Validation Functions
assert_not_blurry
assert_not_blurry(input_val)
Determines whether the input image is not blurry. In order to use this function, make sure to enable this flag in the Process Files step by setting "detect_blurry_files" to true in the OCR Config box. Args: input_val (dict): Any IBOCR Record dictionary. Returns: True if validation is successful. Otherwise, throws an Exception and report blur factor.
assert_not_empty
assert_not_empty(input_val)
Determines whether the input value exists. If the input is a string, will validate if the string has a length > 0. Args: input_val (Any): Any input. Returns: True if validation is successful. Otherwise, throws an Exception. Examples: assert_not_empty('') -> False
assert_true
assert_true(input_val)
Determines whether the input value is true. Args: input_val (Any): Any input. Returns: True if validation is successful. Otherwise, throws an Exception. Examples: assert_true(10 == 15) -> False
cast
cast(val, casted_type)
Casts a value to a specific type. Casting is needed for validation, as every field must return a specific type to be re-run. For example, IF() can return any type, therefore, one must cast the output to the desired type. Args: val (Any): Any input. casted_type (str): An allowed type for casting. Returns: The value passed into it, but adjusts the registered return type used for validation. Examples: cast(INPUT_COL, 'string') -> INPUT_COL
validate
validate(validation_formulas)
Provide rules to validate a given field. Args: validation_formulas (list[str]): A list of strings (with quotes). Each string is a formula containing a validator. Returns: A dictionary represented as a JSON string. Will have a "status" field, which is set to "OK" if validation was successful, else "ERROR". If status "ERROR", it will have a "msgs" field too, a list of each error message string. Examples: validate(['assert_not_empty(INPUT_COL)']) -> '{"status":"OK"}'