Coverage for presidio_analyzer / predefined_recognizers / country_specific / australia / au_medicare_recognizer.py: 100%
19 statements
« prev ^ index » next coverage.py v7.13.1, created at 2026-03-29 09:03 +0000
« prev ^ index » next coverage.py v7.13.1, created at 2026-03-29 09:03 +0000
1from typing import List, Optional, Tuple
3from presidio_analyzer import EntityRecognizer, Pattern, PatternRecognizer
6class AuMedicareRecognizer(PatternRecognizer):
7 """
8 Recognizes Australian Medicare number using regex, context words, and checksum.
10 Medicare number is a unique identifier issued by Australian Government
11 that enables the cardholder to receive a rebates of medical expenses
12 under Australia's Medicare system.
13 It uses a modulus 10 checksum scheme to validate the number.
14 Reference: https://en.wikipedia.org/wiki/Medicare_card_(Australia)
17 :param patterns: List of patterns to be used by this recognizer
18 :param context: List of context words to increase confidence in detection
19 :param supported_language: Language this recognizer supports
20 :param supported_entity: The entity this recognizer can detect
21 :param replacement_pairs: List of tuples with potential replacement values
22 for different strings to be used during pattern matching.
23 This can allow a greater variety in input, for example by removing dashes or spaces.
24 """
26 PATTERNS = [
27 Pattern(
28 "Australian Medicare Number (Medium)",
29 r"\b[2-6]\d{3}\s\d{5}\s\d\b",
30 0.1,
31 ),
32 Pattern(
33 "Australian Medicare Number (Low)",
34 r"\b[2-6]\d{9}\b",
35 0.01,
36 ),
37 ]
39 CONTEXT = [
40 "medicare",
41 ]
43 def __init__(
44 self,
45 patterns: Optional[List[Pattern]] = None,
46 context: Optional[List[str]] = None,
47 supported_language: str = "en",
48 supported_entity: str = "AU_MEDICARE",
49 replacement_pairs: Optional[List[Tuple[str, str]]] = None,
50 name: Optional[str] = None,
51 ):
52 self.replacement_pairs = (
53 replacement_pairs if replacement_pairs else [("-", ""), (" ", "")]
54 )
55 patterns = patterns if patterns else self.PATTERNS
56 context = context if context else self.CONTEXT
57 super().__init__(
58 supported_entity=supported_entity,
59 patterns=patterns,
60 context=context,
61 supported_language=supported_language,
62 name=name,
63 )
65 def validate_result(self, pattern_text: str) -> bool:
66 """
67 Validate the pattern logic e.g., by running checksum on a detected pattern.
69 :param pattern_text: the text to validated.
70 Only the part in text that was detected by the regex engine
71 :return: A bool indicating whether the validation was successful.
72 """
73 # Pre-processing before validation checks
74 text = EntityRecognizer.sanitize_value(pattern_text, self.replacement_pairs)
75 medicare_list = [int(digit) for digit in text if not digit.isspace()]
77 # Set weights based on digit position
78 weight = [1, 3, 7, 9, 1, 3, 7, 9]
80 # Perform checksums
81 sum_product = 0
82 for i in range(8):
83 sum_product += medicare_list[i] * weight[i]
84 remainder = sum_product % 10
85 return remainder == medicare_list[8]