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.
Functions in mgmt
are similar to functions in other languages, however they
also have a reactive
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
on the subject.
Native functions are functions which are implemented in the mgmt language itself. These are currently not available yet, but are coming soon. Stay tuned!
Most functions should be implemented using the simple function API. This API allows you to implement simple, static, pure 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
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/
module. It should probably get created in the correct directory inside of:
lang/core/
. The
function should be implemented as a simple.Scaffold
in our API. It is then
registered with the engine during init()
. An example explains it best:
package simple
import (
"context"
"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", &simple.Scaffold{
T: types.NewType("func(int) str"), // declare the signature
F: func(ctx context.Context, 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.
package simple
import (
"context"
"fmt"
"github.com/purpleidea/mgmt/lang/funcs/simple"
"github.com/purpleidea/mgmt/lang/types"
)
func init() {
// This is the actual definition of the `len` function.
simple.Register("len", &simple.Scaffold{
T: types.NewType("func(?1) int"), // contains a unification var
C: simple.TypeMatch([]string{ // match on any of these sigs
"func(str) int",
"func([]?1) int",
"func(map{?1: ?2}) int",
}),
// The implementation is left as an exercise for the reader.
F: Len,
})
}
Most functions should be implemented using the simple function API. If they need to have multiple polymorphic forms under the same name, with each resultant type match needing to be paired to a different implementation, then you can use this API. This is useful for situations when the functions differ in output type only.
To implement a reactive function in mgmt
it must satisfy the
Func
interface. Using the 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() *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.
func (obj *FooFunc) Info() *interfaces.Info {
return &interfaces.Info{
Pure: true,
Sig: types.NewType("func(a int) str"),
}
}
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.
// Init runs some startup code for this function.
func (obj *FooFunc) Init(init *interfaces.Init) error {
obj.init = init
return nil
}
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.
// 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.
There is some additional information that any function author will need to know. Each issue is listed separately below!
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.
type FooFunc struct {
init *interfaces.Init
// this space can be used if needed
}
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.
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.
// 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 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.
(Send your questions as a patch to this FAQ! I'll review it, merge it, and respond by commit with the answer.)
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.
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.
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!
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.
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.
Additional blog posts, videos and other material is available!.
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!