mkunion
Improves work with unions in golang by generating beautiful code (in other languages referred as sum types, variants, discriminators, tagged unions)
Project generates code for you, so you don't have to write it by hand.
It's a good idea to use it when you have a lot of unions in your codebase.
What it offers?
- Visitor interface with appropriate methods added to each union type
- Default implementation of Visitor that simplifies work with unions
- Reducer that can do recursive traversal (depth and breadth first) & default implementation of Reducer, fantastic for traversing ASTs
What it's useful for?
- Custom DSL. When you want to create your own DSL, you can use this library to create AST for it. (./examples/ast)
- State machine. When you need to manage state of your application, you can use this library to create states and transitions as unions. (./examples/state)
Have fun! I hope you will find it useful.
Usage
Install mkunion
Make sure that you have installed mkunion and is in GOPATH/bin
go install github.com/widmogrod/mkunion/cmd/mkunion@v1.16
Create your first union
Create your first union. In our example it's a simple tree with Branch and Leaf nodes
package example
//go:generate mkunion -name=Tree
type (
Branch struct{ L, R Tree }
Leaf struct{ Value int }
)
Generate code
Run
go generate ./...
Go will generate few files for you in the same location as union defnition
// source file
example/tree_example.go
// generated file
example/tree_example_mkunion_tree_default_reducer.go
example/tree_example_mkunion_tree_default_visitor.go
example/tree_example_mkunion_tree_reducer_bfs.go
example/tree_example_mkunion_tree_reducer_dfs.go
example/tree_example_mkunion_tree_visitor.go
Don't commit generated files to your repository. They are generated on the fly.
In your CI/CD process you need to run go generate before testing & building your project.
Use generated code
With our example you may want to sum all values in tree.
To be precise, we want to sum values that Leaf
struct holds.
For example, such tree needs to be summed to 10:
tree := &Branch{
L: &Leaf{Value: 1},
R: &Branch{
L: &Branch{
L: &Leaf{Value: 2},
R: &Leaf{Value: 3},
},
R: &Leaf{Value: 4},
},
}
To sum up values in a tree we can do it in 3 ways.
In all mkunion
will help us to do it in a clean way.
1. Implement tree reducer with help of Match
function
This approach is familiar with everyone who use functional programming.
- In this approach you're responsible for defining how you want to travers tree.
We will go with depth-first traversal.
MustMatchTree
function will do type checking, you need to handle all cases.
func MyReduceDepthFirstTree[A any](x Tree, aggregate func (int, A) A, init A) A {
// MustMatchTree is generated function my mkunion
return MustMatchTree(
x,
func (x *Leaf) B {
return aggregate(x.Value, init)
},
func (x *Branch) B {
// Note: here you define traversal order
// Right branch first, left branch second
return MyReduceDepthFirstTree(x.L, aggregate, MyReduceDepthFirstTree(x.R, f, init))
},
)
}
You use this function like this:
result := MyReduceDepthFirstTree(tree, func (x, y int) int {
return x + y
}, 0)
assert.Equal(t, 10, result)
2. Leverage generated default reduction with traversal strategies (depth first, breadth first)
You should use this approach
- When you need to traverse tree in different way than a depth first, like breadth first without writing your own code
- When you need to stop traversing of a tree at some point. For example, when you want to find a value in a tree, or meet some condition.
To demonstrate different traversal strategies, we will reduce a tree to a structure that will hold not only result of sum, but also order of nodes visited
// This structure will hold order of nodes visited, and resulting sum
type orderAgg struct {
Order []int
Result int
}
// This is how we define reducer function for traversal of tree
var red TreeReducer[orderAgg] = &TreeDefaultReduction[orderAgg]{
PanicOnFallback: false,
DefaultStopReduction: false,
OnLeaf: func(x *Leaf, agg orderAgg) (orderAgg, bool) {
return orderAgg{
Order: append(agg.Order, x.Value),
Result: agg.Result + x.Value,
}, false
},
}
// Dept first traversal
result := ReduceTreeDepthFirst(red, tree, orderAgg{})
assert.Equal(t, 10, result.Result)
assert.Equal(t, []int{1, 2, 3, 4}, result.Order) // notice that order is different!
// Breadth first traversal
result = ReduceTreeBreadthFirst(red, tree, orderAgg{})
assert.Equal(t, 10, result.Result)
assert.Equal(t, []int{1, 4, 2, 3}, result.Order) // notice that order is different!
Note:
- You can see that generated code knows how to traverse union recursively.
- You can write flat code and don't worry about recursion.
- Generator assumes that if in structure is reference to union type
Tree
, then it's recursive.
- Such code can also work on slices. You can take a look at
example/where_predicate_example.go
to see something more complex
3. Implement visitor interface
This is most open way to traverse tree.
- You have to implement
TreeVisitor
interface that was generated for you by mkunion
tool.
- You have to define how traversal should happen
This approach is better when you want to hold state or references in sumVisitor
struct.
In simple example this is not necessary, but in more complex cases you may store HTTP client, database connection or something else.
// assert that sumVisitor implements TreeVisitor interface
var _ TreeVisitor = (*sumVisitor)(nil)
// implementation of sumVisitor
type sumVisitor struct{}
func (s sumVisitor) VisitBranch(v *Branch) any {
return v.L.AcceptTree(s).(int) + v.R.AcceptTree(s).(int)
}
func (s sumVisitor) VisitLeaf(v *Leaf) any {
return v.Value
}
You can use sumVisitor
like this:
assert.Equal(t, 10, tree.AcceptTree(&sumVisitor{}))
Use mkunion
to simplify state management
Let's build our intuition first and crete simple state machine that increments counter using github.com/widmogrod/mkunion/x/machine
package
Let's import the package
import "github.com/widmogrod/mkunion/x/machine"
Let's define our state machine
m := NewSimpleMachineWithState(func(cmd string, state int) (int, error) {
switch cmd {
case "inc":
return state + 1, nil
case "dec":
return state - 1, nil
default:
return 0, fmt.Errorf("unknown cmd: %s", cmd)
}
}, 10)
Now to increment or decrement counter we can do it like this:
err := m.Handle("inc")
assert.NoError(t, err)
assert.Equal(t, 11, m.State())
Simple, right?
Let's use mkunion
crete more complex state machine
We learn how API of machine looks like. Let's complicate above example and use mkunion
to express distinct commands and states.
We will build state machine to manage Tic Tac Toe game.
I will not explain rules of Tic Tac Toe, and focus on how to use mkunion
to model state transitions.
You can find full example in example
- When we want to play a game, we need to start it first.
CreateGameCMD
is command that defines rules of the game
- To allow other player to join the game we have
JoinGameCMD
- And lastly we need a command to make a move
MakeMoveCMD
Here is how we define those interactions:
//go:generate mkunion -name=Command
type (
CreateGameCMD struct {
FirstPlayerID PlayerID
BoardRows int
BoardCols int
WinningLength int
}
JoinGameCMD struct{
SecondPlayerID PlayerID
}
MoveCMD struct {
PlayerID PlayerID
Position Move
}
)
Next we need to rules of the game.
- We cannot start a game without two players.
GameWaitingForPlayer
state will be used to indicate his.
- When we have two players, we can start a game.
GameInProgress
state will be used to indicate his. This state allows to make moves.
- When we have a winner, we can end a game.
GameEndWithWin
or GameEndWithDraw
state will be used to indicate his. This state does not allow to make moves.
//go:generate mkunion -name=State
type (
GameWaitingForPlayer struct {
TicTacToeBaseState
}
GameProgress struct {
TicTacToeBaseState
NextMovePlayerID Move
MovesTaken map[Move]PlayerID
MovesOrder []Move
}
GameEndWithWin struct {
TicTacToeBaseState
Winner PlayerID
WiningSequence []Move
MovesTaken map[Move]PlayerID
}
GameEndWithDraw struct {
TicTacToeBaseState
MovesTaken map[Move]PlayerID
}
)
Now we have to connect those rules by state transition.
This is how transition function looks like.
Implementation is omitted for brevity, but whole code can be found in machine.go
func Transition(cmd Command, state State) (State, error) {
return MustMatchCommandR2(
cmd,
func(x *CreateGameCMD) (State, error) {
if state != nil {
return nil, ErrGameAlreadyStarted
}
// validate game rules
rows, cols, length := GameRules(x.BoardRows, x.BoardCols, x.WinningLength)
return &GameWaitingForPlayer{
TicTacToeBaseState: TicTacToeBaseState{
FirstPlayerID: x.FirstPlayerID,
BoardRows: rows,
BoardCols: cols,
WinningLength: length,
},
}, nil
},
func(x *JoinGameCMD) (State, error) {
// omitted for brevity
},
func(x *MoveCMD) (State, error) {
// omitted for brevity
},
)
}
We define Transition
that use MustMatchCommandR2
that was generated by mkunion
to manage state transition
Now we will use github.com/widmogrod/mkunion/x/machine
package to provide unifed API for state machine
m := machine.NewMachineWithState(Transition, nil)
err := m.Handle(&CreateGameCMD{
FirstPlayerID: "player1",
BoardRows: 3,
BoardCols: 3,
WinningLength: 3,
})
assert.NoError(t, err)
assert.Equal(t, &GameWaitingForPlayer{
TicTacToeBaseState: TicTacToeBaseState{
FirstPlayerID: "player1",
BoardRows: 3,
BoardCols: 3,
WinningLength: 3,
},
}, m.State())
This is it. We have created state machine that manages Tic Tac Toe game.
Now with power of x/schema
transiting golang records and union types over network like JSON is easy.
// deserialise client commands
schemaCommand, err := schema.FromJSON(data)
cmd, err := schema.ToGo(schemaCommand)
// apply command to state (you may want to load it from database, s/schema package can help with that, it has DynamoDB schema support)
m := machine.NewMachineWithState(Transition, nil)
err = m.Handle(cmd)
// serialise state to send to client
schemaState := schema.FromGo(m.State())
data, err := schema.ToJSON(schemaState)
This is all. I hope you will find this useful.
Pattern matching
mkunion
can generate pattern matching code for few diverse tuples, triples etc for you.
Tou just need to define interface with methods that you want to pattern match:
//go:generate mkunion match -name=MyTriesMatch
type MyTriesMatch[T0, T1 Tree] interface {
MatchLeafs(*Leaf, *Leaf)
MatchBranches(*Branch, any)
MatchMixed(any, any)
}
Example interface definition will be used to generate matching functions.
Function will have name starting with interface name, and will have suffixes like R0, R1, R2, that indicate number of return values.
Below is example of generated code for MyTriesMatchR1
function:
MyTriesMatchR1(
&Leaf{Value: 1}, &Leaf{Value: 3},
func(x0 *Leaf, x1 *Leaf) int {
// your matching code goes here
},
func(x0 *Branch, x1 any) int {
// your matching code goes here
},
func(x0 any, x1 any) int {
// your matching code goes here
},
)
Note: Current implementation don't test if pattern matchers are exhaustive.
You can easily create pattern matchers that will never be called, just make (any, any) case a first invocation, and none fo the other cases will be ever called.
In future version, you can expect that this will change.
More examples
Please take a look at ./example
directory. It contains more examples of generated code.
Have fun! I hope you will find it useful.
Development & contribution
When you want to contribute to this project, go for it!
Unit test are must have for any PR.
Other than that, nothing special is required.
You may want to create issue to describe your idea before you start working on it.
That will help other developers to understand your idea and give you feedback.
go generate ./...
go test ./...
Roadmap ideas
V1.0.x
- Add visitor generation for unions
- Add support for depth-first traversal
- Add support for slice []{Variant} type traversal
V1.1.x
- Add support for map[any]{Variant} type
V1.2.x
- Add breadth-first reducer traversal
V1.3.x
- Use go:embed for templates
V1.4.x
- Add function generation like
Match
to simplify work with unions
- Benchmark implementation of
Match
vs Reducer (depth-first has close performance, but breadth-first is much slower)
V1.5.x
- Add support for multiple go:generate mkunion in one file
V1.6.x
- Add variant types inference
- Add
Unwrap
method to OneOf
V1.7.x
-
MustMatch*R2
function return tuple as result
- Introduce recursive schema prototype (
github.com/widmogrod/mkunion/x/schema
package)
- Integrate with schema for json serialization/deserialization
-
mkunion
can skip extensions -skip-extensions=<generator_name>
to be generated
- Remove OneOf to be the same as variant! (breaking change)
V1.8.x
- Introduce
github.com/widmogrod/mkunion/x/machine
for simple state machine construction
V1.9.x
- Introduce schema helper functions like Get(schema, location), As[int](schema, default), Reduce[A](schema, init, func(schema, A) A) A
- Allow to have union with one element, this is useful for domain model that is not yet fully defined
-
x/schema
breaking change. ToGo
returns any and error. Use MustToGo
to get panic on error
V1.10.x
- Introduce
Match*
and Match*R2
functions, that offer possibility to specif behaviour when value is nil
V1.14.x
- Introduce
Match*R0
and MustMatch*R0
functions, that allow matching but don't return any value
V1.15.x
- Union interface has method
Accept{Varian}
instead of just Accept
. Thanks to that is possible to use the same type in multiple unions. Such feature is beneficial for domain modelling.
- CLI
mkunion
change flag -types
to -variants
V1.16.x
- Pattern matching. Use
munion match -name=MyMatcher
where MyMather is interface. Function will generate functions that can pattern match and have return types MyMatcherR0, MyMatcherR1, MyMatcherR2
V1.17.x
- Exhaustive pattern matching checks during generation
- Allow extending (embedding) base Visitor interface with external interface
- Schema Registry should reject registration of names that are already registered!
- Add configurable behaviour how schema should act when field is missing, but schema has a value for it
V2.x.x
- Add support for generic union types
Removed from roadmap
- [-] Allow to change visitor name form Visit* to i.e Handle*.
Matcher functions are elastic enough that rename is not needed.