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Scoop – A command-line installer for locked down PCs with Powershell 2

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Scoop – A command-line installer for locked down PCs with Powershell 2

I'm a lead contributor to the Windows command-line installer, Scoop. Previously, Scoop only worked with Powershell 3+, but due to the silly number of PCs running basically stock versions of Windows 7 (or earlier) with Powershell 2 available, I saw the opportunity to bring Scoop to these machines. On a personal note, I'm a student at the University of Newcastle, Australia that has many PCs as described above. You don't have admin access (for obvious reasons) and you can't install anything. Downloading and using portable apps is possible but painful when the list of things to install gets big. So, over the last weekend I've back-ported Scoop to Powershell 2 (with the help of a few libraries) and I was hoping to get some patient HN users to test it out if they have access to PCs as described. The install process is basically the same as on the Scoop site (http://scoop.sh/) but you need to run a different install script which I'll provide below: set-executionpolicy unrestricted -s currentuser #enable powershell iex (new-object net.webclient).downloadstring('https://raw.githubusercontent.com/lukesampson/scoop/powershell2/bin/install.ps1') I'm pretty sure most things work (I have been testing on a fresh Windows 7 VM). The biggest problem so far is that jq (JSON parser) is slow (or my programming is crap). So installing something with a big .json file (like busybox) takes about 25 seconds to load into a Powershell object.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
80%80% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
60%60% 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 HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, user · Missing: agents, macos, agent
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive
52%52% 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
15%15% 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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