Protecc, a Missile Command-like game made with Paper.js and Netlify

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Try it out here: https://www.playprotecc.com Why Paper.js? I was looking into Javascript libraries so I could start prototyping this (Three, Pixi, and Phaser were the initial frontrunners) and I stumbled across this HN thread: https://news.ycombinator.com/item?id=23083730 Comments warned against using Paper.js for games, as it “isn’t meant to handle thousands of rectangles,” but praised it for its path-manipulating capabilities. Seemed like a promising enough lead to follow for that reason - the game is heavy on "wiggles" and I wasn’t keeping thousands of shapes on the screen at any one time - so I figured it was worth investigating. I have to say: it absolutely was. I'd highly recommend it for a lot of different of 2D projects. It was so versatile and easy to use that I ended up building a couple small buttons and modals with it too (although this was partly because I didn't want to leave PaperScript-world). Major thanks to Netlify, too. They made setting this up a breeze.

Visit product View on Hacker NewsMar 3, 2021

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2points

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

75%75% 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 · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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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