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Conjure_enum – a C++20 enum and typename reflection Library

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Conjure_enum – a C++20 enum and typename reflection Library

We're pleased to announce the release of v1.0.1 of conjure_enum, a lightweight header-only C++20 library designed to streamline working with enums and typenames by providing simple reflection capability. Yes, there is magic_enum - and we based this implementation on the core of magic_enum, but refocused for C++20, using some of the key features of this newer language version such constexpr algorithms, std::source_location, std::to_array and concepts; we also improved and expanded the API.

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Product HuntUnlikely to reach the leaderboard · Strong signals: new, using · Missing: mac, agents, macos
43%43% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
34%34% 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
32%32% 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: arr · Missing: mrr, revenue, profit
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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

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