# SPDX-License-Identifier: GPL-2.0-only # # This file is part of Nominatim. (https://nominatim.org) # # Copyright (C) 2022 by the Nominatim developer community. # For a full list of authors see the git log. """ Specialized processor for postcodes. Supports a 'lookup' variant of the token, which produces variants with optional spaces. """ from typing import Mapping, Any, List from nominatim.tokenizer.token_analysis.generic_mutation import MutationVariantGenerator ### Configuration section def configure(rules: Mapping[str, Any], normalization_rules: str) -> None: # pylint: disable=W0613 """ All behaviour is currently hard-coded. """ return None ### Analysis section def create(normalizer: Any, transliterator: Any, config: None) -> 'PostcodeTokenAnalysis': # pylint: disable=W0613 """ Create a new token analysis instance for this module. """ return PostcodeTokenAnalysis(normalizer, transliterator) class PostcodeTokenAnalysis: """ Special normalization and variant generation for postcodes. This analyser must not be used with anything but postcodes as it follows some special rules: `normalize` doesn't necessarily need to return a standard form as per normalization rules. It needs to return the canonical form of the postcode that is also used for output. `get_variants_ascii` then needs to ensure that the generated variants once more follow the standard normalization and transliteration, so that postcodes are correctly recognised by the search algorithm. """ def __init__(self, norm: Any, trans: Any) -> None: self.norm = norm self.trans = trans self.mutator = MutationVariantGenerator(' ', (' ', '')) def normalize(self, name: str) -> str: """ Return the standard form of the postcode. """ return name.strip().upper() def get_variants_ascii(self, norm_name: str) -> List[str]: """ Compute the spelling variants for the given normalized postcode. Takes the canonical form of the postcode, normalizes it using the standard rules and then creates variants of the result where all spaces are optional. """ # Postcodes follow their own transliteration rules. # Make sure at this point, that the terms are normalized in a way # that they are searchable with the standard transliteration rules. return [self.trans.transliterate(term) for term in self.mutator.generate([self.norm.transliterate(norm_name)]) if term]