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150 lines
5.5 KiB
Python
150 lines
5.5 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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Generic processor for names that creates abbreviation variants.
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"""
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from typing import Mapping, Dict, Any, Iterable, Iterator, Optional, List, cast
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import itertools
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import datrie
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from nominatim.errors import UsageError
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from nominatim.tokenizer.token_analysis.config_variants import get_variant_config
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from nominatim.tokenizer.token_analysis.generic_mutation import MutationVariantGenerator
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### Configuration section
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def configure(rules: Mapping[str, Any], normalization_rules: str) -> Dict[str, Any]:
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""" Extract and preprocess the configuration for this module.
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"""
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config: Dict[str, Any] = {}
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config['replacements'], config['chars'] = get_variant_config(rules.get('variants'),
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normalization_rules)
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config['variant_only'] = rules.get('mode', '') == 'variant-only'
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# parse mutation rules
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config['mutations'] = []
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for rule in rules.get('mutations', []):
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if 'pattern' not in rule:
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raise UsageError("Missing field 'pattern' in mutation configuration.")
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if not isinstance(rule['pattern'], str):
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raise UsageError("Field 'pattern' in mutation configuration "
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"must be a simple text field.")
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if 'replacements' not in rule:
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raise UsageError("Missing field 'replacements' in mutation configuration.")
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if not isinstance(rule['replacements'], list):
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raise UsageError("Field 'replacements' in mutation configuration "
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"must be a list of texts.")
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config['mutations'].append((rule['pattern'], rule['replacements']))
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return config
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### Analysis section
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def create(normalizer: Any, transliterator: Any,
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config: Mapping[str, Any]) -> 'GenericTokenAnalysis':
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""" Create a new token analysis instance for this module.
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"""
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return GenericTokenAnalysis(normalizer, transliterator, config)
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class GenericTokenAnalysis:
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""" Collects the different transformation rules for normalisation of names
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and provides the functions to apply the transformations.
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"""
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def __init__(self, norm: Any, to_ascii: Any, config: Mapping[str, Any]) -> None:
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self.norm = norm
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self.to_ascii = to_ascii
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self.variant_only = config['variant_only']
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# Set up datrie
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if config['replacements']:
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self.replacements = datrie.Trie(config['chars'])
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for src, repllist in config['replacements']:
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self.replacements[src] = repllist
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else:
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self.replacements = None
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# set up mutation rules
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self.mutations = [MutationVariantGenerator(*cfg) for cfg in config['mutations']]
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def normalize(self, name: str) -> str:
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""" Return the normalized form of the name. This is the standard form
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from which possible variants for the name can be derived.
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"""
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return cast(str, self.norm.transliterate(name)).strip()
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def get_variants_ascii(self, norm_name: str) -> List[str]:
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""" Compute the spelling variants for the given normalized name
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and transliterate the result.
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"""
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variants = self._generate_word_variants(norm_name)
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for mutation in self.mutations:
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variants = mutation.generate(variants)
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return [name for name in self._transliterate_unique_list(norm_name, variants) if name]
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def _transliterate_unique_list(self, norm_name: str,
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iterable: Iterable[str]) -> Iterator[Optional[str]]:
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seen = set()
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if self.variant_only:
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seen.add(norm_name)
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for variant in map(str.strip, iterable):
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if variant not in seen:
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seen.add(variant)
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yield self.to_ascii.transliterate(variant).strip()
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def _generate_word_variants(self, norm_name: str) -> Iterable[str]:
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baseform = '^ ' + norm_name + ' ^'
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baselen = len(baseform)
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partials = ['']
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startpos = 0
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if self.replacements is not None:
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pos = 0
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force_space = False
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while pos < baselen:
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full, repl = self.replacements.longest_prefix_item(baseform[pos:],
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(None, None))
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if full is not None:
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done = baseform[startpos:pos]
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partials = [v + done + r
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for v, r in itertools.product(partials, repl)
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if not force_space or r.startswith(' ')]
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if len(partials) > 128:
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# If too many variants are produced, they are unlikely
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# to be helpful. Only use the original term.
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startpos = 0
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break
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startpos = pos + len(full)
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if full[-1] == ' ':
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startpos -= 1
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force_space = True
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pos = startpos
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else:
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pos += 1
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force_space = False
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# No variants detected? Fast return.
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if startpos == 0:
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return (norm_name, )
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if startpos < baselen:
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return (part[1:] + baseform[startpos:-1] for part in partials)
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return (part[1:-1] for part in partials)
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