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Generate ASCII Charts on iOS

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Generate ASCII Charts on iOS

After having seen some charts made with text, I had the urge to create a chart generator that could run on iOS. After having converted the great asciichart from Python to Swift, I've created a small utility app using SwiftUI & SwiftData. Here is an example of chart generated from the app: 18┼╮ 17┤│ 15┤╰╮ 14┤ │ ╭╮╭╮ 12┤ ╰──╯│││ 10┤ ╰╯╰╮ 8,8┤ │ ╭╮ ╭╴ 7,2┤ │ ╭─╮╭╯╰╮│ 5,6┤ ╰╮╭╯ ││ ││ 4┤ ││ ╰╯ ╰╯ 2,5┼ ╰╯ Would be happy to answer your questions & suggestions!

Visit productView on Hacker NewsDec 6, 2023
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Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
71%71% predicted probability of success on TrustMRR, 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: using · Missing: mac, agents, macos
53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% 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
22%22% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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