There are several scenarios where we need different types of JSON validation. In this article, we will cover the following. Here, we will have a look at how to validate incoming JSON data. To check if all required fields are present in the JSON and validate the data.

Here, we would also know how to check valid JSON before parsing it. For example, if you are working with the API, what if it returns a valid JSON or other data? Here, we will validate the appropriate JSON format standard conventions with the help of JSON validator and JSON path validator.

Check if a string is valid or not?

When we receive a response from any JSON API, we have to check valid JSON before performing any operation using these data. There are various ways to validate the corresponding JSON format standard conventions.

Using json.loads and json.load () method.

As we know, the JSON module provides two methods to parse JSON data using Python.

json.loads (): To parse JSON from String.

json.load () to parse JSON file.

Both methods will throw ValueError if the string or pass the data can not be rendered as JSON. When we receive a JSON response, we can pass it on to JSON.loads () method to check format validator as per the standard convention and to check valid JSON. Let’s look at an example.

import JSON

def validateJSON (jsonData):

    try:

        json.loads (jsonData)

    except ValueError as err:

        return False

    returns True

InvalidJsonData = "" "{" name ":" jane doe "," salary ": 9000," email ":" [email protected] "}" ""

isValid = validateJSON (InvalidJsonData)

print ( "JSON string Given Day", isValid)

validJsonData = "" "{" name ":" jane doe "," salary ": 9000," email ":" [email protected] "}" ""

isValid = validateJSON (validJsonData)

print ( "JSON string Given Day", isValid)

Output:

Given JSON string False Day

Given JSON string True Day

As you can see in the first instance, we passed a JSON string to check valid JSON that is not valid with the load method. In the first JSON data, we have added an extra comma to make it invalid because it produces the ValueError JSON.loads process.

On the second call, we pass a valid JSON document and successfully parsed the JSON.loads method.

Validation JSON File

Let’s assume that you want to parse JSON files using Python. Instead of directly parsing it, we need to validate that we can check if JSON is valid. Let’s see how to use the command-line options from the JSON.tool module to check valid JSON file containing JSON data.

the contents of the file before running the following command

Command:

python -m JSON.tool fileName

Example:

python -m JSON.tool studentDetails.json

We received the following error, for the contents of the file are not validated using JSON format validator.

Error expects property names enclosed in double quotes: row 1 column 2 (char 1)

The same command is executed after correcting errors.

JSON Schema validation using Python

Sometimes we need something extra than just a standard JSON validation. That is, we will see how to validate incoming JSON data to examine all the necessary fields. Fields present in the JSON file or the response and check valid JSON data type the area.

The scenarios include the following:

We need data from JSON filed in the kind we want. For example, we want all numeric fields in the number format, not the number encoded in a format string. For example this Marks: “75” to use it directly instead of checking out and changing them at any time.

We need to use the library JSON schema. This library is useful to check valid JSON. Libraries use the format to make the validation based on the scheme given. JSON schema implementation of JSON Schema for Python.

Using JSON schema, we can make our choice scheme, so whenever we can validate the JSON document on this scheme, if passed, we can say that the form is valid JSON. You should follow the below-mentioned steps when dealing with JSON data files and validating their syntax and semantics.

  • First, install the JSON schema using the pip command. pip install JSON schema
  • Define the Schema: Describe what you expect JSON.
  • Convert JSON to a Python object using JSON.load or JSON.loads methods.
  • Pass the resulting JSON to a () method to validate from JSON schema a. This method will raise an exception if the given JSON is not what is described in the schema.

Conclusion

JSON has always been the top choice of developers dealing with websites. Its human-readable format is easy to understand which makes writing programs, fetching data, and later on, modifying them easier. So that was all the way to validate JSON data return. To check valid JSON, there are no more offline tools required as you can do it on the go from any of your smart handheld devices.