Slangify
Power up your Domain Specific Language.
Design your DSL. Create a Grammar to Parse your syntax. Slangify is here to show you how. We focus on why, where & how to use Raku Grammars.
Write grammars the same way you write functions or classes. Build your language with native semantics, composition, tooling and flow.
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DSLs are a secret weapon for LLM effectiveness because their human-readable, domain-centric structure constrains both the training set and model outputs, making them significantly easier for LLMs to generate accurately.
Why does parsing still feel like a chore?
Most languages treat parsing as an afterthought — something you bolt on with a library, define in a string, and hope behaves.
Why should parsing require a module install?
Why define your grammar as a string, separate from your code?
Why number your capture groups?
Why can't you extend a grammar like a class?
Why treat non-ASCII text as a special case?
What if ...
A grammar is a class. Tokens are named. The parse tree is instant.
grammar DateParser {
token TOP { <year> '-' <month> '-' <day> }
token year { \d ** 4 }
token month { \d ** 2 }
token day { \d ** 2 }
}
my $m = DateParser.parse("2026-05-12");
say $m<year>; # ｢2026｣ named, not positional
say $m<month>; # ｢05｣
say $m<day>; # ｢12｣
In Raku, a Slang is a user-defined Domain Specific Language - an embedded DSL.
Defined by a Grammar and its Actions, Slang code may be written seamlessly within any Raku code - it becomes part of the wider language.
Slangify is the tool that extends the native syntax in a single line of code. It's the simple and powerful way to make your DSL come alive. Either as an an embedding, or as a stand-alone user tool or both.
Easy to make, easy to use and easy to maintain.