JSON Schema Validator
Validate JSON documents against JSON Schema (Draft 7) specifications.
Features
- Schema Validation: Validate JSON against schema
- Error Details: Detailed validation error messages
- Batch Validation: Validate multiple files
- Schema Generation: Generate schema from examples
- Multiple Drafts: Support for Draft 4, 6, 7
Quick Start
from json_validator import JSONValidator
validator = JSONValidator()
# Validate data against schema
schema = {
"type": "object",
"properties": {
"name": {"type": "string"},
"age": {"type": "integer", "minimum": 0}
},
"required": ["name"]
}
data = {"name": "John", "age": 30}
result = validator.validate(data, schema)
print(f"Valid: {result['valid']}")
CLI Usage
# Validate JSON file against schema
python json_validator.py --data user.json --schema user_schema.json
# Validate with inline schema
python json_validator.py --data config.json --schema '{"type": "object"}'
# Generate schema from sample
python json_validator.py --generate sample.json --output schema.json
# Batch validate directory
python json_validator.py --data-dir ./configs/ --schema config_schema.json
API Reference
JSONValidator Class
class JSONValidator:
def __init__(self, draft: str = "draft7")
# Validation
def validate(self, data: dict, schema: dict) -> dict
def validate_file(self, data_path: str, schema_path: str) -> dict
def validate_batch(self, data_files: list, schema: dict) -> list
# Schema operations
def generate_schema(self, data: dict) -> dict
def check_schema(self, schema: dict) -> dict
Validation Result
{
"valid": True, # or False
"errors": [], # List of error details
"path": "$", # JSON path to data root
}
# With errors:
{
"valid": False,
"errors": [
{
"message": "'name' is a required property",
"path": "$",
"schema_path": "required"
},
{
"message": "-5 is less than minimum 0",
"path": "$.age",
"schema_path": "properties.age.minimum"
}
]
}
Schema Examples
Object Schema
schema = {
"type": "object",
"properties": {
"id": {"type": "integer"},
"name": {"type": "string", "minLength": 1},
"email": {"type": "string", "format": "email"},
"active": {"type": "boolean", "default": True}
},
"required": ["id", "name", "email"],
"additionalProperties": False
}
Array Schema
schema = {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {"type": "integer"},
"value": {"type": "number"}
}
},
"minItems": 1,
"uniqueItems": True
}
Nested Schema
schema = {
"type": "object",
"properties": {
"user": {
"type": "object",
"properties": {
"name": {"type": "string"},
"address": {
"type": "object",
"properties": {
"street": {"type": "string"},
"city": {"type": "string"}
}
}
}
}
}
}
Generate Schema from Data
validator = JSONValidator()
sample_data = {
"name": "Product A",
"price": 29.99,
"tags": ["electronics", "sale"],
"inStock": True
}
schema = validator.generate_schema(sample_data)
# Returns inferred schema based on data types
Supported Keywords
Type Validation
type: string, number, integer, boolean, array, object, nullenum: allowed valuesconst: exact value
String Validation
minLength,maxLengthpattern: regex patternformat: email, uri, date, date-time, ipv4, ipv6, uuid
Number Validation
minimum,maximumexclusiveMinimum,exclusiveMaximummultipleOf
Array Validation
items: schema for itemsminItems,maxItemsuniqueItemscontains
Object Validation
properties: property schemasrequired: required propertiesadditionalPropertiesminProperties,maxPropertiespatternProperties
Error Handling
result = validator.validate(data, schema)
if not result['valid']:
for error in result['errors']:
print(f"Error at {error['path']}: {error['message']}")
Dependencies
- jsonschema>=4.20.0