Types in ML-Inspired Languages

Learning about types via the OCaml and Elm

Transcript

1. Types in ML-Influenced
   Languages
   Exploring modern type inference
   

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2. What is ML? No, not machine learning
   ● “Meta Language”
   ● Originally designed as a language to build a theorem prover by Robin Milner
   ● Strong, static typing
   ● Enables powerful type inference via the Hindley-Milner algorithm
   ● We’ll focus on those last two pieces in modern implementations
   ● Code samples will be in OCaml
   

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3. Type Inference
   ● Type inference refers to the methods that allow a machine to understand and
   enforce a type used in a function without the programmer actually declaring a
   type signature
   ● Allows the compiler to enforce types by checking all usages of functions and
   their type signatures before runtime
   

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4. Type Inference: Example 1
   What type is the argument? What is the return type?
   

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5. What type is the argument? What is the return type?
   Type Inference: Example 2
   

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6. What types are the arguments? What is the return type?
   Type Inference: Example 3
   

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7. Parametric Polymorphism
   ● Similar to generics in other languages
   ● Given all the information at hand, the computer cannot tell exactly what type is
   required, therefore it must work for any type a’ and return any type b’
   

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8. Currying and Partial Application
   ● A curried function is a function that takes multiple arguments before executing,
   but accepts one argument at a time.
   

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9. Currying and Partial Application
   Typically, you get both for free and safely in typed, functional languages. All
   functions are curried by default.
   

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10. Safe partial application
    

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11. Advanced Types: Type Aliases
    A type alias, or type synonym, is a new name for an existing type. This opens the
    door for more expressive domain modeling
    

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12. Type Aliases - records
    Records are a data structure in many languages designed to hold multiple pieces of
    data (like tuples!) but with named fields and accessors
    

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13. Algebraic Data Types - Sum Types (aka Union Types)
    ● A type that represents a limited variety of arbitrary, user defined types
    

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14. Algebraic Data Types - Constructors with Data
    ● Our types can hold onto data
    ● Note the * in definition - refers to a “product type”
    

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15. How are types not classes?
    ● Classes encapsulate behavior and state, types focus on data
    

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16. Pattern Matching
    This enables exhaustive type checking from the compiler when using a type!
    

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17. Pattern Matching
    

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18. Representing null - the option type
    ● Also called optionals (Swift), Maybe (Haskell, Elm)
    

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19. Live Code
    

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20. Other languages
    

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21. If you want to learn more
    Effective ML by Yaron Minsky
    ● https://blog.janestreet.com/effective-ml-revisited/
    ● https://blog.janestreet.com/effective-ml-video/
    Domain Modeling Made Functional
    ● https://fsharpforfunandprofit.com/ddd/
    Why Type-First Development Matters
    ● http://tomasp.net/blog/type-first-development.aspx/
    

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