JSON Loading

Basic Import

For JSON, use this import statement:

from yankee.json.schema import Schema, fields as f

Data Keys

Data keys can be defined in two ways. Either they are inferred from the fieldname, or they are defined expressly as JSONPath objects.

Inferred Data Keys: This library assumes that the input JSON document follows the typical JSON convention of using camelCase fieldnames, as opposed to the Python convention of using snake_case class attributes. As a result, field names are inflected into camelCase as part of the key inference process. So a field named “first_name” will use “firstName” as its data key.

Explicit Data Keys: If a data key is provided as a string, it is interpreted as a JSON Path expression. These expressions are supported by the jsonpath_ng library, which provides documentation on JSON Path syntax.

Input Documents

The JSON module is supported by the excellent UltraJSON library. For a JSON schema, the object passed to a Schemas .load method can be either string, or a dict object. If a dict object is provided, it is used directly. If a str object is provided, it is loaded using ujson.loads.

Complete Example

Take this:

{
        "name": "Johnny Appleseed",
        "birthdate": "2000-01-01",
        "something": [
            {"many": {
                "levels": {
                    "deep": 123
                }
            }}
        ]
    }

Do this:

from yankee.json.schema import Schema, fields as f

class JsonExample(Schema):
    name = f.String()
    birthday = f.Date("birthdate")
    deep_data = f.Int("something.0.many.levels.deep")

Get this:

{
    "name": "Johnny Appleseed",
    "birthday": datetime.date(2000, 1, 1),
    "deep_data": 123
}