Validating JSON Data with Python and JSON Schema

Validating JSON Data with Python and JSON Schema

Introduction

This is a short tutorial on how to use Python to validate JSON file data. Rather than iterating through all the fields in the JSON, usage of libraries like JSONschema etc. are considered more efficient. Hence, I thought of sharing my experience.

Prerequisites

Python Installation: Ensure Python is installed on your system. If not, download and install it from the official Python website.
JSON Files:
- Weather Data File (weather.json): A JSON file containing weather data, typically obtained from weather APIs e.g. weatherapi.
- JSON Schema File (weather_schema.json): A JSON schema file that defines the expected structure, required fields, and data types of the weather data JSON. Tools like Quicktype or JSON Schema Tool can help generate a schema from a JSON example.
jsonschema Library: This Python library is used for validating JSON data against a schema.

Install it using pip: pip install jsonschema

How to Run the Script

Prepare Your JSON Files: Ensure your weather.json and weather_schema.json are placed in the same directory as your script.
Run the Script: Open Visual Studio Code, create a Python file or a Jupyter notebook

And copy-paste the code below. Adjust as needed.

import json
from jsonschema import validate, ValidationError

# Load the JSON data and schema
with open('weather.json', 'r') as file:
    weather_data = json.load(file)

with open('weather_schema.json', 'r') as file:
    schema = json.load(file)

# Function to validate JSON
def is_valid_json(data, schema):
    try:
        validate(instance=data, schema=schema)
        return True
    except ValidationError as ve:
        print(f"Validation error: {ve}")
        return False

# Validate the weather data
if is_valid_json(weather_data, schema):
    print("Validation Successful!")
else:
    print("Validation Failed!")

Run and debug using the editor.

Code Overview

The script consists of the following components:

Loading JSON Data and Schema: We use Python’s built-in json module to load the weather data and the schema from their respective files.
Validation Logic: Utilizing the jsonschema.validate() function, we check if the JSON data adheres to the schema, capturing any validation errors that might indicate discrepancies.
Error Handling: The script identifies and prints specific validation errors, making it easier to pinpoint issues in the data or the schema.

Conclusion

This code can be further enhanced to be included in an Azure Function. For example, if you are fetching data as JSON format from a web API, this code can be added there to perform data validation.

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