"""
Generic processor for names that creates abbreviation variants.
"""
+from typing import Mapping, Dict, Any, Iterable, Iterator, Optional, List, cast
import itertools
import datrie
+from nominatim.errors import UsageError
+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.
"""
- config = {}
+ config: Dict[str, Any] = {}
config['replacements'], config['chars'] = get_variant_config(rules.get('variants'),
- normalization_rules)
+ normalizer)
config['variant_only'] = rules.get('mode', '') == 'variant-only'
+ # 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.")
+
+ config['mutations'].append((rule['pattern'], rule['replacements']))
+
return config
### Analysis section
-def create(transliterator, config):
+def create(normalizer: Any, transliterator: Any,
+ config: Mapping[str, Any]) -> 'GenericTokenAnalysis':
""" Create a new token analysis instance for this module.
"""
- return GenericTokenAnalysis(transliterator, config)
+ return GenericTokenAnalysis(normalizer, transliterator, config)
class GenericTokenAnalysis:
and provides the functions to apply the transformations.
"""
- def __init__(self, to_ascii, config):
+ 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']
else:
self.replacements = None
+ # set up mutation rules
+ self.mutations = [MutationVariantGenerator(*cfg) for cfg in config['mutations']]
+
+
+ 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()
+
- def get_variants_ascii(self, norm_name):
+ def compute_variants(self, norm_name: str) -> List[str]:
""" Compute the spelling variants for the given normalized name
and transliterate the result.
"""
- results = set()
- for variant in self._generate_word_variants(norm_name):
- if not self.variant_only or variant.strip() != norm_name:
- trans_name = self.to_ascii.transliterate(variant).strip()
- if trans_name:
- results.add(trans_name)
+ variants = self._generate_word_variants(norm_name)
+
+ for mutation in self.mutations:
+ variants = mutation.generate(variants)
+
+ return [name for name in self._transliterate_unique_list(norm_name, variants) if name]
+
+
+ def _transliterate_unique_list(self, norm_name: str,
+ iterable: Iterable[str]) -> Iterator[Optional[str]]:
+ seen = set()
+ if self.variant_only:
+ seen.add(norm_name)
- return list(results)
+ for variant in map(str.strip, iterable):
+ if variant not in seen:
+ seen.add(variant)
+ yield self.to_ascii.transliterate(variant).strip()
- def _generate_word_variants(self, norm_name):
+ def _generate_word_variants(self, norm_name: str) -> Iterable[str]:
baseform = '^ ' + norm_name + ' ^'
baselen = len(baseform)
partials = ['']