Validation patterns and compliance checking for Kailash SDK including parameter validation, DataFlow pattern validation, connection validation, absolute import validation, workflow structure...
Validation patterns and compliance checking for Kailash SDK development.
results["node_id"]["result"] (not .result)| Validation | Catches | Key Pattern |
|---|---|---|
| Parameters | Missing/wrong-type params | Check before workflow.build() |
| Connections | Wrong 4-param format, nonexistent nodes | (src_id, src_param, tgt_id, tgt_param) |
| Workflow | Duplicate IDs, dead-ends, no entry point | Structural integrity |
| DataFlow | .result access, UUID conversion |
results["id"]["result"] |
| Imports | Relative imports, circular deps | Absolute imports only |
| Security | Hardcoded secrets, SQL injection | Env vars, parameterized queries |
from kailash.validation import WorkflowValidator
validator = WorkflowValidator(workflow)
results = validator.validate_all()
if not results.is_valid:
for error in results.errors:
print(f"Error: {error}")
.build() before executepython -m kailash.validation.cli validate-all
python -m kailash.validation.cli check-security
gold-standards-validator - Compliance checkingpattern-expert - Pattern validationtesting-specialist - Test validation