validation-patterns

What problem does it solve?

Manual code review and compliance checking are time-consuming and error-prone. This Skill automates the validation of Kailash SDK code, ensuring it adheres to best practices and security standards, preventing bugs and deployment issues.

Core Features & Use Cases

• Comprehensive Validation: Checks parameters, connections, workflow structure, DataFlow patterns, absolute imports, and security.
• Automated Code Review: Integrates into pre-commit hooks or CI/CD pipelines to enforce code quality.
• Use Case: Before deploying a new Kailash workflow, use this Skill to automatically verify all parameters are correct, connections are valid, and no security vulnerabilities exist, saving hours of manual auditing.

Quick Start

Example: Automated workflow validation

from kailash.validation import WorkflowValidator

Assuming 'workflow' is your WorkflowBuilder instance

validator = WorkflowValidator(workflow) results = validator.validate_all() if not results.is_valid: for error in results.errors: print(f"Error: {error}")