X-Git-Url: https://git.openstreetmap.org./nominatim.git/blobdiff_plain/ca7b46511d41d67e229f758e638367c241815c11..7a1d22ff15849a349e3cffdf604877a11060c749:/nominatim/tokenizer/token_analysis/postcodes.py diff --git a/nominatim/tokenizer/token_analysis/postcodes.py b/nominatim/tokenizer/token_analysis/postcodes.py index e105b132..18fc2a8d 100644 --- a/nominatim/tokenizer/token_analysis/postcodes.py +++ b/nominatim/tokenizer/token_analysis/postcodes.py @@ -25,8 +25,18 @@ def create(normalizer, transliterator, config): # pylint: disable=W0613 """ return PostcodeTokenAnalysis(normalizer, transliterator) + class PostcodeTokenAnalysis: - """ Detects common housenumber patterns and normalizes them. + """ 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, trans): self.norm = norm @@ -44,11 +54,12 @@ class PostcodeTokenAnalysis: def get_variants_ascii(self, norm_name): """ Compute the spelling variants for the given normalized postcode. - The official form creates one variant. If a 'lookup version' is - given, then it will create variants with optional spaces. + 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)])] + self.mutator.generate([self.norm.transliterate(norm_name)]) if term]