https://wkoszek.github.io/easyforgejo/ With this script, you should get Forgejo installed on your Linux computer in 2min. I tested this on a VM for now, and it works well enough for beta launch. Repo is here: https://github.com/wkoszek/easyforgejo Let me know what you think and submit PRs if you find bugs. I'd not use it in production just yet.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: computer · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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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