jq.cr

thin JSON::Any wrapper to emulate jq for crystal

Usage

• For example, here is a Grafana request data.

{
  "panelId":1,
  "range":{"from":"2016-09-02T13:32:09.981Z","to":"2016-09-02T14:17:34.306Z"},
  "rangeRaw":{"from":"2016-09-02T13:32:09.981Z","to":"2016-09-02T14:17:34.306Z"},
  "interval":"2s",
  "targets":[{"target":"cpu","refId":"A"},{"target":"mem","refId":"B"}],
  "format":"json",
  "maxDataPoints":1299
}

Parse in Functional way

• Just call 'Jq#[]` with query path.

require "jq"

jq = Jq.new(str)
jq[".range.from"].as_s       # => "2016-09-02T13:32:09.981Z"
jq[".targets[].target"].as_a # => ["cpu","mem"]
jq[".format"].as_s           # => "json"
jq[".maxDataPoints"].as_i    # => 1299
jq[".xxx"]                   # Jq::ParseError("`.xxx' Missing hash key: "xxx")

• See spec/fixtures/* files for further usage, or try crystal spec -v for full features

Auto parsing and casting by mapping

• looks like JSON.mapping except this requires Tuple(type, json_path, (time_format)) for its arg.
• NOTE: use Int64 rather than Int32 for Integer

require "jq"

class Request
  Jq.mapping({
    from:    {Time, ".range.from", "%FT%T.%LZ"},
    targets: {Array(String), ".targets[].target"},
    format:  String,
    max:     {Int64, ".maxDataPoints"},
  })
end

req = Request.from_json(str)
req.from     # => Time.new(2016,9,2,13,32,9,981)
req.targets  # => ["cpu","mem"]
req.format   # => "json"
req.max      # => 1299

Installation

Add this to your application's shard.yml:

dependencies:
  jq:
    github: maiha/jq.cr

Development

cd jq.cr
crystal deps   # install dependencies
crystal spec   # run specs

Contributing

1. Fork it ( https://github.com/maiha/jq.cr/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