+# 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 collections import defaultdict, namedtuple
import itertools
+import re
from icu import Transliterator
import datrie
-### Analysis section
+from nominatim.config import flatten_config_list
+from nominatim.errors import UsageError
-def create(norm_rules, trans_rules, config):
- """ Create a new token analysis instance for this module.
+### Configuration section
+
+ICUVariant = namedtuple('ICUVariant', ['source', 'replacement'])
+
+def configure(rules, normalization_rules):
+ """ Extract and preprocess the configuration for this module.
"""
- return GenericTokenAnalysis(norm_rules, trans_rules, config['variants'])
+ config = {}
+ config['replacements'], config['chars'] = _get_variant_config(rules.get('variants'),
+ normalization_rules)
+ config['variant_only'] = rules.get('mode', '') == 'variant-only'
-class GenericTokenAnalysis:
- """ Collects the different transformation rules for normalisation of names
- and provides the functions to apply the transformations.
+ return config
+
+
+def _get_variant_config(rules, normalization_rules):
+ """ Convert the variant definition from the configuration into
+ replacement sets.
"""
+ immediate = defaultdict(list)
+ chars = set()
+
+ if rules:
+ vset = set()
+ rules = flatten_config_list(rules, 'variants')
- 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)
+ vmaker = _VariantMaker(normalization_rules)
+
+ for section in rules:
+ for rule in (section.get('words') or []):
+ vset.update(vmaker.compute(rule))
# Intermediate reorder by source. Also compute required character set.
- immediate = defaultdict(list)
- chars = set()
- for variant in replacements:
+ for variant in vset:
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
+ return list(immediate.items()), ''.join(chars)
+
+
+class _VariantMaker:
+ """ Generater for all necessary ICUVariants from a single variant rule.
- def get_normalized(self, name):
- """ Normalize the given name, i.e. remove all elements not relevant
- for search.
+ All text in rules is normalized to make sure the variants match later.
+ """
+
+ def __init__(self, norm_rules):
+ self.norm = Transliterator.createFromRules("rule_loader_normalization",
+ norm_rules)
+
+
+ def compute(self, rule):
+ """ Generator for all ICUVariant tuples from a single variant rule.
"""
- return self.normalizer.transliterate(name).strip()
+ 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 ICUVariant(froms, tos)
+
+ for src, repl in itertools.product(src_terms, repl_terms):
+ if src and repl:
+ for froms, tos in _create_variants(*src, repl, decompose):
+ yield ICUVariant(froms, tos)
+
+
+ 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)).strip()
+ if not norm_name:
+ return None
+
+ return norm_name, match.group(1), match.group(3)
+
+
+_FLAG_MATCH = {'^': '^ ',
+ '$': ' ^',
+ '': ' '}
+
+
+def _create_variants(src, preflag, postflag, repl, decompose):
+ if preflag == '~':
+ postfix = _FLAG_MATCH[postflag]
+ # suffix decomposition
+ src = src + postfix
+ repl = repl + postfix
+
+ yield src, repl
+ yield ' ' + src, ' ' + repl
+
+ 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 + ' '
+
+ if decompose:
+ yield src, repl + ' '
+ yield src + ' ', repl
+ else:
+ prefix = _FLAG_MATCH[preflag]
+ postfix = _FLAG_MATCH[postflag]
+
+ yield prefix + src + postfix, prefix + repl + postfix
+
+
+### Analysis section
+
+def create(transliterator, config):
+ """ Create a new token analysis instance for this module.
+ """
+ return GenericTokenAnalysis(transliterator, config)
+
+
+class GenericTokenAnalysis:
+ """ Collects the different transformation rules for normalisation of names
+ and provides the functions to apply the transformations.
+ """
+
+ def __init__(self, to_ascii, config):
+ self.to_ascii = to_ascii
+ self.variant_only = config['variant_only']
+
+ # 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
+
def get_variants_ascii(self, norm_name):
""" Compute the spelling variants for the given normalized name
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 < 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
# No variants detected? Fast return.
if startpos == 0:
+ if self.variant_only:
+ return []
+
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 self._compute_result_set(partials, baseform[startpos:],
+ norm_name if self.variant_only else '')
- def _compute_result_set(self, partials, prefix):
+ def _compute_result_set(self, partials, prefix, exclude):
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)
+ vname = (variant + prefix)[1:-1].strip()
+ if vname != exclude:
+ trans_name = self.to_ascii.transliterate(vname).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()
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