json-type

Guess Type from JSON values by using Crystal.

$ cat vals.txt
0
1
5
$ json-type vals.txt
Int32

$ cat vals.txt
0
0.1
$ json-type vals.txt
Float64 | Int32

Usecase

If the document's API is inadequate, we often deduce the type from the response JSON.

$ jq . res.json
[
  {
    "id": 10,
    "name": "foo",
    "count": 5,
...

$ jq '[].id' res.json > vals.txt
$ json-type vals.txt
Int32

$ jq '[].name' res.json > vals.txt
$ json-type vals.txt
String | Nil

$ jq '[].count' res.json > vals.txt
$ json-type vals.txt
Float64 | Int32 | String

Thus, we can design the struct of the response of the API as follows in Crystal.

record Foo,
  id    : Int32,
  name  : String | Nil,
  count : Float64 | Int32 | String

Mechanism

json-type simply runs the data as crystal code, and then gets its union type from reflection.

• vals.txt

0
"foo"
null

First, json-type puts those data as an Array into crystal file named json-type-source.cr like this.

a = [0, "foo", nil]
puts a.class.to_s

Here, null or empty lines are automatically converted to nil.

Second, json-type executes the created code by invoking a new crystal process.

crystal json-type-source.cr

So, note two points.

1. crystal should be installed in your environment.
2. be careful that all json data will be executed as crystal codes.

Development

$ make test

Contributing

1. Fork it (https://github.com/maiha/json-type/fork)
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request

Contributors

• maiha maiha - creator, maintainer