How to Validate JSON Schema using Python

by DonOfDen


Posted on 15 Mar 2020

Tags: Python JSON schema validation


python-validate-json-schema

This blog post will help you understand JSON Schema validation in Python, which uses Jsonschema the most complete and compliant JSON Schema validator.

GITHUB Project: python-validate-json-schema

JSON Schema

JSON Schema is a specification for JSON based format for defining the structure of JSON data. It was written under IETF draft which expired in 2011. JSON Schema.

  • Describes your existing data format.
  • Clear, human- and machine-readable documentation.
  • Complete structural validation, useful for automated testing.
  • Complete structural validation, validating client-submitted data.

Currently the most complete and compliant JSON Schema validator available for python is Jsonschema.

Given below is a basic JSON schema, which covers a basic user details.

{
   "$schema":"http://json-schema.org/draft-04/schema#",
   "title":"User",
   "description":"A user request json",
   "type":"object",
   "properties":{
      "id":{
         "description":"The unique identifier for a user",
         "type":"integer"
      },
      "name":{
         "description":"Name of the user",
         "type":"string"
      },
      "contact_number":{
         "type":"number"
      }
   },
   "required":[
      "id",
      "name",
      "contact_number"
   ]
}

jsonschema is an implementation of JSON Schema for Python. Using jsonschema, we can create a schema of our choice, so every time we can validate the JSON document against this schema, if it passed, we could say that the JSON document is valid.

Keyword Description
$schema The $schema keyword states that this schema is written according to the draft v4 specification.
title You will use this to give a title to your schema.
description A little description of the schema.
type The type keyword defines the first constraint on our JSON data: it has to be a JSON Object.
properties Defines various keys and their value types, minimum and maximum values to be used in JSON file.
required This keeps a list of required properties.
minimum This is the constraint to be put on the value and represents minimum acceptable value.
exclusiveMinimum If “exclusiveMinimum” is present and has boolean value true, the instance is valid if it is strictly greater than the value of “minimum”.
maximum This is the constraint to be put on the value and represents maximum acceptable value.
exclusiveMaximum If “exclusiveMaximum” is present and has boolean value true, the instance is valid if it is strictly lower than the value of “maximum”.
multipleOf A numeric instance is valid against “multipleOf” if the result of the division of the instance by this keyword’s value is an integer.
maxLength The length of a string instance is defined as the maximum number of its characters.
minLength The length of a string instance is defined as the minimum number of its characters.
pattern A string instance is considered valid if the regular expression matches the instance successfully.

You can check a http://json-schema.org for the complete list of keywords that can be used in defining a JSON schema. The above schema can be used to test the validity of the following JSON code

First, install jsonschema using pip command.

pip install jsonschema

Python Script:

import json
import jsonschema
from jsonschema import validate


def get_schema():
    """This function loads the given schema available"""
    with open('user_schema.json', 'r') as file:
        schema = json.load(file)
    return schema


def validate_json(json_data):
    """REF: https://json-schema.org/ """
    # Describe what kind of json you expect.
    execute_api_schema = get_schema()

    try:
        validate(instance=json_data, schema=execute_api_schema)
    except jsonschema.exceptions.ValidationError as err:
        print(err)
        err = "Given JSON data is InValid"
        return False, err

    message = "Given JSON data is Valid"
    return True, message


# Convert json to python object.
jsonData = json.loads('{"id" : "10","name": "DonOfDen","contact_number":1234567890}')

# validate it
is_valid, msg = validate_json(jsonData)
print(msg)

Input Json

{"id" : 10,"name": "DonOfDen","contact_number":1234567890}
  • We first convert the input JSON in to python object using json.loads then using jsonschema function validate we validate the given input with the JSON Schema provided.

If you try to run the above script, the output will be Given JSON data is Valid.

Testing with other type of input

Lets test with alternative json input, If you check th python script above The validate() method will raise an exception if given JSON is not what is described in the schema.

{"id" : "10","name": "DonOfDen","contact_number":1234567890}

In the above input json we have modified "id" : 10 from integer to "id" : "10" string.

'10' is not of type 'integer'

Failed validating 'type' in schema['properties']['id']:
    {'description': 'The unique identifier for a user', 'type': 'integer'}

On instance['id']:
    '10'
Given JSON data is InValid

Reference:


Please refer python-validate-json-schema one of my project where I learnt how to implement the above.

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