JSONSchema is way of defining what shape your desired JSON should have and what certain fields type and content should be.

JSON Schema is a vocabulary that allows you to annotate and validate JSON documents.

project’s webiste: http://json-schema.org/

GREAT DOCS ❤️https://spacetelescope.github.io/understanding-json-schema/index.html

in python project you can use this pip installed package https://pypi.python.org/pypi/jsonschema

example validation:

from jsonschema import validate

schema = {
    "type": "object",
    "required": ["department", "employees"],
    "properties": {
        "department": {
            "type": "string"
        },
        "employees": {
            "type": "array",
            "items": {
                "type": "object",
                "required": ["firstName", "lastName", "age", "hobbys"],
                "properties": {
                    "firstName": {
                        "type": "string"
                    },
                    "lastName": {
                        "type": "string"
                    },
                    "age": {
                        "type": "integer"
                    },
                    "hireDate": {
                        "type": "string",
                        "pattern": "([12]\d{3}-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01]))$"
                    },
                    "hobbys": {
                        "type": "array",
                        "items": {
                            "type": "string"
                        },
                        "maxItems": 2
                    }
                }
            }
        }
    }
}

foo = {
    "department": "IT",
    "employees" : [
        {
            "firstName": "John", 
            "lastName": "Clever", 
            "age": 44,
            "hireDate": "2018-04-06",
            "hobbys": []
        },
        {
            "firstName": "Andi", 
            "lastName": "Kostanski", 
            "age": 29,
            "hireDate": "2018-04-06",
            "hobbys": [
                "triathlon",
                "skitour",
            ]
        }
    ]
}

validate(foo, schema)

Defining list of basic types vs list of objects

You define list of basic types, like e.g "hobbys" in employee just by defining "type" inside "items" dict:

"hobbys": {
    "type": "array",
    "items": {
        "type": "string"
    },
    "maxItems": 2
}

while if you need to define list of certain shape objects you have to define "type": "object" and define "type" of each "properties" inside "items" :

"employees": {
    "type": "array",
    "items": {
        "type": "object",
        "required": ["firstName", "lastName"],
        "properties": {
            "firstName": {
                "type": "string"
            },
            "lastName": {
                "type": "string"
            }
        }
    }
}

More options to validate:

each of field can be in required list to make it obligatory
for lists you can define maxItems, minItems to control allowed number of objects.
for ensuring list object uniqness just provide "uniqueItems": true this works only on basic data types (not on objects)
you can validate strings with regex by using pattern like in above example for valid date in YYYY-MM-DD
tuple validation may be something nice for structured data types https://spacetelescope.github.io/understanding-json-schema/reference/array.html#tuple-validation

Usefull links of docs with greate examples: