Coverage for src/csv_schema_validator/schema_validator.py: 20%

1# schema_validator.py 

2from pydantic import ValidationError 

3from .schema_models import CSVSchema 

4 

5 

6def validate_schema_structure(schema_dict: dict) -> dict: 

7 """ 

8 Validate the structure of a CSV schema. 

9 

10 Args: 

11 schema_dict: Dictionary containing the schema definition 

12 

13 Returns: 

14 Dictionary with validation results: 

15 - is_valid: Boolean indicating if schema is valid 

16 - errors: List of validation errors 

17 - validated_schema: Pydantic model instance if valid 

18 """ 

19 try: 

20 validated_schema = CSVSchema(**schema_dict) 

21 return {"is_valid": True, "errors": [], "validated_schema": validated_schema} 

22 except ValidationError as e: 

23 errors = [] 

24 for error in e.errors(): 

25 errors.append( 

26 { 

27 "field": ".".join(str(x) for x in error["loc"]), 

28 "message": error["msg"], 

29 "type": error["type"], 

30 "input": error["input"], 

31 } 

32 ) 

33 

34 return {"is_valid": False, "errors": errors, "validated_schema": None} 

35 except TypeError as e: 

36 return { 

37 "is_valid": False, 

38 "errors": [{"error_type": "invalid_schema", "error_message": str(e)}], 

39 "schema_value": schema_dict, 

40 } 

41 except Exception as e: 

42 return { 

43 "is_valid": False, 

44 "errors": [{"error_type": "unknown_error", "error_message": str(e)}], 

45 "schema_value": schema_dict, 

46 "validated_schema": validated_schema, 

47 }