Coverage for presidio_analyzer / predefined_recognizers / country_specific / spain / es_nie_recognizer.py: 95%
20 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 EsNieRecognizer(PatternRecognizer):
7 """
8 Recognize NIE number using regex and checksum.
10 Reference(s):
11 https://es.wikipedia.org/wiki/N%C3%BAmero_de_identidad_de_extranjero
12 https://www.interior.gob.es/opencms/ca/servicios-al-ciudadano/tramites-y-gestiones/dni/calculo-del-digito-de-control-del-nif-nie/
14 :param patterns: List of patterns to be used by this recognizer
15 :param context: List of context words to increase confidence in detection
16 :param supported_language: Language this recognizer supports
17 :param supported_entity: The entity this recognizer can detect
18 :param replacement_pairs: List of tuples with potential replacement values
19 for different strings to be used during pattern matching.
20 This can allow a greater variety in input, for example by removing dashes
21 or spaces.
22 """
24 PATTERNS = [
25 Pattern(
26 "NIE",
27 r"\b[X-Z]?[0-9]?[0-9]{7}[-]?[A-Z]\b",
28 0.5,
29 ),
30 ]
32 CONTEXT = ["número de identificación de extranjero", "NIE"]
34 def __init__(
35 self,
36 patterns: Optional[List[Pattern]] = None,
37 context: Optional[List[str]] = None,
38 supported_language: str = "es",
39 supported_entity: str = "ES_NIE",
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 )
56 def validate_result(self, pattern_text: str) -> bool:
57 """Validate the pattern by using the control character."""
59 pattern_text = EntityRecognizer.sanitize_value(
60 pattern_text, self.replacement_pairs
61 )
63 letters = "TRWAGMYFPDXBNJZSQVHLCKE"
64 letter = pattern_text[-1]
66 # check last is a letter, and first is in X,Y,Z
67 if not pattern_text[1:-1].isdigit or pattern_text[:1] not in "XYZ":
68 return False
69 # check size is 8 or 9
70 if len(pattern_text) < 8 or len(pattern_text) > 9:
71 return False
73 # replace XYZ with 012, and check the mod 23
74 number = int(str("XYZ".index(pattern_text[0])) + pattern_text[1:-1])
75 return letter == letters[number % 23]