Coverage for presidio_analyzer / predefined_recognizers / country_specific / uk / uk_nhs_recognizer.py: 100%

1from typing import List, Optional, Tuple 

2 

3from presidio_analyzer import EntityRecognizer, Pattern, PatternRecognizer 

4 

5 

6class NhsRecognizer(PatternRecognizer): 

7 """ 

8 Recognizes NHS number using regex and checksum. 

9 

10 :param patterns: List of patterns to be used by this recognizer 

11 :param context: List of context words to increase confidence in detection 

12 :param supported_language: Language this recognizer supports 

13 :param supported_entity: The entity this recognizer can detect 

14 :param replacement_pairs: List of tuples with potential replacement values 

15 for different strings to be used during pattern matching. 

16 This can allow a greater variety in input, for example by removing dashes or spaces. 

17 """ 

18 

19 PATTERNS = [ 

20 Pattern( 

21 "NHS (medium)", 

22 r"\b([0-9]{3})[- ]?([0-9]{3})[- ]?([0-9]{4})\b", 

23 0.5, 

24 ), 

25 ] 

26 

27 CONTEXT = [ 

28 "national health service", 

29 "nhs", 

30 "health services authority", 

31 "health authority", 

32 ] 

33 

34 def __init__( 

35 self, 

36 patterns: Optional[List[Pattern]] = None, 

37 context: Optional[List[str]] = None, 

38 supported_language: str = "en", 

39 supported_entity: str = "UK_NHS", 

40 replacement_pairs: Optional[List[Tuple[str, str]]] = None, 

41 name: Optional[str] = None, 

42 ): 

43 self.replacement_pairs = ( 

44 replacement_pairs if replacement_pairs else [("-", ""), (" ", "")] 

45 ) 

46 patterns = patterns if patterns else self.PATTERNS 

47 context = context if context else self.CONTEXT 

48 super().__init__( 

49 supported_entity=supported_entity, 

50 patterns=patterns, 

51 context=context, 

52 supported_language=supported_language, 

53 name=name, 

54 ) 

55 

56 def validate_result(self, pattern_text: str) -> bool: 

57 """ 

58 Validate the pattern logic e.g., by running checksum on a detected pattern. 

59 

60 :param pattern_text: the text to validated. 

61 Only the part in text that was detected by the regex engine 

62 :return: A bool indicating whether the validation was successful. 

63 """ 

64 text = EntityRecognizer.sanitize_value(pattern_text, self.replacement_pairs) 

65 total = sum( 

66 [int(c) * multiplier for c, multiplier in zip(text, reversed(range(11)))] 

67 ) 

68 remainder = total % 11 

69 check_remainder = remainder == 0 

70 

71 return check_remainder