This repository contains an experimental Jsonnet docs generator, consisting of multiple parts:
- Docsonnet, a data model for logically describing the structure of public facing Jsonnet API's.
doc-util
, A Jsonnet extension that allows to write Docsonnet directly alongside your Jsonnet. Currently implemented as a library, might become language sugar at some pointdocsonnet
: A CLI application and Go library for parsing Docsonnet and transforming it to e.g. Markdown pages
To make use of Docsonnet, use doc-util
to annotate your Jsonnet like so:
{
// package declaration
'#': d.pkg(
name='url',
url='github.com/jsonnet-libs/xtd/url/main.libsonet',
help='`url` implements URL escaping and query building',
),
// function description
'#encodeQuery': d.fn(
'`encodeQuery` takes an query parameters and returns them as an escaped `key=value` string',
[d.arg('params', d.T.object)]),
encodeQuery(params)::
local fmtParam(p) = '%s=%s' % [self.escapeString(p), self.escapeString(params[p])];
std.join('&', std.map(fmtParam, std.objectFields(params))),
}
Jsonnet itself does not know traditional packages, classes or similar.
For documentation and distribution purposes however, it seems reasonable to introduce a concept of loose packages, defined as a single importable file, holding all of your public API.
As an example, a hypothetical url
library could define its package like above example does.
Packages are defined by including assigning a d.pkg
call to a key literally named #
(hash). All fields, including nested packages, of the same object having the #
key belong to that package.
Most common part of an API will be functions. These are annotated in a similar fashion:
{
"#myFunc": d.fn("myFunc greets you", [d.arg("who", d.T.string)])
myFunc(who):: "hello %s!" % who
}
Along the actual function definition, a docsonnet key is added, with the functions name prefixed by the familiar #
as its name.
Above example defines myFunc
as a function, that greets the user and takes a single argument of type string
.
Sometimes you might want to group functions of a similar kind, by nesting them into plain Jsonnet objects.
Such an object might need a description as well, so you can also annotate it:
{
"#myObj": d.obj("myObj holds my functions")
myObj:: {
"#myFunc": d.fn("myFunc greets you", [d.arg("who", d.T.string)])
myFunc(who):: "hello %s!" % who
}
}
Again, the naming rule #
joined with the fields name must be followed, so the docsonnet
utility can automatically join together the contents of your object with its annotated description.
Once you have a Jsonnet library annotated with doc-util
, you can generate the docs using one of three ways:
The docs can be rendered using Jsonnet with the render function.
In your library source, add a file docs.jsonnet
(assuming your library entrypoint is main.libsonnet
) with the
following contents:
local d = import 'github.com/jsonnet-libs/docsonnet/doc-util/main.libsonnet';
d.render(import 'main.libsonnet')
Then, you can render the markdown to the docs/
folder using the following command:
jsonnet -J vendor -S -c -m docs/ docs.jsonnet
Note that this requires doc-util
to be installed to vendor/
to work properly.
Alternatively, the docs can be rendered using the docsonnet
go binary. The docsonnet
binary embeds the doc-util
library, avoiding the need to have doc-util
installed.
You can install the docsonnet
binary using go install
:
go install github.com/jsonnet-libs/docsonnet@master
Once the binary is installed, you can generate the docs by passing it the main entrypoint to your Jsonnet library:
docsonnet main.libsonnet
Note
Linters like jsonnet-lint or
tk lint
require the imports to be resolvable, so you should adddoc-util
tovendor/
when using these linters.
You can also use the docker image which contains the docsonnet
binary if you do not wish to set up go or install the binary locally:
docker run --rm -v "$(pwd):/src" -v "$(pwd)/docs:/docs" jsonnetlibs/docsonnet /src/main.libsonnet
I had some attempts on this, especially because it feels more natural. However, the language properties of Jsonnet make this quite challenging:
- AST parsing is insufficient: grafana/tanka#223 (comment). Just by parsing the syntax tree of Jsonnet, we only receive a representation of the file contents, not the logical ones a human might infer
- No effective view on things: Jsonnet is a lazily evaluated, highly dynamic language. Just by looking at a single file, we might not even see what ends up at the user when importing the library, because during evaluation things can be heavily overwritten.
Because of that, we would need to perform a slimmed down evaluation on the AST before getting our information out of it. This is a lot of work, especially when we can just use the real Jsonnet compiler to do this for us. That's docsonnet.
I know. Think of docsonnet as a proof of concept and a technology preview. Only what you specify is a fixed thing, not the way you do.
Of course nobody wants these ugly function calls as docs. But they are incredibly powerful, because we can use Jsonnet merging and patching on the generated docsonnet fields, and the Jsonnet compiler handles that for us.
In case this idea works out well, we might very well consider adding docsonnet as language sugar to Jsonnet, which might look like this:
{
## myFunc greets you
## @params:
## who: string
myFunc(who):: "hello %s!" % who
}
Note the double hash ##
as a special indicator for the compiler, so it can desugar above to:
{
"#myFunc": d.fn("myFunc greets you", [d.arg("who", d.T.string)])
myFunc(who):: "hello %s!" % who
}
This will all happen transparently, without any user interaction
Because the Docsonnet gives you the missing logical representation of your Jsonnet library, it enables straight forward implementation of other language tooling, such as code-completion.
Instead of inferring what fields are available for a library, we can just look at its docsonnet and provide the fields specified there, along with nice descriptions and argument types.