What type is my JSON? Ask our Markov chain!

In this blog post, we explain how we used a Markov chain to detect whether a JSON object represents a class (fixed properties) or a map (dynamic keys) to infer its type and generate the same code a human programmer would for representing that data.

For example, given this Bitcoin API data:

    {

        "0000000000000000000e222e4e7afc29c49f6398783a94c846dee2e13c6408f5": {
            "size": 969709,
            "height": 510599,
            "difficulty": 3007383866429.732,
            "previous": "000000000000000000552a7783efd39eaa1c5ff6789e21a0bbe7547bc454fced"
        },
        "000000000000000000552a7783efd39eaa1c5ff6789e21a0bbe7547bc454fced": {
            "size": 991394,
            "height": 510598,
            "difficulty": 3007383866429.732,
            "previous": "00000000000000000043aba4c065d4d92aec529566287ebec5fe9010246c9589"
        },
        "00000000000000000043aba4c065d4d92aec529566287ebec5fe9010246c9589": {
            "size": 990527,
            "height": 510597,
            "difficulty": 3007383866429.732,
            "previous": "00000000000000000009025b9e95911a4dc050de129ea4eb5e40ef280751a0cb"
        }
    }

You'd expect the corresponding Swift code:

    typealias Blocks = [String: Block] // a.k.a. Dictionary<String, Block>

    struct Block {
        let size, height: Int
        let difficulty: Double
        let previous: String
    }

Rather than:

    struct Blocks {
        let _0000000000000000000e222e4e7afc29c49f6398783a94c846dee2e13c6408f5: Block
        let _00000000000000000043aba4c065d4d92aec529566287ebec5fe9010246c9589: Block
        let _00000000000000000009025b9e95911a4dc050de129ea4eb5e40ef280751a0cb: Block
    }

    struct Block {
        let size, height: Int
        let difficulty: Double
        let previous: String
    }

We taught quicktype to make the same decision by evaluating the JSON property names with a Markov chain trained on simulated class property names. Our blog article goes into detail and lets you play with our Markov chain!