1 # SPDX-License-Identifier: GPL-3.0-or-later
3 # This file is part of Nominatim. (https://nominatim.org)
5 # Copyright (C) 2024 by the Nominatim developer community.
6 # For a full list of authors see the git log.
8 Specialized processor for housenumbers. Analyses common housenumber patterns
9 and creates variants for them.
11 from typing import Any, List, cast
14 from ...data.place_name import PlaceName
15 from .generic_mutation import MutationVariantGenerator
17 RE_NON_DIGIT = re.compile('[^0-9]')
18 RE_DIGIT_ALPHA = re.compile(r'(\d)\s*([^\d\s␣])')
19 RE_ALPHA_DIGIT = re.compile(r'([^\s\d␣])\s*(\d)')
20 RE_NAMED_PART = re.compile(r'[a-z]{4}')
22 # Configuration section
25 def configure(*_: Any) -> None:
26 """ All behaviour is currently hard-coded.
33 def create(normalizer: Any, transliterator: Any, config: None) -> 'HousenumberTokenAnalysis':
34 """ Create a new token analysis instance for this module.
36 return HousenumberTokenAnalysis(normalizer, transliterator)
39 class HousenumberTokenAnalysis:
40 """ Detects common housenumber patterns and normalizes them.
42 def __init__(self, norm: Any, trans: Any) -> None:
46 self.mutator = MutationVariantGenerator('␣', (' ', ''))
48 def get_canonical_id(self, name: PlaceName) -> str:
49 """ Return the normalized form of the housenumber.
51 # shortcut for number-only numbers, which make up 90% of the data.
52 if RE_NON_DIGIT.search(name.name) is None:
55 norm = cast(str, self.trans.transliterate(self.norm.transliterate(name.name)))
56 # If there is a significant non-numeric part, use as is.
57 if RE_NAMED_PART.search(norm) is None:
58 # Otherwise add optional spaces between digits and letters.
59 (norm_opt, cnt1) = RE_DIGIT_ALPHA.subn(r'\1␣\2', norm)
60 (norm_opt, cnt2) = RE_ALPHA_DIGIT.subn(r'\1␣\2', norm_opt)
61 # Avoid creating too many variants per number.
67 def compute_variants(self, norm_name: str) -> List[str]:
68 """ Compute the spelling variants for the given normalized housenumber.
70 Generates variants for optional spaces (marked with '␣').
72 return list(self.mutator.generate([norm_name]))