WASI socket extensions for Go 1.21

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The WASI preview 1 specification was missing socket APIs so some WebAssembly runtimes added extensions to allow applications to do more than basic file I/O. This package enables a large class of Go programs (almost any program doing networking) to run when compiled to WebAssembly using the WASI preview 1 spec. It exposes functions similar to net.Dial and net.Listen that can be used to leverage the socket extensions thanks to the new //go:wasmimport compiler directive. It also has a set of examples of how to use popular Go packages when compiling to GOOS=wasip1. Contributions and feedback are welcome, give it a try and let us know what you think!

Visit product View on Hacker NewsJun 13, 2023

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

74%74% 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 · Missing: supports, reddit linkedin, podcasting

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

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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

18%18% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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