Xf

XferLang, a data-transfer and configuration alternative to JSON

Hacker News

XferLang, a data-transfer and configuration alternative to JSON

About nine months ago I posted ( https://news.ycombinator.com/item?id=42114543 ) about a language I had begun experimenting with, called XferLang. I got several helpful comments, and since then I've completely revamped the design and built a complete language spec and library around it. I've even integrated it into some apps I use daily. The language, intended to be an alternative to JSON and YAML, is a strongly typed, human‑readable/writable, structured text language. Where it differs from JSON is support for comments, strict typing of data, support for processing instructions (which are extensible), nascent scripting features, and embedding of text without the need for character escaping. Right now it is implemented in a .NET 8.0 library, but I want to port it to other languages as well. I would really appreciate any critiques on the language's ergonomics, any opinions on its real-world applicability, and any reasons you would or wouldn't adopt something like this over JSON/YAML/TOML. Thanks for your feedback!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
70%70% 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 HuntOn track for Day 1 leaderboard · Strong signals: apps, new · Missing: mac, agents, macos
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, month · Missing: mobile apps, ios, personal
47%47% 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
45%45% 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
16%16% 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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