Validate Json Data Using Python

August 29, 2023 Post a Comment

I need to create a function that validates incoming json data and returns a python dict. It should check if all necessary fields are present in a json file and also validate the da

Solution 1:

If you haven't check jsonschema library, it can be useful to validate data. JSON Schema is a way to describe the content of JSON. The library just uses the format to make validations based on the given schema.

I made a simple example from basic usage.

import json
from jsonschema import validate

# Describe what kind of json you expect.
schema = {
    "type" : "object",
    "properties" : {
        "description" : {"type" : "string"},
        "status" : {"type" : "boolean"},
        "value_a" : {"type" : "number"},
        "value_b" : {"type" : "number"},
    },
}

# Convert json to python object.
my_json = json.loads('{"description": "Hello world!", "status": true, "value_a": 1, "value_b": 3.14}')

# Validate will raise exception if given json is not# what is described in schema.
validate(instance=my_json, schema=schema)

# print for debugprint(my_json)

Solution 2:

As you're using a JSON file, you can use this example:

import json
defvalidate(filename):
    withopen(filename) as file:
        try:
            return json.load(file) # put JSON-data to a variableexcept json.decoder.JSONDecodeError:
            print("Invalid JSON") # in case json is invalidelse:
            print("Valid JSON") # in case json is valid

Solution 3:

I had the same problem and was dissatisfied with the existing solution of using jsonschema. It gives terrible error messages that are not at all user-friendly.

I wrote my own library to define schemas, which has a lot of additional functionality over jsonschema:

https://github.com/FlorianDietz/syntaxTrees

It gives very precise error messages, allows you to write code to customize the validation process, lets you define functions that operate on the validated JSON, and even creates HTML documentation for the schemas you define.

Schemas are defined as classes, similar to how Django defines models:

classMyExampleNode(syntaxTreesBasics.Node):
    field_1 = fields.Float(default=0)
    field_2 = fields.String()
    field_3 = fields.Value('my_example_node', null=True, default=None)
    classMeta:
        name = 'my_example_node'

Solution 4:

The jsonschema and syntax trees are overkill just to find basic syntax errors, and the try/except solution provides no hints as to where. This minor improvement provides the error message you need to find the problem:

import json
defvalidate(filename):
    withopen(filename) as file:
        try:
            return json.load(file) # put JSON-data to a variableexcept json.decoder.JSONDecodeError as err:
            print(f"Invalid JSON: {err}") # in case json is invalidelse:
            print("Valid JSON") # in case json is valid

For example, with this in the file:

{"a": 123, 'b': 456}

it will provide:

invalid JSON: Expecting property name enclosed indouble quotes: line 1column12 (char11)

That is the sort of hint a user will need to locate the issue without the overhead of creating a full schema.

Solution 5:

While Jsonschema module is good but documentation is missing complex examples. And library not reporting any errors for invalid schema just ignoring!

This is example:

from jsonschema import validate

set_tl_schema = {
    "type" : "object",
    "properties" :  {

    "level": {
      "value": {"type" : "number"},
      "updatedAt": {"type" : "number"}
    }
}
}

x = {'level': {'updatedAt': '1970-01-01T00:00:00.000Z', 'value': 1}, }

try:
    validate(instance=x, schema=set_tl_schema)
except jsonschema.exceptions.ValidationError as ex:
    print(ex)

Mistake was that level also need properties field. But validator never report you that.

I found very efficient and easy to use module:

https://pypi.org/project/json-checker/

>>>from json_checker import Checker>>>current_data = {'first_key': 1, 'second_key': '2'}>>>expected_schema = {'first_key': int, 'second_key': str}>>>checker = Checker(expected_schema)>>>result = checker.validate(current_data)

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