+# 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.
"""
Generic processor for names that creates abbreviation variants.
"""
-from collections import defaultdict
+from typing import Mapping, Dict, Any, Iterable, Iterator, Optional, List, cast
import itertools
-import re
-from icu import Transliterator
import datrie
-from nominatim.config import flatten_config_list
from nominatim.errors import UsageError
-import nominatim.tokenizer.icu_variants as variants
+from nominatim.data.place_name import PlaceName
+from nominatim.tokenizer.token_analysis.config_variants import get_variant_config
+from nominatim.tokenizer.token_analysis.generic_mutation import MutationVariantGenerator
### Configuration section
-def configure(rules, normalization_rules):
+def configure(rules: Mapping[str, Any], normalizer: Any, _: Any) -> Dict[str, Any]:
""" Extract and preprocess the configuration for this module.
"""
- return {'variants': _parse_variant_list(rules.get('variants'),
- normalization_rules)}
+ config: Dict[str, Any] = {}
+ config['replacements'], config['chars'] = get_variant_config(rules.get('variants'),
+ normalizer)
+ config['variant_only'] = rules.get('mode', '') == 'variant-only'
-def _parse_variant_list(rules, normalization_rules):
- vset = set()
+ # parse mutation rules
+ config['mutations'] = []
+ for rule in rules.get('mutations', []):
+ if 'pattern' not in rule:
+ raise UsageError("Missing field 'pattern' in mutation configuration.")
+ if not isinstance(rule['pattern'], str):
+ raise UsageError("Field 'pattern' in mutation configuration "
+ "must be a simple text field.")
+ if 'replacements' not in rule:
+ raise UsageError("Missing field 'replacements' in mutation configuration.")
+ if not isinstance(rule['replacements'], list):
+ raise UsageError("Field 'replacements' in mutation configuration "
+ "must be a list of texts.")
- if rules:
- rules = flatten_config_list(rules, 'variants')
+ config['mutations'].append((rule['pattern'], rule['replacements']))
- vmaker = _VariantMaker(normalization_rules)
+ return config
- properties = []
- for section in rules:
- # Create the property field and deduplicate against existing
- # instances.
- props = variants.ICUVariantProperties.from_rules(section)
- for existing in properties:
- if existing == props:
- props = existing
- break
- else:
- properties.append(props)
- for rule in (section.get('words') or []):
- vset.update(vmaker.compute(rule, props))
-
- return vset
-
-
-class _VariantMaker:
- """ Generater for all necessary ICUVariants from a single variant rule.
+### Analysis section
- All text in rules is normalized to make sure the variants match later.
+def create(normalizer: Any, transliterator: Any,
+ config: Mapping[str, Any]) -> 'GenericTokenAnalysis':
+ """ Create a new token analysis instance for this module.
"""
+ return GenericTokenAnalysis(normalizer, transliterator, config)
- def __init__(self, norm_rules):
- self.norm = Transliterator.createFromRules("rule_loader_normalization",
- norm_rules)
-
-
- def compute(self, rule, props):
- """ Generator for all ICUVariant tuples from a single variant rule.
- """
- parts = re.split(r'(\|)?([=-])>', rule)
- if len(parts) != 4:
- raise UsageError("Syntax error in variant rule: " + rule)
-
- decompose = parts[1] is None
- src_terms = [self._parse_variant_word(t) for t in parts[0].split(',')]
- repl_terms = (self.norm.transliterate(t.strip()) for t in parts[3].split(','))
-
- # If the source should be kept, add a 1:1 replacement
- if parts[2] == '-':
- for src in src_terms:
- if src:
- for froms, tos in _create_variants(*src, src[0], decompose):
- yield variants.ICUVariant(froms, tos, props)
- for src, repl in itertools.product(src_terms, repl_terms):
- if src and repl:
- for froms, tos in _create_variants(*src, repl, decompose):
- yield variants.ICUVariant(froms, tos, props)
-
-
- def _parse_variant_word(self, name):
- name = name.strip()
- match = re.fullmatch(r'([~^]?)([^~$^]*)([~$]?)', name)
- if match is None or (match.group(1) == '~' and match.group(3) == '~'):
- raise UsageError("Invalid variant word descriptor '{}'".format(name))
- norm_name = self.norm.transliterate(match.group(2))
- if not norm_name:
- return None
-
- return norm_name, match.group(1), match.group(3)
-
-
-_FLAG_MATCH = {'^': '^ ',
- '$': ' ^',
- '': ' '}
+class GenericTokenAnalysis:
+ """ Collects the different transformation rules for normalisation of names
+ and provides the functions to apply the transformations.
+ """
+ def __init__(self, norm: Any, to_ascii: Any, config: Mapping[str, Any]) -> None:
+ self.norm = norm
+ self.to_ascii = to_ascii
+ self.variant_only = config['variant_only']
-def _create_variants(src, preflag, postflag, repl, decompose):
- if preflag == '~':
- postfix = _FLAG_MATCH[postflag]
- # suffix decomposition
- src = src + postfix
- repl = repl + postfix
+ # Set up datrie
+ if config['replacements']:
+ self.replacements = datrie.Trie(config['chars'])
+ for src, repllist in config['replacements']:
+ self.replacements[src] = repllist
+ else:
+ self.replacements = None
- yield src, repl
- yield ' ' + src, ' ' + repl
+ # set up mutation rules
+ self.mutations = [MutationVariantGenerator(*cfg) for cfg in config['mutations']]
- if decompose:
- yield src, ' ' + repl
- yield ' ' + src, repl
- elif postflag == '~':
- # prefix decomposition
- prefix = _FLAG_MATCH[preflag]
- src = prefix + src
- repl = prefix + repl
- yield src, repl
- yield src + ' ', repl + ' '
+ def get_canonical_id(self, name: PlaceName) -> str:
+ """ Return the normalized form of the name. This is the standard form
+ from which possible variants for the name can be derived.
+ """
+ return cast(str, self.norm.transliterate(name.name)).strip()
- if decompose:
- yield src, repl + ' '
- yield src + ' ', repl
- else:
- prefix = _FLAG_MATCH[preflag]
- postfix = _FLAG_MATCH[postflag]
- yield prefix + src + postfix, prefix + repl + postfix
+ def compute_variants(self, norm_name: str) -> List[str]:
+ """ Compute the spelling variants for the given normalized name
+ and transliterate the result.
+ """
+ variants = self._generate_word_variants(norm_name)
+ for mutation in self.mutations:
+ variants = mutation.generate(variants)
-### Analysis section
+ return [name for name in self._transliterate_unique_list(norm_name, variants) if name]
-def create(norm_rules, trans_rules, config):
- """ Create a new token analysis instance for this module.
- """
- return GenericTokenAnalysis(norm_rules, trans_rules, config['variants'])
+ def _transliterate_unique_list(self, norm_name: str,
+ iterable: Iterable[str]) -> Iterator[Optional[str]]:
+ seen = set()
+ if self.variant_only:
+ seen.add(norm_name)
-class GenericTokenAnalysis:
- """ Collects the different transformation rules for normalisation of names
- and provides the functions to apply the transformations.
- """
+ for variant in map(str.strip, iterable):
+ if variant not in seen:
+ seen.add(variant)
+ yield self.to_ascii.transliterate(variant).strip()
- def __init__(self, norm_rules, trans_rules, replacements):
- self.normalizer = Transliterator.createFromRules("icu_normalization",
- norm_rules)
- self.to_ascii = Transliterator.createFromRules("icu_to_ascii",
- trans_rules +
- ";[:Space:]+ > ' '")
- self.search = Transliterator.createFromRules("icu_search",
- norm_rules + trans_rules)
-
- # Intermediate reorder by source. Also compute required character set.
- immediate = defaultdict(list)
- chars = set()
- for variant in replacements:
- if variant.source[-1] == ' ' and variant.replacement[-1] == ' ':
- replstr = variant.replacement[:-1]
- else:
- replstr = variant.replacement
- immediate[variant.source].append(replstr)
- chars.update(variant.source)
- # Then copy to datrie
- self.replacements = datrie.Trie(''.join(chars))
- for src, repllist in immediate.items():
- self.replacements[src] = repllist
-
-
- def get_normalized(self, name):
- """ Normalize the given name, i.e. remove all elements not relevant
- for search.
- """
- return self.normalizer.transliterate(name).strip()
- def get_variants_ascii(self, norm_name):
- """ Compute the spelling variants for the given normalized name
- and transliterate the result.
- """
+ def _generate_word_variants(self, norm_name: str) -> Iterable[str]:
baseform = '^ ' + norm_name + ' ^'
+ baselen = len(baseform)
partials = ['']
startpos = 0
- pos = 0
- force_space = False
- while pos < len(baseform):
- full, repl = self.replacements.longest_prefix_item(baseform[pos:],
- (None, None))
- if full is not None:
- done = baseform[startpos:pos]
- partials = [v + done + r
- for v, r in itertools.product(partials, repl)
- if not force_space or r.startswith(' ')]
- if len(partials) > 128:
- # If too many variants are produced, they are unlikely
- # to be helpful. Only use the original term.
- startpos = 0
- break
- startpos = pos + len(full)
- if full[-1] == ' ':
- startpos -= 1
- force_space = True
- pos = startpos
- else:
- pos += 1
- force_space = False
+ if self.replacements is not None:
+ pos = 0
+ force_space = False
+ while pos < baselen:
+ full, repl = self.replacements.longest_prefix_item(baseform[pos:],
+ (None, None))
+ if full is not None:
+ done = baseform[startpos:pos]
+ partials = [v + done + r
+ for v, r in itertools.product(partials, repl)
+ if not force_space or r.startswith(' ')]
+ if len(partials) > 128:
+ # If too many variants are produced, they are unlikely
+ # to be helpful. Only use the original term.
+ startpos = 0
+ break
+ startpos = pos + len(full)
+ if full[-1] == ' ':
+ startpos -= 1
+ force_space = True
+ pos = startpos
+ else:
+ pos += 1
+ force_space = False
# No variants detected? Fast return.
if startpos == 0:
- trans_name = self.to_ascii.transliterate(norm_name).strip()
- return [trans_name] if trans_name else []
-
- return self._compute_result_set(partials, baseform[startpos:])
+ return (norm_name, )
+ if startpos < baselen:
+ return (part[1:] + baseform[startpos:-1] for part in partials)
- def _compute_result_set(self, partials, prefix):
- results = set()
-
- for variant in partials:
- vname = variant + prefix
- trans_name = self.to_ascii.transliterate(vname[1:-1]).strip()
- if trans_name:
- results.add(trans_name)
-
- return list(results)
-
-
- def get_search_normalized(self, name):
- """ Return the normalized version of the name (including transliteration)
- to be applied at search time.
- """
- return self.search.transliterate(' ' + name + ' ').strip()
+ return (part[1:-1] for part in partials)
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