frunk 0.1.13

Frunk provides developers with a number of functional programming tools like HList, Generic, Validated, Monoid, Semigroup and friends.

Frunk Build Status Join the chat at

frunk frəNGk

  • Functional programming toolbelt in Rust.
  • Might seem funky at first, but you'll like it.
  • Comes from: funktional (German) + Rust → Frunk

The general idea is to make things easier by providing FP tools in Rust to allow for stuff like this:

use frunk::monoid::*;

let v = vec![Some(1), Some(3)];
assert_eq!(combine_all(&v), Some(4));

// Slightly more magical
let t1 =       (1, 2.5f32,                String::from("hi"),  Some(3));
let t2 =       (1, 2.5f32,            String::from(" world"),     None);
let t3 =       (1, 2.5f32,         String::from(", goodbye"), Some(10));
let tuples = vec![t1, t2, t3];

let expected = (3, 7.5f32, String::from("hi world, goodbye"), Some(13));
assert_eq!(combine_all(&tuples), expected);

For a deep dive, RustDocs are available for:

Table of Contents

  1. HList
  2. Generic
  3. Validated
  4. Semigroup
  5. Monoid
  6. Todo
  7. Contributing
  8. Inspirations



Statically typed heterogeneous lists.

First, let's enable hlist:

#[macro_use] extern crate frunk; // allows us to use the handy hlist! macro
use frunk_core::hlist::*;

Some basics:

let h = hlist![1];
// Type annotations for HList are optional. Here we let the compiler infer it for us
// h has a static type of: HCons<i32, HNil>

// HLists have a head and tail
assert_eq!(hlist![1].head, 1);
assert_eq!(hlist![1].tail, HNil);

HLists have a hlist_pat! macro for pattern matching;

let h: Hlist!(&str, &str, i32, bool) = hlist!["Joe", "Blow", 30, true];
// We use the Hlist! type macro to make it easier to write 
// a type signature for HLists, which is a series of nested HCons
// h has an expanded static type of: HCons<&str, HCons<&str, HCons<i32, HCons<bool, HNil>>>>

let hlist_pat!(f_name, l_name, age, is_admin) = h;
assert_eq!(f_name, "Joe");
assert_eq!(l_name, "Blow");
assert_eq!(age, 30);
assert_eq!(is_admin, true);

// You can also use into_tuple2() to turn the hlist into a nested pair

You can also traverse HLists using .pop()

let h = hlist![true, "hello", Some(41)];
// h has a static type of: HCons<bool, HCons<&str, HCons<Option<{integer}>, HNil>>>
let (h1, tail1) = h.pop();
assert_eq!(h1, true);
assert_eq!(tail1, hlist!["hello", Some(41)]);

You can reverse, map, and fold over them too:

// Reverse
let h1 = hlist![true, "hi"];
assert_eq!(h1.into_reverse(), hlist!["hi", true]);

// Fold (foldl and foldr exist)
let h2 = hlist![1, false, 42f32];
let folded = h2.foldr(
        |i, acc| i + acc,
        |_, acc| if acc > 42f32 { 9000 } else { 0 },
        |f, acc| f + acc
assert_eq!(folded, 9001)

// Map
let h3 = hlist![9000, "joe", 41f32];
let mapped =![
    |n| n + 1,
    |s| s,
    |f| f + 1f32]);
assert_eq!(mapped, hlist![9001, "joe", 42f32]);


Generic is a way of representing a type in ... a generic way. By coding around Generic, you can to write functions that abstract over types and arity, but still have the ability to recover your original type afterwards. This can be a fairly powerful thing.

Frunk comes out of the box with a nice custom Generic derivation so that boilerplate is kept to a minimum.

Here are some examples:

HList ⇄ Struct

extern crate frunk;
#[macro_use] // for the hlist macro
extern crate frunk_core;
use frunk::*; // for the Generic trait and HList

#[derive(Generic, Debug, PartialEq)]
struct Person<'a> {
    first_name: &'a str,
    last_name: &'a str,
    age: usize,

let h = hlist!("Joe", "Blow", 30);
let p: Person = from_generic(h);
           Person {
               first_name: "Joe",
               last_name: "Blow",
               age: 30,

This also works the other way too; just pass a struct to into_generic and get its generic representation.

Converting between Structs

Sometimes you may have 2 different types that are structurally the same (e.g. different domains but the same data). Use cases include:

  • You have a models for deserialising from an external API and equivalents for your app logic
  • You want to represent different stages of the same data using types (see this question on StackOverflow)

Generic comes with a handy convert_from method that helps make this painless:

// Assume we have all the imports needed
struct ApiPerson<'a> {
    FirstName: &'a str,
    LastName: &'a str,
    Age: usize,

struct DomainPerson<'a> {
    first_name: &'a str,
    last_name: &'a str,
    age: usize,

let a_person = ApiPersion {
                   first_name: "Joe",
                   last_name: "Blow",
                   age: 30,
let d_person: DomainPersion = convert_from(a_person); // done


Validated is a way of running a bunch of operations that can go wrong (for example, functions returning Result<T, E>) and, in the case of one or more things going wrong, having all the errors returned to you all at once. In the case that everything went well, you get an HList of all your results.

Mapping (and otherwise working with plain) Results is different because it will stop at the first error, which can be annoying in the very common case (outlined best by the Cats project).

To use Validated, first:

#[macro_use] extern crate frunk; // allows us to use the handy hlist! macro
use frunk_core::hlist::*;
use frunk::validated::*;

Assuming we have a Person struct defined

#[derive(PartialEq, Eq, Debug)]
struct Person {
    age: i32,
    name: String,
    street: String,

Here is an example of how it can be used in the case that everything goes smoothly.

fn get_name() -> Result<String, Error> { /* elided */ }
fn get_age() -> Result<i32, Error> { /* elided */ }
fn get_street() -> Result<String, Error> { /* elided */ }

// Build up a `Validated` by adding in any number of `Result`s
let validation = get_name().into_validated() + get_age() + get_street();
// When needed, turn the `Validated` back into a Result and map as usual
let try_person = validation.into_result()
                           // Destructure our hlist
                           .map(|hlist_pat!(name, age, street)| { 
                               Person {
                                   name: name,
                                   age: age,
                                   street: street,

           Person {
               name: "James".to_owned(),
               age: 32,
               street: "Main".to_owned(),

If, on the other hand, our Results are faulty:

/// This next pair of functions always return Recover::Err 
fn get_name_faulty() -> Result<String, String> {
    Result::Err("crap name".to_owned())

fn get_age_faulty() -> Result<i32, String> {
    Result::Err("crap age".to_owned())

let validation2 = get_name_faulty().into_validated() + get_age_faulty();
let try_person2 = validation2.into_result()
                             .map(|_| unimplemented!());

// Notice that we have an accumulated list of errors!
           vec!["crap name".to_owned(), "crap age".to_owned()]); 


Things that can be combined.

use frunk::semigroup::*;

assert_eq!(Some(1).combine(&Some(2)), Some(3));

assert_eq!(All(3).combine(&All(5)), All(1)); // bit-wise && 
assert_eq!(All(true).combine(&All(false)), All(false));


Things that can be combined and have an empty/id value.

use frunk::monoid::*;

let t1 = (1, 2.5f32, String::from("hi"), Some(3));
let t2 = (1, 2.5f32, String::from(" world"), None);
let t3 = (1, 2.5f32, String::from(", goodbye"), Some(10));
let tuples = vec![t1, t2, t3];

let expected = (3, 7.5f32, String::from("hi world, goodbye"), Some(13));
assert_eq!(combine_all(&tuples), expected)

let product_nums = vec![Product(2), Product(3), Product(4)];
assert_eq!(combine_all(&product_nums), Product(24))


Stabilise interface, general cleanup

Before a 1.0 release, would be best to revisit the design of the interfaces and do some general code (and test cleanup).


Benchmarks are available in ./benches and can be run with:

$ rustup run nightly cargo bench

It would be nice to use something like bench-cmp to compare before and after, but for some reason, there is no output. Should investigate why.

Not yet implemented

Given that Rust has no support for Higher Kinded Types, I'm not sure if these are even possible to implement. In addition, Rustaceans are used to calling iter() on collections to get a lazy view, manipulating their elements with map or and_then, and then doing a collect() at the end to keep things efficient. The usefulness of these following structures maybe limited in that context.

  1. Functor
  2. Monad
  3. Apply
  4. Applicative


Yes please !

The following are considered important, in keeping with the spirit of Rust and functional programming:

  • Safety (type and memory)
  • Efficiency
  • Correctness


Scalaz, Shapeless, Cats, Haskell, the usual suspects ;)