Loadable – Simplifying Async Data Handling in React

Hacker News

Hi HN, I'm excited to share a project that I've been working on - Loadable, a new NPM package to help reduce boilerplate and simplify handling asynchronous data in React applications. Features include: Loading State Management: Manages the loading state for you, removing the need for manual management. Error Handling: Handles errors during data fetching, providing a unified way to deal with potential issues. Data Fetching Based on Dependencies: Fetch data based on dependencies, similar to useEffect. Support for Synchronous and Asynchronous Functions: Can work with both sync and async functions. Type-Safe: The library is fully typed, offering strong TypeScript support. Check it out here: https://www.npmjs.com/package/@tobq/loadable Feel free to follow me at [@tobi_akin]( https://twitter.com/tobi_akin ) Feedback and suggestions are very welcome, as I'm hoping to make this as useful and practical for you all as possible.

Visit product View on Hacker NewsMay 21, 2023

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

73%73% 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.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

41%41% 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

39%39% 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

13%13% 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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