A Wasm to Go Translator

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I've spent the past couple of weeks building a Wasm-to-Go translator. It supports a subset of Wasm useful enough to translate SQLite into 600k LoC (~20 MiB) of Go code. It already passes all of my Go SQLite driver's tests across the 20 platforms I support. Performance compared to https://wazero.io/ is a bit of a mixed bag: code that frequently crosses the Go-Wasm boundary improves, but code that spends most of its time in "Wasm land" doesn't. There's probably room for improvement (I'd love to hear your ideas), but this is also a testament to how good the wazero AOT compiler actually is. You can get a feel for the generated code by looking into https://github.com/ncruces/wasm2go/tree/main/testdata I should eventually spend some time ensuring the translator passes the spectest, though I suspect that'll be far less fun than building the translator itself was.

Visit product View on Hacker NewsFeb 26, 2026

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

74%74% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

17%17% 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.

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