Processor for names that are imported into the database based on the
ICU library.
"""
-import json
+from collections import defaultdict
import itertools
from icu import Transliterator
import datrie
-from nominatim.db.properties import set_property, get_property
-
-DBCFG_IMPORT_NORM_RULES = "tokenizer_import_normalisation"
-DBCFG_IMPORT_TRANS_RULES = "tokenizer_import_transliteration"
-DBCFG_IMPORT_REPLACEMENTS = "tokenizer_import_replacements"
-DBCFG_SEARCH_STD_RULES = "tokenizer_search_standardization"
-
-
-class ICUNameProcessorRules:
- """ Data object that saves the rules needed for the name processor.
-
- The rules can either be initialised through an ICURuleLoader or
- be loaded from a database when a connection is given.
- """
- def __init__(self, loader=None, conn=None):
- if loader is not None:
- self.norm_rules = loader.get_normalization_rules()
- self.trans_rules = loader.get_transliteration_rules()
- self.replacements = loader.get_replacement_pairs()
- self.search_rules = loader.get_search_rules()
- elif conn is not None:
- self.norm_rules = get_property(conn, DBCFG_IMPORT_NORM_RULES)
- self.trans_rules = get_property(conn, DBCFG_IMPORT_TRANS_RULES)
- self.replacements = json.loads(get_property(conn, DBCFG_IMPORT_REPLACEMENTS))
- self.search_rules = get_property(conn, DBCFG_SEARCH_STD_RULES)
- else:
- assert False, "Parameter loader or conn required."
-
- # Compute the set of characters used in the replacement list.
- # We need this later when computing the tree.
- chars = set()
- for full, repl in self.replacements:
- chars.update(full)
- for word in repl:
- chars.update(word)
- self.replacement_charset = ''.join(chars)
-
-
- def save_rules(self, conn):
- """ Save the rules in the property table of the given database.
- the rules can be loaded again by handing in a connection into
- the constructor of the class.
- """
- set_property(conn, DBCFG_IMPORT_NORM_RULES, self.norm_rules)
- set_property(conn, DBCFG_IMPORT_TRANS_RULES, self.trans_rules)
- set_property(conn, DBCFG_IMPORT_REPLACEMENTS, json.dumps(self.replacements))
- set_property(conn, DBCFG_SEARCH_STD_RULES, self.search_rules)
-
class ICUNameProcessor:
+ """ Collects the different transformation rules for normalisation of names
+ and provides the functions to apply the transformations.
+ """
- def __init__(self, rules):
+ def __init__(self, norm_rules, trans_rules, replacements):
self.normalizer = Transliterator.createFromRules("icu_normalization",
- rules.norm_rules)
+ norm_rules)
self.to_ascii = Transliterator.createFromRules("icu_to_ascii",
- rules.trans_rules)
+ trans_rules +
+ ";[:Space:]+ > ' '")
self.search = Transliterator.createFromRules("icu_search",
- rules.search_rules)
+ norm_rules + trans_rules)
- self.replacements = datrie.Trie(rules.replacement_charset)
- for full, repl in rules.replacements:
- self.replacements[full] = repl
+ # 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)
+ 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.
"""
- baseform = ' ' + norm_name + ' '
- variants = ['']
+ baseform = '^ ' + norm_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]
- variants = [v + done + r for v, r in itertools.product(variants, repl)]
+ 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:
- return [self.to_ascii.transliterate(norm_name)]
+ trans_name = self.to_ascii.transliterate(norm_name).strip()
+ return [trans_name] if trans_name else []
+
+ return self._compute_result_set(partials, baseform[startpos:])
+
+
+ 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 [self.to_ascii.transliterate(v + baseform[startpos:pos]).strip() for v in variants]
+ 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)
+ return self.search.transliterate(' ' + name + ' ').strip()
projects / nominatim.git / blobdiff