Visualize Swift Package and Xcode Project with Interactive Graph

Hacker News

When I decided to modularize my iOS project with SPM, I thought that visualizing a package with its dependencies in a graph would be very helpful and intuitive. However, every time I needed to see the graph of any package in my local package list, I found it very inconvenient to write the command to create the dot file in the terminal. It was even hard to see. Therefore, I created SwiftDeps( https://swiftdeps.com ) to make these tasks faster and easier and to improve work efficiency. SwiftDeps is a MacOS application created to help you visualize your Swift Package or Xcode project as an interactive graph. It is well suited for building projects with a modular architecture. With such a visual graph, you can see the interdependencies between objects in your project or in a Swift package. In addition, the application also helps you check for new updates for the Swift packages you are using. Furthermore, Swiftdeps also identifies any issues in your project such as circular dependencies, orphaned packages, etc.

Visit product View on Hacker NewsMar 22, 2023

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Launch Intel predictions

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

81%81% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

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

TrustMRRFits verified-revenue profile · Strong signals: ios, visualize · Missing: mobile apps, personal, entrepreneurs

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

14%14% 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.

Correct prediction on native model

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