A declarative, dynamic and simple object mapper

Butterfly is a declarative and dynamic object mapper tool built to do the object mapping seamless and easy. This tool is not suited to be used in an application needing high throughput as it does a lot of string a manipulation and lookups. The real use for this library is where some dynamic behavior is needed in some app and some kind of dynamic object mapping is required based on some mapping file.

The usage of butterfly is very easy. You have some date to work on and have a domain type which you need to map the data into. Take the example data in the test data weather.json. The data looks like this:

{
  "coord": {
    "lon": -0.13,
    "lat": 51.51
  },
  "weather": [
    {
      "id": 300,
      "main": "Drizzle",
      "description": "light intensity drizzle",
      "icon": "09d"
    }
  ],
  "base": "stations",
  "main": {
    "temp": 280.32,
    "pressure": 1012,
    "humidity": 81,
    "temp_min": 279.15,
    "temp_max": 281.15
  },
  "visibility": 10000,
  "wind": {
    "speed": 4.1,
    "deg": 80
  },
  "clouds": {
    "all": 90
  },
  "dt": 1485789600,
  "sys": {
    "type": 1,
    "id": 5091,
    "message": 0.0103,
    "country": "GB",
    "sunrise": 1485762037,
    "sunset": 1485794875
  },
  "id": 2643743,
  "name": "London",
  "cod": 200
}

and need to be mapped to a type looks like this (as some app needs the data in this format)

{
	"weather": {
		"location": {
			"longitude": -0.13,
			"latitude": 51.51,
			"name": "London"
		},
		"temperature": 280.32,
		"pressure": 1012,
		"humidity": 81,
		"visibility": 10000,
		"wind": {
			"speed": 4.1,
			"degree": 80
		}
	},
	"data": [
		{
			"id": 300,
			"forcast": "light intensity drizzle"
		}
	]
}

For the above to achieve, here is the mapping file:

{
  "coord": {
    "lon": "weather.location.longitude",
    "lat": "weather.location.latitude"
  },
  "weather": [
    {
      "id": "weather.data[].id",
      "description": "weather.data[].forcast"
    }
  ],
  "main": {
    "temp": "weather.temperature",
    "pressure": "weather.pressure",
    "humidity": "weather.humidity"
  },
  "visibility": "weather.visibility",
  "wind": {
    "speed": "weather.wind.speed",
    "deg": "weather.wind.degree"
  },
  "name": "weather.location.name"
}

As it can be seen the mapping file looks exactly the same like the actual data. This is because it is the data file, but we have added the mapping keys of the type to which it needs to be mapped to. For the simple keys, it is evident how it is working and for the list types, we have to keep just one item in the list and have the mapping there. Butterfly will automatically create the list objects properly converted according to the mapping and the list will have the same number of items that the data file originally had.

Here in the example we have only one item, but it works for how many items it is there.

Note For list items, the mapping has to be correctly configured and the [] list operator has to be there in proper position according to the domain type.

from butterfly.engine import transform

result = transform("testdata/weather.json", "testdata/weather-mapping.json")
print(json.dumps(result))