schema_validator

Name: schema_validator
Availability: InStock
Author: cas-bigdatalab

Validate structured data against JSON schemas with field and constraint checks.

541|171|Updated May 3, 2018

Search Tags:#structured data #data integrity #data validation #json schema #schema compliance

Ready to run

npx skills add https://github.com/cas-bigdatalab/piflow --skill schema-validator-cas-bigdatalab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: schema_validator
Source: https://github.com/cas-bigdatalab/piflow/tree/main/workspace/skills/schema_validator
Command: npx skills add https://github.com/cas-bigdatalab/piflow --skill schema-validator-cas-bigdatalab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps ensure that data conforms to the specified schema, providing a quick and accurate way to validate data integrity.

Core Features & Use Cases

Data Validation: Checks if data adheres to the provided schema.
Field Verification: Validates fields for existence, type, format, and constraints.
Use Case: It can be used in data preprocessing workflows to filter out data that does not conform to a predefined structure.

Quick Start

Use the schema_validator skill to validate the data in 'customer_data.json' against the schema 'customer_schema.json'.

Frequently Asked Questions about schema_validator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I validate structured data against a JSON schema?▼

To validate structured data against a JSON schema, you need to provide both the data file and the schema definition. The validator checks if the data conforms to specified field types, constraints, and table-level rules to ensure data integrity.

What is JSON schema compliance and when do I need it?▼

JSON schema compliance ensures structured data matches defined field types and constraints. You need it during data preprocessing or integrity checks to filter out records that do not conform to a predefined structure.

How do I check if my JSON data matches required field types and constraints?▼

You can check JSON data against required field types and constraints by validating it with a defined JSON schema. This process verifies field existence, format, and table-level constraints to confirm data conformity.

Can I use schema validation in data preprocessing workflows to filter bad records?▼

Yes, you can use schema validation in data preprocessing workflows. By checking data against a JSON schema, you can effectively filter out non-conforming records and ensure downstream data integrity.

Does the validator check both field-level and table-level constraints?▼

Yes, the validator checks both field-level and table-level constraints. It ensures structured data conforms to specified field types, formats, and existence rules, alongside broader table-level constraints defined in the JSON schema.

What format do I need to define rules in to verify data integrity?▼

You need to define rules in JSON format to verify data integrity. The validation process requires a JSON schema definition to check if your structured data adheres to the specified constraints.