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51b6d16dc6
The functional split betweenthe two functions is now that the first one creates the ID that is used in the word table and the second one creates the variants. There no longer is a requirement that the ID is the normalized version. We might later reintroduce the requirement that a normalized version be available but it doesn't necessarily need to be through the ID. The function that creates the ID now gets the full PlaceName. That way it might take into account attributes that were set by the sanitizers. Finally rename both functions to something more sane.
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
# SPDX-License-Identifier: GPL-2.0-only
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#
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# This file is part of Nominatim. (https://nominatim.org)
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#
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# Copyright (C) 2022 by the Nominatim developer community.
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# For a full list of authors see the git log.
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"""
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Specialized processor for housenumbers. Analyses common housenumber patterns
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and creates variants for them.
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"""
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from typing import Any, List, cast
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import re
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from nominatim.data.place_name import PlaceName
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from nominatim.tokenizer.token_analysis.generic_mutation import MutationVariantGenerator
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RE_NON_DIGIT = re.compile('[^0-9]')
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RE_DIGIT_ALPHA = re.compile(r'(\d)\s*([^\d\s␣])')
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RE_ALPHA_DIGIT = re.compile(r'([^\s\d␣])\s*(\d)')
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RE_NAMED_PART = re.compile(r'[a-z]{4}')
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### Configuration section
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def configure(*_: Any) -> None:
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""" All behaviour is currently hard-coded.
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"""
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return None
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### Analysis section
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def create(normalizer: Any, transliterator: Any, config: None) -> 'HousenumberTokenAnalysis': # pylint: disable=W0613
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""" Create a new token analysis instance for this module.
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"""
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return HousenumberTokenAnalysis(normalizer, transliterator)
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class HousenumberTokenAnalysis:
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""" Detects common housenumber patterns and normalizes them.
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"""
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def __init__(self, norm: Any, trans: Any) -> None:
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self.norm = norm
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self.trans = trans
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self.mutator = MutationVariantGenerator('␣', (' ', ''))
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def get_canonical_id(self, name: PlaceName) -> str:
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""" Return the normalized form of the housenumber.
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"""
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# shortcut for number-only numbers, which make up 90% of the data.
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if RE_NON_DIGIT.search(name.name) is None:
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return name.name
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norm = cast(str, self.trans.transliterate(self.norm.transliterate(name.name)))
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# If there is a significant non-numeric part, use as is.
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if RE_NAMED_PART.search(norm) is None:
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# Otherwise add optional spaces between digits and letters.
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(norm_opt, cnt1) = RE_DIGIT_ALPHA.subn(r'\1␣\2', norm)
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(norm_opt, cnt2) = RE_ALPHA_DIGIT.subn(r'\1␣\2', norm_opt)
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# Avoid creating too many variants per number.
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if cnt1 + cnt2 <= 4:
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return norm_opt
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return norm
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def compute_variants(self, norm_name: str) -> List[str]:
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""" Compute the spelling variants for the given normalized housenumber.
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Generates variants for optional spaces (marked with '␣').
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"""
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return list(self.mutator.generate([norm_name]))
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