Inko 0.10.0 released

Published on by Yorick Peterse

It's been almost two years since the last Inko release, and 1.5 years since we started work on drastically changing Inko to make it a more compelling language. Today we're pleased to announce the release of version 0.10.0. As this release contains so many changes we'll start by (re)introducing Inko, discuss why it took so long to release a new version, and of course discuss the changes themselves.

Table of contents

What is Inko?

Inko is a statically typed language for building concurrent software with confidence. Inko offers various features such as deterministic automatic memory management, move semantics, efficient and elegant error handling, type-safe concurrency support, static typing, and more.

Inko is an interpreted language with a custom bytecode virtual machine and compiler, both written in Rust. Inko is easy and fast to install, and supports Linux, macOS and Windows.

Inko is useful for writing all sorts of applications, from HTTP servers and databases to simple command-line programs. As such it competes with languages such as Ruby, Python, Erlang, and Go.

What happened since the last release?

Inko used to use a garbage collector for memory management, and a concurrency API similar to Erlang. Both of these have their issues: garbage collectors are notoriously unpredictable, and may require a lot of tuning. Erlang's concurrency API in turn is difficult to make type-safe. We first started looking into solving these issues over two years ago, but at the time we couldn't come up with a viable solution.

Along the way we came across the paper "Ownership You Can Count On: A Hybrid Approach to Safe Explicit Memory Management" (mirrored here). The paper discusses a form of object ownership that's easy to adopt, without needing an overly complicated type system or borrow checker. While we're not the first to come across this paper (e.g. Nim considered it back in 2019), it does seem we're the first to implement it fully. Reading the paper lead to the creation of this merge request, in which we started work on moving away from using a garbage collector and towards using single ownership and move semantics for memory management.

Along the way we came across the paper "Uniqueness and Reference Immutability for Safe Parallelism". Reading the paper we realised the setup discussed in the paper could prove compelling when combined with single ownership and move semantics. Most notably it would allow moving of data between processes without the need for deep copying or synchronisation. If you've ever used Pony, the setup discussed in the paper may sound familiar and that's no coincidence: Pony's approach to concurrency appears to be based on this paper, or at least draws inspiration from it. Unlike Pony, our approach involves fewer reference capabilities, which should make it easier to work with.

Of course reading papers is one thing, but changing an entire language is a different beast entirely, and what's what we've been up to for the last 1.5 years or so. Inko 0.10.0 is the result of this work, and we believe it will make Inko a compelling language to use in the coming years.

Installing Inko

The easier way to install Inko is using Inko's version manager:

ivm install 0.10.0

You can then set it as your default version as follows:

ivm default 0.10.0

After this you can use the inko executable like any other.

Arch Linux

If you're using Arch Linux you can also install Inko using the AUR and your favourite AUR wrapper:

yay -S inko

Or if you want to build it manually, use these steps:

git clone
cd inko
makepkg -si


Users of macOS can also use Homebrew:

brew install inko

Note that we don't maintain the Homebrew formula ourselves and as such it may take a while to be updated to version 0.10.0.

From source

You can also build from source:

git clone --branch=v0.10.0
cd inko

# This installs Inko into /usr
make build PREFIX=/usr
make install PREFIX=/usr

If you want to contribute to Inko you'll need to build the master branch like so:

git clone
cd inko
cargo build --release

In this case the executable is located at ./target/release/inko.

Changes included in 0.10.0

Before take a look at what's included in this release it's important to set the right expectations. Inko is only at version 0.10, and we still have a long road ahead of us before reaching version 1.0. This means you may encounter bugs, compiler crashes, performance issues, or missing/lacking documentation. If you encounter any problems, please report them on our issue tracker.

With that said, let's dive into the changes included in this release.

Single ownership of values

Single ownership is a way of managing memory by assigning owners to values, and discarding (known as "dropping") of these values when the owner is done with them. Typically values start of as being owned by the surrounding scope, but ownership can be transferred by "moving" the values. A move can be an assignment to a variable or field, or passing the value as an argument.

Using single ownership means automatic memory management is deterministic and predictable, and doesn't require a garbage collector or (atomic) reference counting. Not using a garbage collector means not having to spend countless hours tweaking its various settings or worse: having to resort to hacks such as allocating a 10 GiB byte array, because the garbage collector doesn't let you tweak it in the first place.

To illustrate what single ownership looks like in Inko, consider this simple example:

let a = [10, 20, 30]
let b = a

When the array literal ([10, 20, 30]) is first created, its owner is the surrounding scope. Assigning the value to a transfers ownership to a. Assigning a to b then transfers ownership to b, disallowing the use of a from this point on. If b goes out of scope and its value isn't moved, it drops its value.

In Inko there are four kinds of values: owned values, immutable references, mutable references, and unique values (which we'll cover in the next section); each with its own set of rules. Values start out as owned, and when these are no longer needed they are dropped. References are created when you need to temporarily borrow a value but don't want to drop it when you're done with it. For example:

let a = [10, 20, 30] # => Array[Int]
let b = ref a        # => ref Array[Int]

When b is no longer in use, only the reference is discarded; not the value it points to (a in this case). Mutation is restricted to owned values and mutable references (created using the mut keyword), giving you greater control over who gets to mutate what.

Unlike Rust, Inko allows you to have both mutable and immutable references to the same value at the same time. You're also allowed to move the value pointed to while references exist. This makes writing software with Inko easier, and certain patterns that are difficult in Rust (e.g. self-referential data structures) are trivial to implement in Inko. For example, here's how you'd define a doubly-linked list:

class Node[T] {
  # These are the class' fields and their types.
  let @next: Option[Node[T]]
  let @previous: Option[mut Node[T]]
  let @value: T

class List[T] {
  let @head: Option[Node[T]]
  let @tail: Option[mut Node[T]]

In Rust this would require the use of (unsafe) raw pointers, indexes (introducing extra indirection), or more complicated alternatives.

Inko makes this possible by not performing all safety checks at compile-time, instead performing some of them at runtime. In particular, each owned value tracks its number of (im)mutable references. If an owned value is dropped while references to it still exist, the program aborts with an error. Creating and discarding references in turn mutates this counter accordingly. Many of these reference count changes can be optimised away, and indeed Inko's compiler does just that; though there's a lot of room for improvement. Integers, floats and strings are value types, meaning they are copied when moved. For strings we use atomic reference counting, meaning that 10 copies of a 1 GiB string only need 1 GiB of memory.

For a systems language such as Rust, managing reference counts at runtime may not be desirable, though it's not unheard of in Rust: types such as Arc and RefCell do just that in Rust. For a more high-level language such as Inko we believe it's a compelling trade-off, as it provides you the benefits of single ownership but at a smaller cost.

Type-safe concurrency

Inspired by Erlang, Inko uses lightweight isolated threads known as "lightweight processes". These processes don't share memory and communicate by sending messages. This is built on top of Inko's ownership model: when you send values to a process, the values are moved into the receiving process and are no longer available to the sender.

Value types are copied when sent, but for other types we have to guarantee the sender retains no references to the values, and that the values don't contain references to values still in use by the sender. In other words, we have to guarantee the value is unique (in that the value itself is the only reference to/from it). For this Inko uses an approach similar to Pony: recovery and unique values. Unlike Pony our implementation is simpler to use, due to the combination of single ownership and having fewer reference capabilities.

A unique value is essentially a box of which the compiler knows nothing outside the box points into it, and nothing inside the box points to the outside; though values in the box can point to each other just fine.

Recovery is the process of taking an owned value and turning it into a unique value, or turning a unique value back into an owned value. Recovery is simple yet effective: Inko has a recover keyword, which takes either a single expression or a block:

recover [10, 20]     # => uni Array[Int]
recover { [10, 20] } # => uni Array[Int]

Inside a recover block variables defined outside it are only available if they are value types or unique, everything else can't be used:

let a = [10, 20]
let b = recover a # => invalid, because `a` is defined outside the `recover`

This leads to the following observation: if outside owned values and references aren't available, then any such value created inside the recover expression can only point to or contain other values created in the recover expression. This means that if the recover expression returns an owned value, it's safe to convert it into a unique value, because no outside references to it will exist any more at that point.

The same is true the other way around: unique values are available to recover expressions. The value returned by a recover expression in turn is moved into its new value/type. This means that if the recover expression returns a unique value, it's safe to turn it into an owned value.

Using unique values comes with restrictions, such as not being able to call methods on them if they take arguments that aren't "sendable". A value is "sendable" if it's a value type or a unique type. Under certain conditions we can relax these restrictions, making it easier to call methods on unique values. For example, if a method is immutable and doesn't take arguments, any owned value it returns or throws must have been created as part of the method call. This means it's safe to treat the value as sendable, because no outside references to it can exist when its produced.

Creating processes is done by defining classes marked as async:

class async Counter {
  let @value: Int

When creating instances of such classes, Inko spawns a new process. Processes are a bit like generators in that they don't do anything by default, instead they act upon messages sent to them. Messages are defined as methods marked as async, and are processed in FIFO order:

class async Counter {
  let @value: Int

  fn async mut increment(value: Int) {
    @value += value

  fn async value -> Int {

Sending messages is done using Inko's regular method call syntax:

let counter = Counter { @value = 0 }

counter.value # => 2

When sending messages Inko defaults to awaiting the result right away. This makes it easier to transition from regular types to processes, while also making async calls more explicit. How do we not wait right away? Simple: just stick async in front of the expression:

let counter = Counter { @value = 0 }

async counter.increment(1)
async counter.increment(1)

In this case you get a Future back instead of the message result, and you can resolve it using the method Future.await:

let counter = Counter { @value = 0 }

async counter.increment(1)
async counter.increment(1)

let future = async counter.value

future.await # => 2

In all cases Inko's scheduler takes care of suspending and rescheduling the process, ensuring the underlying OS thread is available to perform other work.

Inko's approach to concurrency makes it easy to write efficient concurrent software, without having to worry about race conditions and without the need for deep copying values when sending them between processes.

A new compiler

Inko's compiler is now written in Rust instead of Ruby. While originally the idea was to work towards a self-hosting compiler we realised this isn't worth the time and effort. A self-hosting compiler complicates the development process as you have to maintain two compilers, while also complicating the installation process. Perhaps in the future we'll revise this, but at least not in the coming years.

Inko's compiler is a typical batch compiler consisting of many phases, somewhat inspired by the Nanopass framework. First we parse the source code into an AST, which is then lowered into Inko's high-level intermediate representation (creatively called "HIR"). HIR is basically just the AST with some small changes, and is used for type checking. Type checking is performed on HIR and annotates HIR with their types. Once done, we lower HIR into Inko's mid-level representation called "MIR". MIR is where we enforce single ownership, perform optimisations, compile pattern matching, and more.

The final step is to generate bytecode from MIR, which is then written to an Inko bytecode image. An image is just a file containing all the bytecode for an Inko program, somewhat similar to a Java JAR.

The new compiler is quite fast, even though we have spent little time optimising it: compiling Inko's test suite, which includes the entire standard library, only takes about 75 milliseconds. The exact time needed will probably change as we add more optimisations and improve the compiler, but it's a good start.

For more details on the compiler, take a look at this section of the manual.

Better type inference

As part of the compiler rewrite, type inference improved dramatically. Inko is also able to infer types based on how they're used later:

let a = [] # `a` is inferred as `Array[Int]` based on the `push()` below


This works for all generic types, not just arrays:

let mut a = Option.None # `a` inferred as `Option[Int]`

a = Option.Some(42)

Note that Inko doesn't have global type inference, meaning type signatures for methods are necessary. This is by design, as we feel this makes it easier to understand method definitions.

Symbol visibility

Symbols (classes, constants, etc) now default to being private to the modules they're defined in, instead of always being public. You can make symbols public using the pub keyword:

class PrivateClass {}
class pub PublicClass {}

let A = 10
let pub A = 10

Accessing fields directly

Inko now supports direct access of fields (depending on their visibility). The syntax is the same as getter/setter methods:

class Person {
  let @name: String

let alice = Person { @name = 'Alice' } # => 'Alice' = 'Bob' # => 'Bob'

Using the same syntax makes it easier to turn a field into a getter/setter method, without having to change all uses of the field. Note that while the syntax is the same, Inko's compiler doesn't generate getter/setter methods for you; instead accessing a field is just that: accessing a field.

Algebraic data types

Inko now supports algebraic data types, sometimes also known as sum types. These are defined using class enum like so:

class enum Result[T, E] {
  case Ok(T)
  case Error(E)

Creating instances of such types is done using regular method calls:

# Result.Ok() and Result.Error() are just methods generated by the compiler.
Result.Error('Oh no!')

When used for pattern matching, the compiler ensures the match is exhaustive, and will suggest any missing cases when the match isn't exhaustive.


Inko now supports tuples with up to eight values, instead of only supporting up to three values. Tuples are also available in type signatures:

let a: (Int, String) = (10, 'test')

Tuples are accessed as follows:

a.0 # => 10
a.1 # => 'test'

Tuples are just regular classes, such as Tuple2, Tuple3 and Tuple4. The compiler knows what class to use for a tuple based on the number of values it stores. This means the above is essentially syntax sugar for the following:

let a: Tuple2[Int, String] = Tuple2 { @0 = 10, @1 = 'test' }

Pattern matching

Inko now supports full pattern matching, instead of the limited form of pattern matching is used to support. Patterns such as enum variants, class literals, tuples, and integer literals are all supported. Guards are also supported

Here's what pattern matching looks like:

match Option.Some(42) {
  case Some(num) if num >= 40 and num <= 50 -> 'yay'
  case _ -> 'nay'

match (10, 'testing') {
  case (num, 'testing') if num < 20 -> 'yay'
  case _ -> 'nay'

class Person {
  let @name: String

let alice = Person { @name = 'Alice' }

match alice {
  case { @name = 'Alice' } -> "It's Alice!"
  case { @name = 'Bob' } -> "It's Bob!"
  case _ -> "It's somebody else!"

Match expressions are compiled into decision trees which are then lowered into MIR. When matching against an enum, the match is compiled into a jump table.

For more information about pattern matching, refer to the manual.

Installing Inko is easier

Now that the compiler is written in Rust and various other dependencies have been removed, installing Inko couldn't be easier: a simple cargo build --release is all it takes. The time it takes to compile Inko has also been reduced, with release builds taking just under 10 seconds on modern hardware.

Inko now uses the system allocator

Inko used an allocator based on Immix. While this allocator is excellent when paired with a garbage collector, it's less useful without. Most notably, handling fragmentation proved difficult. Along the way we realised our allocator was unlikely to ever outperform well established allocators such as jemalloc, and that our time was better spent elsewhere. Because of this, Inko now uses the system allocator for managing memory, and has built-in (optional) support for using jemalloc.

For now all Inko objects are allocated onto the heap, but stack allocating objects is something we'll look into in the future.

Improved standard library

The standard library received various additions, such as extra methods and improvements.

Range is no longer generic and only supports Int values, as this is what ranges are mostly used for. The .. and ... range syntax is removed, in favour of using regular methods (e.g. Int.until and

Map now preserves the insertion order of key-value pairs, making it easier to test, serialise and display Map values. The load factor is increased to 90%, reducing the amount of rehashing necessary.

DateTime uses a different algorithm for breaking timestamps, based on this article by Howard Hinnant.

String.length is removed in favour of using String.chars, which returns an iterator over the grapheme clusters of the string. This makes it more explicit that counting extended grapheme clusters is potentially expensive. We also added more methods to String, such as String.contains?, String.pad_start and String.pad_end, and improved the implementation of existing methods such as String.split.

Formatting and parsing integers is improved by using dedicated methods for the different integer bases, instead of using a single method that supports many bases (and panics when the base is invalid). For example, instead of this:

Int.parse('fff', radix: 16)

You now write the following:


The first approach isn't ideal as Int.parse would panic if radix was e.g. 100, as returning a None would hide the error of the base being invalid. The new approach doesn't suffer from this, and has the added benefit of using a more descriptive method name.

The module std::env no longer support setting environment variables, as changing these can lead to issues when interacting with C code through Inko's FFI, and it just isn't useful. The VM now caches environment variables at startup, making methods such as std::env.get more efficient.

What's next

For the next release of Inko we'll focus on building upon the changes included in 0.10.0, such as by improving the standard library and the compiler's test suite.

To make sharing Inko code easier we'll start looking into building a package manager for Inko, though this is unlikely to make it into the next release due to the scope of the work.

We'll also continue looking into compiling Inko to machine code. This isn't something planned for the next release specifically, but rather something we're looking into on the side.

Following and supporting Inko

If Inko sounds like an interesting project, consider joining the Matrix channel or the #inko channel in the /r/ProgrammingLanguages Discord server. You can also follow along on the /r/inko subreddit.

We are working on Inko full-time and using our savings to cover the costs. If you'd like to support the continued development of Inko, please consider donating using GitHub Sponsors. Every donation, no matter how small, is greatly appreciated.