libICU instead of the PostgreSQL module.
"""
from collections import Counter
-import functools
-import io
import itertools
-import json
import logging
import re
from textwrap import dedent
from pathlib import Path
-from icu import Transliterator
-import psycopg2.extras
-
from nominatim.db.connection import connect
from nominatim.db.properties import set_property, get_property
+from nominatim.db.utils import CopyBuffer
from nominatim.db.sql_preprocessor import SQLPreprocessor
+from nominatim.tokenizer.icu_rule_loader import ICURuleLoader
+from nominatim.tokenizer.icu_name_processor import ICUNameProcessor, ICUNameProcessorRules
-DBCFG_NORMALIZATION = "tokenizer_normalization"
DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
-DBCFG_TRANSLITERATION = "tokenizer_transliteration"
-DBCFG_ABBREVIATIONS = "tokenizer_abbreviations"
+DBCFG_TERM_NORMALIZATION = "tokenizer_term_normalization"
LOG = logging.getLogger()
class LegacyICUTokenizer:
""" This tokenizer uses libICU to covert names and queries to ASCII.
Otherwise it uses the same algorithms and data structures as the
- normalization routines in Nominatm 3.
+ normalization routines in Nominatim 3.
"""
def __init__(self, dsn, data_dir):
self.dsn = dsn
self.data_dir = data_dir
- self.normalization = None
- self.transliteration = None
- self.abbreviations = None
+ self.naming_rules = None
+ self.term_normalization = None
+ self.max_word_frequency = None
def init_new_db(self, config, init_db=True):
if config.TOKENIZER_CONFIG:
cfgfile = Path(config.TOKENIZER_CONFIG)
else:
- cfgfile = config.config_dir / 'legacy_icu_tokenizer.json'
+ cfgfile = config.config_dir / 'legacy_icu_tokenizer.yaml'
- rules = json.loads(cfgfile.read_text())
- self.transliteration = ';'.join(rules['normalization']) + ';'
- self.abbreviations = rules["abbreviations"]
- self.normalization = config.TERM_NORMALIZATION
+ loader = ICURuleLoader(cfgfile)
+ self.naming_rules = ICUNameProcessorRules(loader=loader)
+ self.term_normalization = config.TERM_NORMALIZATION
+ self.max_word_frequency = config.MAX_WORD_FREQUENCY
- self._install_php(config)
+ self._install_php(config.lib_dir.php)
self._save_config(config)
if init_db:
""" Initialise the tokenizer from the project directory.
"""
with connect(self.dsn) as conn:
- self.normalization = get_property(conn, DBCFG_NORMALIZATION)
- self.transliteration = get_property(conn, DBCFG_TRANSLITERATION)
- self.abbreviations = json.loads(get_property(conn, DBCFG_ABBREVIATIONS))
+ self.naming_rules = ICUNameProcessorRules(conn=conn)
+ self.term_normalization = get_property(conn, DBCFG_TERM_NORMALIZATION)
+ self.max_word_frequency = get_property(conn, DBCFG_MAXWORDFREQ)
def finalize_import(self, config):
"""
self.init_from_project()
- if self.normalization is None\
- or self.transliteration is None\
- or self.abbreviations is None:
+ if self.naming_rules is None:
return "Configuration for tokenizer 'legacy_icu' are missing."
return None
Analyzers are not thread-safe. You need to instantiate one per thread.
"""
- norm = Transliterator.createFromRules("normalizer", self.normalization)
- trans = Transliterator.createFromRules("normalizer", self.transliteration)
- return LegacyICUNameAnalyzer(self.dsn, norm, trans, self.abbreviations)
-
+ return LegacyICUNameAnalyzer(self.dsn, ICUNameProcessor(self.naming_rules))
- def _install_php(self, config):
+ # pylint: disable=missing-format-attribute
+ def _install_php(self, phpdir):
""" Install the php script for the tokenizer.
"""
- abbr_inverse = list(zip(*self.abbreviations))
php_file = self.data_dir / "tokenizer.php"
php_file.write_text(dedent("""\
<?php
- @define('CONST_Max_Word_Frequency', {1.MAX_WORD_FREQUENCY});
- @define('CONST_Term_Normalization_Rules', "{0.normalization}");
- @define('CONST_Transliteration', "{0.transliteration}");
- @define('CONST_Abbreviations', array(array('{2}'), array('{3}')));
- require_once('{1.lib_dir.php}/tokenizer/legacy_icu_tokenizer.php');
- """.format(self, config,
- "','".join(abbr_inverse[0]),
- "','".join(abbr_inverse[1]))))
+ @define('CONST_Max_Word_Frequency', {0.max_word_frequency});
+ @define('CONST_Term_Normalization_Rules', "{0.term_normalization}");
+ @define('CONST_Transliteration', "{0.naming_rules.search_rules}");
+ require_once('{1}/tokenizer/legacy_icu_tokenizer.php');
+ """.format(self, phpdir)))
def _save_config(self, config):
database as database properties.
"""
with connect(self.dsn) as conn:
- set_property(conn, DBCFG_NORMALIZATION, self.normalization)
+ self.naming_rules.save_rules(conn)
+
set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY)
- set_property(conn, DBCFG_TRANSLITERATION, self.transliteration)
- set_property(conn, DBCFG_ABBREVIATIONS, json.dumps(self.abbreviations))
+ set_property(conn, DBCFG_TERM_NORMALIZATION, self.term_normalization)
def _init_db_tables(self, config):
# get partial words and their frequencies
words = Counter()
- with self.name_analyzer() as analyzer:
- with conn.cursor(name="words") as cur:
- cur.execute("SELECT svals(name) as v, count(*) FROM place GROUP BY v")
-
- for name, cnt in cur:
- term = analyzer.make_standard_word(name)
- if term:
- for word in term.split():
- words[word] += cnt
+ name_proc = ICUNameProcessor(self.naming_rules)
+ with conn.cursor(name="words") as cur:
+ cur.execute(""" SELECT v, count(*) FROM
+ (SELECT svals(name) as v FROM place)x
+ WHERE length(v) < 75 GROUP BY v""")
+
+ for name, cnt in cur:
+ terms = set()
+ for word in name_proc.get_variants_ascii(name_proc.get_normalized(name)):
+ if ' ' in word:
+ terms.update(word.split())
+ for term in terms:
+ words[term] += cnt
# copy them back into the word table
- copystr = io.StringIO(''.join(('{}\t{}\n'.format(*args) for args in words.items())))
+ with CopyBuffer() as copystr:
+ for args in words.items():
+ copystr.add(*args)
- with conn.cursor() as cur:
- cur.copy_from(copystr, 'word', columns=['word_token', 'search_name_count'])
- cur.execute("""UPDATE word SET word_id = nextval('seq_word')
- WHERE word_id is null""")
+ with conn.cursor() as cur:
+ copystr.copy_out(cur, 'word',
+ columns=['word_token', 'search_name_count'])
+ cur.execute("""UPDATE word SET word_id = nextval('seq_word')
+ WHERE word_id is null""")
conn.commit()
normalization.
"""
- def __init__(self, dsn, normalizer, transliterator, abbreviations):
+ def __init__(self, dsn, name_proc):
self.conn = connect(dsn).connection
self.conn.autocommit = True
- self.normalizer = normalizer
- self.transliterator = transliterator
- self.abbreviations = abbreviations
- #psycopg2.extras.register_hstore(self.conn)
+ self.name_processor = name_proc
self._cache = _TokenCache()
self.conn = None
- def normalize(self, phrase):
- """ Normalize the given phrase, i.e. remove all properties that
- are irrelevant for search.
- """
- return self.normalizer.transliterate(phrase)
+ def get_word_token_info(self, words):
+ """ Return token information for the given list of words.
+ If a word starts with # it is assumed to be a full name
+ otherwise is a partial name.
+
+ The function returns a list of tuples with
+ (original word, word token, word id).
- @functools.lru_cache(maxsize=1024)
- def make_standard_word(self, name):
- """ Create the normalised version of the name.
+ The function is used for testing and debugging only
+ and not necessarily efficient.
"""
- norm = ' ' + self.transliterator.transliterate(name) + ' '
- for full, abbr in self.abbreviations:
- if full in norm:
- norm = norm.replace(full, abbr)
+ tokens = {}
+ for word in words:
+ if word.startswith('#'):
+ tokens[word] = ' ' + self.name_processor.get_search_normalized(word[1:])
+ else:
+ tokens[word] = self.name_processor.get_search_normalized(word)
- return norm.strip()
+ with self.conn.cursor() as cur:
+ cur.execute("""SELECT word_token, word_id
+ FROM word, (SELECT unnest(%s::TEXT[]) as term) t
+ WHERE word_token = t.term
+ and class is null and country_code is null""",
+ (list(tokens.values()), ))
+ ids = {r[0]: r[1] for r in cur}
+
+ return [(k, v, ids.get(v, None)) for k, v in tokens.items()]
+
+
+ @staticmethod
+ def normalize_postcode(postcode):
+ """ Convert the postcode to a standardized form.
+
+ This function must yield exactly the same result as the SQL function
+ 'token_normalized_postcode()'.
+ """
+ return postcode.strip().upper()
def _make_standard_hnr(self, hnr):
This function takes minor shortcuts on transliteration.
"""
- if hnr.isdigit():
- return hnr
-
- return self.transliterator.transliterate(hnr)
+ return self.name_processor.get_search_normalized(hnr)
- def add_postcodes_from_db(self):
- """ Add postcodes from the location_postcode table to the word table.
+ def update_postcodes_from_db(self):
+ """ Update postcode tokens in the word table from the location_postcode
+ table.
"""
- copystr = io.StringIO()
+ to_delete = []
with self.conn.cursor() as cur:
- cur.execute("SELECT distinct(postcode) FROM location_postcode")
- for (postcode, ) in cur:
- copystr.write(postcode)
- copystr.write('\t ')
- copystr.write(self.transliterator.transliterate(postcode))
- copystr.write('\tplace\tpostcode\t0\n')
-
- cur.copy_from(copystr, 'word',
- columns=['word', 'word_token', 'class', 'type',
- 'search_name_count'])
- # Don't really need an ID for postcodes....
- # cur.execute("""UPDATE word SET word_id = nextval('seq_word')
- # WHERE word_id is null and type = 'postcode'""")
-
-
- def update_special_phrases(self, phrases):
+ # This finds us the rows in location_postcode and word that are
+ # missing in the other table.
+ cur.execute("""SELECT * FROM
+ (SELECT pc, word FROM
+ (SELECT distinct(postcode) as pc FROM location_postcode) p
+ FULL JOIN
+ (SELECT word FROM word
+ WHERE class ='place' and type = 'postcode') w
+ ON pc = word) x
+ WHERE pc is null or word is null""")
+
+ with CopyBuffer() as copystr:
+ for postcode, word in cur:
+ if postcode is None:
+ to_delete.append(word)
+ else:
+ copystr.add(
+ postcode,
+ ' ' + self.name_processor.get_search_normalized(postcode),
+ 'place', 'postcode', 0)
+
+ if to_delete:
+ cur.execute("""DELETE FROM WORD
+ WHERE class ='place' and type = 'postcode'
+ and word = any(%s)
+ """, (to_delete, ))
+
+ copystr.copy_out(cur, 'word',
+ columns=['word', 'word_token', 'class', 'type',
+ 'search_name_count'])
+
+
+ def update_special_phrases(self, phrases, should_replace):
""" Replace the search index for special phrases with the new phrases.
"""
- norm_phrases = set(((self.normalize(p[0]), p[1], p[2], p[3])
+ norm_phrases = set(((self.name_processor.get_normalized(p[0]), p[1], p[2], p[3])
for p in phrases))
with self.conn.cursor() as cur:
for label, cls, typ, oper in cur:
existing_phrases.add((label, cls, typ, oper or '-'))
- to_add = norm_phrases - existing_phrases
- to_delete = existing_phrases - norm_phrases
-
- if to_add:
- copystr = io.StringIO()
- for word, cls, typ, oper in to_add:
- term = self.make_standard_word(word)
- if term:
- copystr.write(word)
- copystr.write('\t ')
- copystr.write(term)
- copystr.write('\t')
- copystr.write(cls)
- copystr.write('\t')
- copystr.write(typ)
- copystr.write('\t')
- copystr.write(oper if oper in ('in', 'near') else '\\N')
- copystr.write('\t0\n')
-
- cur.copy_from(copystr, 'word',
- columns=['word', 'word_token', 'class', 'type',
- 'operator', 'search_name_count'])
-
- if to_delete:
- psycopg2.extras.execute_values(
- cur,
- """ DELETE FROM word USING (VALUES %s) as v(name, in_class, in_type, op)
- WHERE word = name and class = in_class and type = in_type
- and ((op = '-' and operator is null) or op = operator)""",
- to_delete)
+ added = self._add_special_phrases(cur, norm_phrases, existing_phrases)
+ if should_replace:
+ deleted = self._remove_special_phrases(cur, norm_phrases,
+ existing_phrases)
+ else:
+ deleted = 0
LOG.info("Total phrases: %s. Added: %s. Deleted: %s",
- len(norm_phrases), len(to_add), len(to_delete))
+ len(norm_phrases), added, deleted)
- def add_country_names(self, country_code, names):
- """ Add names for the given country to the search index.
+ def _add_special_phrases(self, cursor, new_phrases, existing_phrases):
+ """ Add all phrases to the database that are not yet there.
+ """
+ to_add = new_phrases - existing_phrases
+
+ added = 0
+ with CopyBuffer() as copystr:
+ for word, cls, typ, oper in to_add:
+ term = self.name_processor.get_search_normalized(word)
+ if term:
+ copystr.add(word, ' ' + term, cls, typ,
+ oper if oper in ('in', 'near') else None, 0)
+ added += 1
+
+ copystr.copy_out(cursor, 'word',
+ columns=['word', 'word_token', 'class', 'type',
+ 'operator', 'search_name_count'])
+
+ return added
+
+
+ @staticmethod
+ def _remove_special_phrases(cursor, new_phrases, existing_phrases):
+ """ Remove all phrases from the databse that are no longer in the
+ new phrase list.
"""
- full_names = set((self.make_standard_word(n) for n in names))
- full_names.discard('')
- self._add_normalised_country_names(country_code, full_names)
+ to_delete = existing_phrases - new_phrases
+
+ if to_delete:
+ cursor.execute_values(
+ """ DELETE FROM word USING (VALUES %s) as v(name, in_class, in_type, op)
+ WHERE word = name and class = in_class and type = in_type
+ and ((op = '-' and operator is null) or op = operator)""",
+ to_delete)
+
+ return len(to_delete)
- def _add_normalised_country_names(self, country_code, names):
+ def add_country_names(self, country_code, names):
""" Add names for the given country to the search index.
"""
+ word_tokens = set()
+ for name in self._compute_full_names(names):
+ if name:
+ word_tokens.add(' ' + self.name_processor.get_search_normalized(name))
+
with self.conn.cursor() as cur:
# Get existing names
cur.execute("SELECT word_token FROM word WHERE country_code = %s",
(country_code, ))
- new_names = names.difference((t[0] for t in cur))
+ word_tokens.difference_update((t[0] for t in cur))
- if new_names:
+ if word_tokens:
cur.execute("""INSERT INTO word (word_id, word_token, country_code,
search_name_count)
- (SELECT nextval('seq_word'), token, '{}', 0
+ (SELECT nextval('seq_word'), token, %s, 0
FROM unnest(%s) as token)
- """.format(country_code), (list(new_names),))
+ """, (country_code, list(word_tokens)))
def process_place(self, place):
names = place.get('name')
if names:
- full_names = set((self.make_standard_word(name) for name in names.values()))
- full_names.discard('')
+ fulls, partials = self._compute_name_tokens(names)
- token_info.add_names(self.conn, full_names)
+ token_info.add_names(fulls, partials)
country_feature = place.get('country_feature')
if country_feature and re.fullmatch(r'[A-Za-z][A-Za-z]', country_feature):
- self._add_normalised_country_names(country_feature.lower(),
- full_names)
+ self.add_country_names(country_feature.lower(), names)
address = place.get('address')
-
if address:
- hnrs = []
- addr_terms = []
- for key, value in address.items():
- if key == 'postcode':
- self._add_postcode(value)
- elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'):
- hnrs.append(value)
- elif key == 'street':
- token_info.add_street(self.conn, self.make_standard_word(value))
- elif key == 'place':
- token_info.add_place(self.conn, self.make_standard_word(value))
- elif not key.startswith('_') and \
- key not in ('country', 'full'):
- addr_terms.append((key, self.make_standard_word(value)))
-
- if hnrs:
- hnrs = self._split_housenumbers(hnrs)
- token_info.add_housenumbers(self.conn, [self._make_standard_hnr(n) for n in hnrs])
-
- if addr_terms:
- token_info.add_address_terms(self.conn, addr_terms)
+ self._process_place_address(token_info, address)
return token_info.data
+ def _process_place_address(self, token_info, address):
+ hnrs = []
+ addr_terms = []
+ for key, value in address.items():
+ if key == 'postcode':
+ self._add_postcode(value)
+ elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'):
+ hnrs.append(value)
+ elif key == 'street':
+ token_info.add_street(*self._compute_name_tokens({'name': value}))
+ elif key == 'place':
+ token_info.add_place(*self._compute_name_tokens({'name': value}))
+ elif not key.startswith('_') and \
+ key not in ('country', 'full'):
+ addr_terms.append((key, *self._compute_name_tokens({'name': value})))
+
+ if hnrs:
+ hnrs = self._split_housenumbers(hnrs)
+ token_info.add_housenumbers(self.conn, [self._make_standard_hnr(n) for n in hnrs])
+
+ if addr_terms:
+ token_info.add_address_terms(addr_terms)
+
+
+ def _compute_name_tokens(self, names):
+ """ Computes the full name and partial name tokens for the given
+ dictionary of names.
+ """
+ full_names = self._compute_full_names(names)
+ full_tokens = set()
+ partial_tokens = set()
+
+ for name in full_names:
+ norm_name = self.name_processor.get_normalized(name)
+ full, part = self._cache.names.get(norm_name, (None, None))
+ if full is None:
+ variants = self.name_processor.get_variants_ascii(norm_name)
+ if not variants:
+ continue
+
+ with self.conn.cursor() as cur:
+ cur.execute("SELECT (getorcreate_full_word(%s, %s)).*",
+ (norm_name, variants))
+ full, part = cur.fetchone()
+
+ self._cache.names[norm_name] = (full, part)
+
+ full_tokens.add(full)
+ partial_tokens.update(part)
+
+ return full_tokens, partial_tokens
+
+
+ @staticmethod
+ def _compute_full_names(names):
+ """ Return the set of all full name word ids to be used with the
+ given dictionary of names.
+ """
+ full_names = set()
+ for name in (n.strip() for ns in names.values() for n in re.split('[;,]', ns)):
+ if name:
+ full_names.add(name)
+
+ brace_idx = name.find('(')
+ if brace_idx >= 0:
+ full_names.add(name[:brace_idx].strip())
+
+ return full_names
+
+
def _add_postcode(self, postcode):
""" Make sure the normalized postcode is present in the word table.
"""
- if re.search(r'[:,;]', postcode) is None and not postcode in self._cache.postcodes:
- term = self.make_standard_word(postcode)
- if not term:
- return
-
- with self.conn.cursor() as cur:
- # no word_id needed for postcodes
- cur.execute("""INSERT INTO word (word, word_token, class, type,
- search_name_count)
- (SELECT pc, %s, 'place', 'postcode', 0
- FROM (VALUES (%s)) as v(pc)
- WHERE NOT EXISTS
- (SELECT * FROM word
- WHERE word = pc and class='place' and type='postcode'))
- """, (' ' + term, postcode))
- self._cache.postcodes.add(postcode)
+ if re.search(r'[:,;]', postcode) is None:
+ postcode = self.normalize_postcode(postcode)
+
+ if postcode not in self._cache.postcodes:
+ term = self.name_processor.get_search_normalized(postcode)
+ if not term:
+ return
+
+ with self.conn.cursor() as cur:
+ # no word_id needed for postcodes
+ cur.execute("""INSERT INTO word (word, word_token, class, type,
+ search_name_count)
+ (SELECT pc, %s, 'place', 'postcode', 0
+ FROM (VALUES (%s)) as v(pc)
+ WHERE NOT EXISTS
+ (SELECT * FROM word
+ WHERE word = pc and class='place' and type='postcode'))
+ """, (' ' + term, postcode))
+ self._cache.postcodes.add(postcode)
+
@staticmethod
def _split_housenumbers(hnrs):
""" Collect token information to be sent back to the database.
"""
def __init__(self, cache):
- self.cache = cache
+ self._cache = cache
self.data = {}
@staticmethod
return '{%s}' % ','.join((str(s) for s in tokens))
- def add_names(self, conn, names):
+ def add_names(self, fulls, partials):
""" Adds token information for the normalised names.
"""
- # Start with all partial names
- terms = set((part for ns in names for part in ns.split()))
- # Add partials for the full terms (TO BE REMOVED)
- terms.update((n for n in names))
- # Add the full names
- terms.update((' ' + n for n in names))
-
- self.data['names'] = self._mk_array(self.cache.get_term_tokens(conn, terms))
+ self.data['names'] = self._mk_array(itertools.chain(fulls, partials))
def add_housenumbers(self, conn, hnrs):
""" Extract housenumber information from a list of normalised
housenumbers.
"""
- self.data['hnr_tokens'] = self._mk_array(self.cache.get_hnr_tokens(conn, hnrs))
+ self.data['hnr_tokens'] = self._mk_array(self._cache.get_hnr_tokens(conn, hnrs))
self.data['hnr'] = ';'.join(hnrs)
- def add_street(self, conn, street):
+ def add_street(self, fulls, _):
""" Add addr:street match terms.
"""
- if not street:
- return
-
- term = ' ' + street
-
- tid = self.cache.names.get(term)
-
- if tid is None:
- with conn.cursor() as cur:
- cur.execute("""SELECT word_id FROM word
- WHERE word_token = %s
- and class is null and type is null""",
- (term, ))
- if cur.rowcount > 0:
- tid = cur.fetchone()[0]
- self.cache.names[term] = tid
+ if fulls:
+ self.data['street'] = self._mk_array(fulls)
- if tid is not None:
- self.data['street'] = '{%d}' % tid
-
- def add_place(self, conn, place):
+ def add_place(self, fulls, partials):
""" Add addr:place search and match terms.
"""
- if not place:
- return
-
- partial_ids = self.cache.get_term_tokens(conn, place.split())
- tid = self.cache.get_term_tokens(conn, [' ' + place])
+ if fulls:
+ self.data['place_search'] = self._mk_array(itertools.chain(fulls, partials))
+ self.data['place_match'] = self._mk_array(fulls)
- self.data['place_search'] = self._mk_array(itertools.chain(partial_ids, tid))
- self.data['place_match'] = '{%s}' % tid[0]
-
- def add_address_terms(self, conn, terms):
+ def add_address_terms(self, terms):
""" Add additional address terms.
"""
tokens = {}
- for key, value in terms:
- if not value:
- continue
- partial_ids = self.cache.get_term_tokens(conn, value.split())
- term = ' ' + value
- tid = self.cache.names.get(term)
-
- if tid is None:
- with conn.cursor() as cur:
- cur.execute("""SELECT word_id FROM word
- WHERE word_token = %s
- and class is null and type is null""",
- (term, ))
- if cur.rowcount > 0:
- tid = cur.fetchone()[0]
- self.cache.names[term] = tid
-
- tokens[key] = [self._mk_array(partial_ids),
- '{%s}' % ('' if tid is None else str(tid))]
+ for key, fulls, partials in terms:
+ if fulls:
+ tokens[key] = [self._mk_array(itertools.chain(fulls, partials)),
+ self._mk_array(fulls)]
if tokens:
self.data['addr'] = tokens
self.housenumbers = {}
- def get_term_tokens(self, conn, terms):
- """ Get token ids for a list of terms, looking them up in the database
- if necessary.
- """
- tokens = []
- askdb = []
-
- for term in terms:
- token = self.names.get(term)
- if token is None:
- askdb.append(term)
- elif token != 0:
- tokens.append(token)
-
- if askdb:
- with conn.cursor() as cur:
- cur.execute("SELECT term, getorcreate_term_id(term) FROM unnest(%s) as term",
- (askdb, ))
- for term, tid in cur:
- self.names[term] = tid
- if tid != 0:
- tokens.append(tid)
-
- return tokens
-
-
def get_hnr_tokens(self, conn, terms):
""" Get token ids for a list of housenumbers, looking them up in the
database if necessary.
projects / nominatim.git / blobdiff