| Crates.io | monadify |
| lib.rs | monadify |
| version | 0.1.1 |
| created_at | 2025-05-11 11:13:41.886931+00 |
| updated_at | 2025-05-11 11:28:24.47642+00 |
| description | A library for functional programming abstractions in Rust, focusing on Monads, Functors, Applicatives, and related concepts. |
| homepage | https://github.com/jarnura/monadify |
| repository | https://github.com/jarnura/monadify |
| max_upload_size | |
| id | 1669288 |
| size | 323,051 |
monadify is a Rust library that provides implementations of common functional programming constructs, with a primary focus on monads and related concepts like Functors, Applicatives, and Profunctors. The goal is to offer a practical exploration of these patterns in idiomatic Rust, serving as both a learning resource and a potentially reusable library component.
The library defines and implements the following core functional programming traits:
Functor: Types that can be mapped over. Provides map(self, f: A -> B) -> F<B>.
Option<A>, Result<A, E>, Vec<A>, CFn<X, A>, CFnOnce<X, A>.Apply: Extends Functor. Provides apply(self, f: F<A -> B>) -> F<B> for applying a wrapped function to a wrapped value.
Option<A>, Result<A, E>, Vec<A>.Applicative: Extends Apply. Provides pure(x: A) -> F<A> for lifting a value into the applicative context.
Option<A>, Result<A, E>, Vec<A>.Bind: Extends Apply. Provides bind(self, f: A -> F<B>) -> F<B> (also known as flatMap or >>=) for sequencing operations.
Option<A>, Result<A, E>, Vec<A>.Monad: A marker trait that groups Applicative and Bind.
Option<A>, Result<A, E>, Vec<A>.Profunctor: Bifunctors contravariant in the first argument and covariant in the second. Provides dimap(self, f: X -> A, g: B -> Y) -> P<X, Y>.
CFn<A, B> and CFnOnce<A, B>.Strong: Extends Profunctor. Provides first and second for operating on product types (tuples).
CFn<A, B>.Choice: Extends Profunctor. Provides left and right for operating on sum types (Result).
CFn<A, B>.The library also includes CFn and CFnOnce wrappers for heap-allocated closures, and various helper functions and macros (e.g., lift2, lift_a1, fn0!, fn1!, _1, _2, view) for working with these abstractions. Optical structures like Lens and Getter (using Profunctor encoding) are also explored.
Here's a quick example of using the Functor trait with Option (HKT is now the default):
use monadify::{Functor, OptionHKTMarker}; // Import HKT Functor and marker
let some_value: Option<i32> = Some(10);
// For HKT, Functor<A,B> is on the marker OptionHKTMarker
let mapped_value = OptionHKTMarker::map(some_value, |x| x * 2);
assert_eq!(mapped_value, Some(20));
let no_value: Option<i32> = None;
let mapped_none = OptionHKTMarker::map(no_value, |x: i32| x * 2);
assert_eq!(mapped_none, None);
And an example using Bind (often called flat_map):
use monadify::{Bind, OptionHKTMarker}; // Import HKT Bind and marker
fn try_parse_and_double(s: &str) -> Option<i32> {
s.parse::<i32>().ok().map(|n| n * 2)
}
let opt_str: Option<String> = Some("5".to_string());
// For HKT, Bind<A,B> is on the marker OptionHKTMarker
// The closure takes String because OptionHKTMarker::Applied<String> is Option<String>
let result = OptionHKTMarker::bind(
opt_str,
|st: String| try_parse_and_double(&st) // Our function A -> F<B>
);
assert_eq!(result, Some(10));
let opt_invalid_str: Option<String> = Some("hello".to_string());
let result_invalid = OptionHKTMarker::bind(
opt_invalid_str,
|st: String| try_parse_and_double(&st)
);
assert_eq!(result_invalid, None);
For more detailed examples, please refer to the documentation comments within the source code and the test files in the tests/ directory.
To build the library:
cargo build
The library includes a comprehensive test suite to verify the laws of Functor, Applicative, Monad, etc.
To run the default HKT tests:
cargo test
This suite includes over 140 tests covering HKT implementations (for Option, Result, Vec, Identity, CFn, ReaderT) and Profunctor laws, all passing.
To run tests for the legacy (non-HKT) implementations, use the legacy feature flag:
cargo test --features legacy
This suite includes over 80 tests for the legacy versions, also all passing.
Performance benchmarks for core operations are available using criterion.rs. To run the benchmarks:
cargo bench
The benchmark results can be found in target/criterion/report/index.html.
Key findings from initial benchmarks:
Functor::map and Bind::bind for Option and Result show negligible overhead compared to native methods.Apply::apply (which involves Box::new for CFn) has a small, consistent overhead (around 2-4 ns).Vec operations show more overhead due to by-value semantics and heap allocations for CFn in some cases.This project is licensed under the terms of the MIT License.