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
+from nominatim.tokenizer import icu_variants as variants
DBCFG_IMPORT_NORM_RULES = "tokenizer_import_normalisation"
DBCFG_IMPORT_TRANS_RULES = "tokenizer_import_transliteration"
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.replacements = \
+ variants.unpickle_variant_set(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.
"""
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_IMPORT_REPLACEMENTS,
+ variants.pickle_variant_set(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 aply the transformations.
+ """
def __init__(self, rules):
self.normalizer = Transliterator.createFromRules("icu_normalization",
rules.norm_rules)
self.to_ascii = Transliterator.createFromRules("icu_to_ascii",
- rules.trans_rules)
+ rules.trans_rules +
+ ";[:Space:]+ > ' '")
self.search = Transliterator.createFromRules("icu_search",
rules.search_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 rules.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
+
+ results = set()
if startpos == 0:
- return [self.to_ascii.transliterate(norm_name)]
+ trans_name = self.to_ascii.transliterate(norm_name).strip()
+ if trans_name:
+ results.add(trans_name)
+ else:
+ for variant in partials:
+ name = variant + baseform[startpos:]
+ trans_name = self.to_ascii.transliterate(name[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