Rob Pike

22 December 2014

A property of universal computation—Turing completeness—is that a computer program can write a computer program. This is a powerful idea that is not appreciated as often as it might be, even though it happens frequently. It's a big part of the definition of a compiler, for instance. It's also how the go test command works: it scans the packages to be tested, writes out a Go program containing a test harness customized for the package, and then compiles and runs it. Modern computers are so fast this expensive-sounding sequence can complete in a fraction of a second.

There are lots of other examples of programs that write programs. Yacc, for instance, reads in a description of a grammar and writes out a program to parse that grammar. The protocol buffer "compiler" reads an interface description and emits structure definitions, methods, and other support code. Configuration tools of all sorts work like this too, examining metadata or the environment and emitting scaffolding customized to the local state.

Programs that write programs are therefore important elements in software engineering, but programs like Yacc that produce source code need to be integrated into the build process so their output can be compiled. When an external build tool like Make is being used, this is usually easy to do. But in Go, whose go tool gets all necessary build information from the Go source, there is a problem. There is simply no mechanism to run Yacc from the go tool alone.

Until now, that is.

The latest Go release, 1.4, includes a new command that makes it easier to run such tools. It's called go generate , and it works by scanning for special comments in Go source code that identify general commands to run. It's important to understand that go generate is not part of go build . It contains no dependency analysis and must be run explicitly before running go build . It is intended to be used by the author of the Go package, not its clients.

The go generate command is easy to use. As a warmup, here's how to use it to generate a Yacc grammar.

First, install Go's Yacc tool:

go get golang.org/x/tools/cmd/goyacc

Say you have a Yacc input file called gopher.y that defines a grammar for your new language. To produce the Go source file implementing the grammar, you would normally invoke the command like this:

goyacc -o gopher.go -p parser gopher.y

The -o option names the output file while -p specifies the package name.

To have go generate drive the process, in any one of the regular (non-generated) .go files in the same directory, add this comment anywhere in the file:

//go:generate goyacc -o gopher.go -p parser gopher.y

This text is just the command above prefixed by a special comment recognized by go generate . The comment must start at the beginning of the line and have no spaces between the // and the go:generate . After that marker, the rest of the line specifies a command for go generate to run.

Now run it. Change to the source directory and run go generate , then go build and so on:

$ cd $GOPATH/myrepo/gopher $ go generate $ go build $ go test

That's it. Assuming there are no errors, the go generate command will invoke yacc to create gopher.go , at which point the directory holds the full set of Go source files, so we can build, test, and work normally. Every time gopher.y is modified, just rerun go generate to regenerate the parser.

For more details about how go generate works, including options, environment variables, and so on, see the design document.

Go generate does nothing that couldn't be done with Make or some other build mechanism, but it comes with the go tool—no extra installation required—and fits nicely into the Go ecosystem. Just keep in mind that it is for package authors, not clients, if only for the reason that the program it invokes might not be available on the target machine. Also, if the containing package is intended for import by go get , once the file is generated (and tested!) it must be checked into the source code repository to be available to clients.

Now that we have it, let's use it for something new. As a very different example of how go generate can help, there is a new program available in the golang.org/x/tools repository called stringer . It automatically writes string methods for sets of integer constants. It's not part of the released distribution, but it's easy to install:

$ go get golang.org/x/tools/cmd/stringer

Here's an example from the documentation for stringer . Imagine we have some code that contains a set of integer constants defining different types of pills:

package painkiller type Pill int const ( Placebo Pill = iota Aspirin Ibuprofen Paracetamol Acetaminophen = Paracetamol )

For debugging, we'd like these constants to pretty-print themselves, which means we want a method with signature,

func (p Pill) String() string

It's easy to write one by hand, perhaps like this:

func (p Pill) String() string { switch p { case Placebo: return "Placebo" case Aspirin: return "Aspirin" case Ibuprofen: return "Ibuprofen" case Paracetamol: // == Acetaminophen return "Paracetamol" } return fmt.Sprintf("Pill(%d)", p) }

There are other ways to write this function, of course. We could use a slice of strings indexed by Pill, or a map, or some other technique. Whatever we do, we need to maintain it if we change the set of pills, and we need to make sure it's correct. (The two names for paracetamol make this trickier than it might otherwise be.) Plus the very question of which approach to take depends on the types and values: signed or unsigned, dense or sparse, zero-based or not, and so on.

The stringer program takes care of all these details. Although it can be run in isolation, it is intended to be driven by go generate . To use it, add a generate comment to the source, perhaps near the type definition:

//go:generate stringer -type=Pill

This rule specifies that go generate should run the stringer tool to generate a String method for type Pill . The output is automatically written to pill_string.go (a default we could override with the -output flag).

Let's run it:

$ go generate $ cat pill_string.go // Code generated by stringer -type Pill pill.go; DO NOT EDIT. package painkiller import "fmt" const _Pill_name = "PlaceboAspirinIbuprofenParacetamol" var _Pill_index = [...]uint8{0, 7, 14, 23, 34} func (i Pill) String() string { if i < 0 || i+1 >= Pill(len(_Pill_index)) { return fmt.Sprintf("Pill(%d)", i) } return _Pill_name[_Pill_index[i]:_Pill_index[i+1]] } $

Every time we change the definition of Pill or the constants, all we need to do is run

$ go generate

to update the String method. And of course if we've got multiple types set up this way in the same package, that single command will update all their String methods with a single command.

There's no question the generated method is ugly. That's OK, though, because humans don't need to work on it; machine-generated code is often ugly. It's working hard to be efficient. All the names are smashed together into a single string, which saves memory (only one string header for all the names, even if there are zillions of them). Then an array, _Pill_index , maps from value to name by a simple, efficient technique. Note too that _Pill_index is an array (not a slice; one more header eliminated) of uint8 , the smallest integer sufficient to span the space of values. If there were more values, or there were negatives ones, the generated type of _Pill_index might change to uint16 or int8 : whatever works best.

The approach used by the methods printed by stringer varies according to the properties of the constant set. For instance, if the constants are sparse, it might use a map. Here's a trivial example based on a constant set representing powers of two:

const _Power_name = "p0p1p2p3p4p5..." var _Power_map = map[Power]string{ 1: _Power_name[0:2], 2: _Power_name[2:4], 4: _Power_name[4:6], 8: _Power_name[6:8], 16: _Power_name[8:10], 32: _Power_name[10:12], ..., } func (i Power) String() string { if str, ok := _Power_map[i]; ok { return str } return fmt.Sprintf("Power(%d)", i) }

In short, generating the method automatically allows us to do a better job than we would expect a human to do.

There are lots of other uses of go generate already installed in the Go tree. Examples include generating Unicode tables in the unicode package, creating efficient methods for encoding and decoding arrays in encoding/gob , producing time zone data in the time package, and so on.

Please use go generate creatively. It's there to encourage experimentation.