NullCheckValidator

Validates that specified columns exist and optionally checks for null values.

Basic Usage

from epftoolbox2.data.validators import NullCheckValidator

validator = NullCheckValidator(
    columns=["load_actual", "price"],
    allow_nulls=False,
)

result = validator.validate(df)
print(result.is_valid)  # True/False
print(result.errors)    # List of error messages

Parameters

Parameter	Type	Default	Description
`columns`	List[str]	Required	Columns to check
`allow_nulls`	bool	`False`	Whether nulls are allowed

ValidationResult

Field	Type	Description
`is_valid`	bool	True if validation passed
`errors`	List[str]	Error messages
`warnings`	List[str]	Warning messages
`info`	dict	Additional information

Example Output

result = validator.validate(df)

if not result.is_valid:
    for error in result.errors:
        print(f"Error: {error}")
    # Error: Column 'price' has 5 null values