A JavaScript library for creating tagged constructors and sum types with minimal boilerplate.
Daggy is a JavaScript library for creating tagged constructors and sum types, which are algebraic data structures representing multiple possible shapes. It solves the problem of excessive boilerplate when implementing disjoint union types in JavaScript, providing a clean and type-safe way to define and work with variants like `Success` and `Failure` cases.
JavaScript developers working with functional programming patterns, especially those building applications that require robust data modeling with sum types and pattern matching.
Developers choose Daggy for its minimal API that drastically reduces boilerplate, its built-in type checking and pattern matching capabilities, and its alignment with functional programming principles without requiring external type systems.
Library for creating tagged constructors.
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Daggy's taggedSum function drastically reduces code for sum types, as shown in the README where it simplifies error handling from manual objects to structured constructors like Result.Success and Result.Failure.
The .cata method enables clean case analysis on sum types, allowing developers to handle variants without nested conditionals, exemplified in the handleResult function for deconstructing Success and Failure cases.
With .is methods, Daggy provides runtime validation for types and constructors, enhancing reliability, as demonstrated in the API where Option.Some.is(a) returns true for valid instances.
Designed for immutability and algebraic data types, Daggy supports functional workflows, making it easy to implement concepts like Option with prototype methods such as map.
Since Daggy operates in plain JavaScript, it lacks static type checking, so errors may only surface at runtime, unlike TypeScript which offers compile-time validation for union types.
As part of the fantasyland project, Daggy assumes familiarity with functional programming libraries, which can be a barrier for teams new to this paradigm and limit community support.
The README is brief and focuses on basic API examples; there's no extensive guide for advanced use cases, serialization, or integration with modern frameworks, requiring additional research.