# Function guide ## Overview The `mgmt` tool has built-in functions which add useful, reactive functionality to the language. This guide describes the different function API's that are available. It is meant to instruct developers on how to write new functions. Since `mgmt` and the core functions are written in golang, some prior golang knowledge is assumed. ## Theory Functions in `mgmt` are similar to functions in other languages, however they also have a [reactive](https://en.wikipedia.org/wiki/Functional_reactive_programming) component. Our functions can produce events over time, and there are different ways to write functions. For some background on this design, please read the [original article](https://purpleidea.com/blog/2018/02/05/mgmt-configuration-language/) on the subject. ## Native Functions Native functions are functions which are implemented in the mgmt language itself. These are currently not available yet, but are coming soon. Stay tuned! ## Simple Function API Most functions should be implemented using the simple function API. This API allows you to implement simple, static, [pure](https://en.wikipedia.org/wiki/Pure_function) functions that don't require you to write much boilerplate code. They will be automatically re-evaluated as needed when their input values change. These will all be automatically made available as helper functions within mgmt templates, and are also available for use anywhere inside mgmt programs. You'll need some basic knowledge of using the [`types`](https://github.com/purpleidea/mgmt/tree/master/lang/types) library which is included with mgmt. This library lets you interact with the available types and values in the mgmt language. It is very easy to use, and should be fairly intuitive. Most of what you'll need to know can be inferred from looking at example code. To implement a function, you'll need to create a file that imports the [`lang/funcs/simple/`](https://github.com/purpleidea/mgmt/tree/master/lang/funcs/simple/) module. It should probably get created in the correct directory inside of: [`lang/funcs/core/`](https://github.com/purpleidea/mgmt/tree/master/lang/funcs/core/). The function should be implemented as a `FuncValue` in our type system. It is then registered with the engine during `init()`. An example explains it best: ### Example ```golang package simple import ( "fmt" "github.com/purpleidea/mgmt/lang/funcs/simple" "github.com/purpleidea/mgmt/lang/types" ) // you must register your functions in init when the program starts up func init() { // Example function that squares an int and prints out answer as an str. simple.ModuleRegister(ModuleName, "talkingsquare", &types.FuncValue{ T: types.NewType("func(int) str"), // declare the signature V: func(input []types.Value) (types.Value, error) { i := input[0].Int() // get first arg as an int64 // must return the above specified value return &types.StrValue{ V: fmt.Sprintf("%d^2 is %d", i, i * i), }, nil // no serious errors occurred }, }) } ``` This simple function accepts one `int` as input, and returns one `str`. Functions can have zero or more inputs, and must have exactly one output. You must be sure to use the `types` library correctly, since if you try and access an input which should not exist (eg: `input[2]`, when there are only two that are expected), then you will cause a panic. If you have declared that a particular argument is an `int` but you try to read it with `.Bool()` you will also cause a panic. Lastly, make sure that you return a value in the correct type or you will also cause a panic! If anything goes wrong, you can return an error, however this will cause the mgmt engine to shutdown. It should be seen as the equivalent to calling a `panic()`, however it is safer because it brings the engine down cleanly. Ideally, your functions should never need to error. You should never cause a real `panic()`, since this could have negative consequences to the system. ## Simple Polymorphic Function API Most functions should be implemented using the simple function API. If they need to have multiple polymorphic forms under the same name, then you can use this API. This is useful for situations when it would be unhelpful to name the functions differently, or when the number of possible signatures for the function would be infinite. The canonical example of this is the `len` function which returns the number of elements in either a `list` or a `map`. Since lists and maps are two different types, you can see that polymorphism is more convenient than requiring a `listlen` and `maplen` function. Nevertheless, it is also required because a `list of int` is a different type than a `list of str`, which is a different type than a `list of list of str` and so on. As you can see the number of possible input types for such a `len` function is infinite. Another downside to implementing your functions with this API is that they will *not* be made available for use inside templates. This is a limitation of the `golang` template library. In the future if this limitation proves to be significantly annoying, we might consider writing our own template library. As with the simple, non-polymorphic API, you can only implement [pure](https://en.wikipedia.org/wiki/Pure_function) functions, without writing too much boilerplate code. They will be automatically re-evaluated as needed when their input values change. To implement a function, you'll need to create a file that imports the [`lang/funcs/simplepoly/`](https://github.com/purpleidea/mgmt/tree/master/lang/funcs/simplepoly/) module. It should probably get created in the correct directory inside of: [`lang/funcs/core/`](https://github.com/purpleidea/mgmt/tree/master/lang/funcs/core/). The function should be implemented as a list of `FuncValue`'s in our type system. It is then registered with the engine during `init()`. You may also use the `variant` type in your type definitions. This special type will never be seen inside a running program, and will get converted to a concrete type if a suitable match to this signature can be found. Be warned that signatures which contain too many variants, or which are very general, might be hard for the compiler to match, and ambiguous type graphs make for user compiler errors. The top-level type must still be a function type, it may only contain variants as part of its signature. It is probably more difficult to unify a function if its return type is a variant, as opposed to if one of its args was. An example explains it best: ### Example ```golang import ( "fmt" "github.com/purpleidea/mgmt/lang/funcs/simplepoly" "github.com/purpleidea/mgmt/lang/types" ) func init() { // You may use the simplepoly.ModuleRegister method to register your // function if it's in a module, as seen in the simple function example. simplepoly.Register("len", []*types.FuncValue{ { T: types.NewType("func([]variant) int"), V: Len, }, { T: types.NewType("func({variant: variant}) int"), V: Len, }, }) } // Len returns the number of elements in a list or the number of key pairs in a // map. It can operate on either of these types. func Len(input []types.Value) (types.Value, error) { var length int switch k := input[0].Type().Kind; k { case types.KindList: length = len(input[0].List()) case types.KindMap: length = len(input[0].Map()) default: return nil, fmt.Errorf("unsupported kind: %+v", k) } return &types.IntValue{ V: int64(length), }, nil } ``` This simple polymorphic function can accept an infinite number of signatures, of which there are two basic forms. Both forms return an `int` as is seen above. The first form takes a `[]variant` which means a `list` of `variant`'s, which means that it can be a list of any type, since `variant` itself is not a concrete type. The second form accepts a `{variant: variant}`, which means that it accepts any form of `map` as input. The implementation for both of these forms is the same: it is handled by the same `Len` function which is clever enough to be able to deal with any of the type signatures possible from those two patterns. At compile time, if your `mcl` code type checks correctly, a concrete type will be known for each and every usage of the `len` function, and specific values will be passed in for this code to compute the length of. As usual, make sure to only write safe code that will not panic! A panic is a bug. If you really cannot continue, then you must return an error. ## Function API To implement a reactive function in `mgmt` it must satisfy the [`Func`](https://github.com/purpleidea/mgmt/blob/master/lang/interfaces/func.go) interface. Using the [Simple Function API](#simple-function-api) is preferable if it meets your needs. Most functions will be able to use that API. If you really need something more powerful, then you can use the regular function API. What follows are each of the method signatures and a description of each. ### Info ```golang Info() *interfaces.Info ``` This returns some information about the function. It is necessary so that the compiler can type check the code correctly, and know what optimizations can be performed. This is usually the first method which is called by the engine. #### Example ```golang func (obj *FooFunc) Info() *interfaces.Info { return &interfaces.Info{ Pure: true, Sig: types.NewType("func(a int) str"), } } ``` ### Init ```golang Init(init *interfaces.Init) error ``` This is called to initialize the function. If something goes wrong, it should return an error. It is passed a struct that contains all the important information and pointers that it might need to work with throughout its lifetime. As a result, it will need to save a copy to that pointer for future use in the other methods. #### Example ```golang // Init runs some startup code for this function. func (obj *FooFunc) Init(init *interfaces.Init) error { obj.init = init return nil } ``` ### Stream ```golang Stream(context.Context) error ``` `Stream` is where the real _work_ is done. This method is started by the language function engine. It will run this function while simultaneously sending it values on the `Input` channel. It will only send a complete set of input values. You should send a value to the output channel when you have decided that one should be produced. Make sure to only use input values of the expected type as declared in the `Info` struct, and send values of the similarly declared appropriate return type. Failure to do so will may result in a panic and sadness. You must shutdown if the input context cancels. You must close the `Output` channel if you are done generating new values and/or when you shutdown. #### Example ```golang // Stream returns the single value that was generated and then closes. func (obj *FooFunc) Stream(ctx context.Context) error { defer close(obj.init.Output) // the sender closes var result string for { select { case input, ok := <-obj.init.Input: if !ok { return nil // can't output any more } ix := input.Struct()["a"].Int() if ix < 0 { return fmt.Errorf("we can't deal with negatives") } result = fmt.Sprintf("the input is: %d", ix) case <-ctx.Done(): return nil } select { case obj.init.Output <- &types.StrValue{ V: result, }: case <-ctx.Done(): return nil } } } ``` As you can see, we read our inputs from the `input` channel, and write to the `output` channel. Our code is careful to never block or deadlock, and can always exit if a close signal is requested. It also cleans up after itself by closing the `output` channel when it is done using it. This is done easily with `defer`. If it notices that the `input` channel closes, then it knows that no more input values are coming and it can consider shutting down early. ## Further considerations There is some additional information that any function author will need to know. Each issue is listed separately below! ### Function struct Each function will implement methods as pointer receivers on a function struct. The naming convention for resources is that they end with a `Func` suffix. #### Example ```golang type FooFunc struct { init *interfaces.Init // this space can be used if needed } ``` ### Function registration All functions must be registered with the engine so that they can be found. This also ensures they can be encoded and decoded. Make sure to include the following code snippet for this to work. ```golang import "github.com/purpleidea/mgmt/lang/funcs" func init() { // special golang method that runs once funcs.Register("foo", func() interfaces.Func { return &FooFunc{} }) } ``` Functions inside of built-in modules will need to use the `ModuleRegister` method instead. ```golang // moduleName is already set to "math" by the math package. Do this in `init`. funcs.ModuleRegister(moduleName, "cos", func() interfaces.Func { return &CosFunc{} }) ``` ### Composite functions Composite functions are functions which import one or more existing functions. This is useful to prevent code duplication in higher level function scenarios. Unfortunately no further documentation about this subject has been written. To expand this section, please send a patch! Please contact us if you'd like to work on a function that uses this feature, or to add it to an existing one! We don't expect this functionality to be particularly useful or common, as it's probably easier and preferable to simply import common golang library code into multiple different functions instead. ## Polymorphic Function API The polymorphic function API is an API that lets you implement functions which do not necessarily have a single static function signature. After compile time, all functions must have a static function signature. We also know that there might be different ways you would want to call `printf`, such as: `printf("the %s is %d", "answer", 42)` or `printf("3 * 2 = %d", 3 * 2)`. Since you couldn't implement the infinite number of possible signatures, this API lets you write code which can be coerced into different forms. This makes implementing what would appear to be generic or polymorphic, instead of something that is actually static and that still has the static type safety properties that were guaranteed by the mgmt language. Since this is an advanced topic, it is not described in full at this time. For more information please have a look at the source code comments, some of the existing implementations, and ask around in the community. ## Frequently asked questions (Send your questions as a patch to this FAQ! I'll review it, merge it, and respond by commit with the answer.) ### Can I use global variables? Probably not. You must assume that multiple copies of your function may be used at the same time. If they require a global variable, it's likely this won't work. Instead it's probably better to use a struct local variable if you need to store some state. There might be some rare instances where a global would be acceptable, but if you need one of these, you're probably already an internals expert. If you think they need to lock or synchronize so as to not overwhelm an external resource, then you have to be especially careful not to cause deadlocking the mgmt engine. ### Can I write functions in a different language? Currently `golang` is the only supported language for built-in functions. We might consider allowing external functions to be imported in the future. This will likely require a language that can expose a C-like API, such as `python` or `ruby`. Custom `golang` functions are already possible when using mgmt as a lib. ### What new functions need writing? There are still many ideas for new functions that haven't been written yet. If you'd like to contribute one, please contact us and tell us about your idea! ### Can I generate many different `FuncValue` implementations from one function? Yes, you can use a function generator in `golang` to build multiple different implementations from the same function generator. You just need to implement a function which *returns* a `golang` type of `func([]types.Value) (types.Value, error)` which is what `FuncValue` expects. The generator function can use any input it wants to build the individual functions, thus helping with code re-use. ### How do I determine the signature of my simple, polymorphic function? The determination of the input portion of the function signature can be determined by inspecting the length of the input, and the specific type each value has. Length is done in the standard `golang` way, and the type of each element can be ascertained with the `Type()` method available on every value. Knowing the output type is trickier. If it can not be inferred in some manner, then the only way is to keep track of this yourself. You can use a function generator to build your `FuncValue` implementations, and pass in the unique signature to each one as you are building them. Using a generator is a common technique which was mentioned previously. One obvious situation where this might occur is if your function doesn't take any inputs! An example `math.fortytwo()` function was implemented that demonstrates the use of function generators to pass the type signatures into the implementations. ### Where can I find more information about mgmt? Additional blog posts, videos and other material [is available!](https://github.com/purpleidea/mgmt/blob/master/docs/on-the-web.md). ## Suggestions If you have any ideas for API changes or other improvements to function writing, please let us know! We're still pre 1.0 and pre 0.1 and happy to break API in order to get it right!