Nominatim/nominatim/tokenizer/legacy_icu_tokenizer.py
Sarah Hoffmann 872ab91421 fix name of transliterator
Should be different from the normalisation rules.
2021-05-05 17:09:38 +02:00

633 lines
22 KiB
Python

"""
Tokenizer implementing normalisation as used before Nominatim 4 but using
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.sql_preprocessor import SQLPreprocessor
DBCFG_NORMALIZATION = "tokenizer_normalization"
DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
DBCFG_TRANSLITERATION = "tokenizer_transliteration"
DBCFG_ABBREVIATIONS = "tokenizer_abbreviations"
LOG = logging.getLogger()
def create(dsn, data_dir):
""" Create a new instance of the tokenizer provided by this module.
"""
return LegacyICUTokenizer(dsn, data_dir)
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 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
def init_new_db(self, config, init_db=True):
""" Set up a new tokenizer for the database.
This copies all necessary data in the project directory to make
sure the tokenizer remains stable even over updates.
"""
if config.TOKENIZER_CONFIG:
cfgfile = Path(config.TOKENIZER_CONFIG)
else:
cfgfile = config.config_dir / 'legacy_icu_tokenizer.json'
rules = json.loads(cfgfile.read_text())
self.transliteration = ';'.join(rules['normalization']) + ';'
self.abbreviations = rules["abbreviations"]
self.normalization = config.TERM_NORMALIZATION
self._install_php(config)
self._save_config(config)
if init_db:
self.update_sql_functions(config)
self._init_db_tables(config)
def init_from_project(self):
""" 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))
def finalize_import(self, config):
""" Do any required postprocessing to make the tokenizer data ready
for use.
"""
with connect(self.dsn) as conn:
sqlp = SQLPreprocessor(conn, config)
sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_indices.sql')
def update_sql_functions(self, config):
""" Reimport the SQL functions for this tokenizer.
"""
with connect(self.dsn) as conn:
max_word_freq = get_property(conn, DBCFG_MAXWORDFREQ)
sqlp = SQLPreprocessor(conn, config)
sqlp.run_sql_file(conn, 'tokenizer/legacy_icu_tokenizer.sql',
max_word_freq=max_word_freq)
def check_database(self):
""" Check that the tokenizer is set up correctly.
"""
self.init_from_project()
if self.normalization is None\
or self.transliteration is None\
or self.abbreviations is None:
return "Configuration for tokenizer 'legacy_icu' are missing."
return None
def name_analyzer(self):
""" Create a new analyzer for tokenizing names and queries
using this tokinzer. Analyzers are context managers and should
be used accordingly:
```
with tokenizer.name_analyzer() as analyzer:
analyser.tokenize()
```
When used outside the with construct, the caller must ensure to
call the close() function before destructing the analyzer.
Analyzers are not thread-safe. You need to instantiate one per thread.
"""
norm = Transliterator.createFromRules("normalizer", self.normalization)
trans = Transliterator.createFromRules("trans", self.transliteration)
return LegacyICUNameAnalyzer(self.dsn, norm, trans, self.abbreviations)
def _install_php(self, config):
""" 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]))))
def _save_config(self, config):
""" Save the configuration that needs to remain stable for the given
database as database properties.
"""
with connect(self.dsn) as conn:
set_property(conn, DBCFG_NORMALIZATION, self.normalization)
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))
def _init_db_tables(self, config):
""" Set up the word table and fill it with pre-computed word
frequencies.
"""
with connect(self.dsn) as conn:
sqlp = SQLPreprocessor(conn, config)
sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer_tables.sql')
conn.commit()
LOG.warning("Precomputing word tokens")
# 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
# copy them back into the word table
copystr = io.StringIO(''.join(('{}\t{}\n'.format(*args) for args in words.items())))
with conn.cursor() as cur:
copystr.seek(0)
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""")
conn.commit()
class LegacyICUNameAnalyzer:
""" The legacy analyzer uses the ICU library for splitting names.
Each instance opens a connection to the database to request the
normalization.
"""
def __init__(self, dsn, normalizer, transliterator, abbreviations):
self.conn = connect(dsn).connection
self.conn.autocommit = True
self.normalizer = normalizer
self.transliterator = transliterator
self.abbreviations = abbreviations
self._cache = _TokenCache()
def __enter__(self):
return self
def __exit__(self, exc_type, exc_value, traceback):
self.close()
def close(self):
""" Free all resources used by the analyzer.
"""
if self.conn:
self.conn.close()
self.conn = None
def get_word_token_info(self, conn, 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).
The function is used for testing and debugging only
and not necessarily efficient.
"""
tokens = {}
for word in words:
if word.startswith('#'):
tokens[word] = ' ' + self.make_standard_word(word[1:])
else:
tokens[word] = self.make_standard_word(word)
with 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[v]) for k, v in tokens.items()]
def normalize(self, phrase):
""" Normalize the given phrase, i.e. remove all properties that
are irrelevant for search.
"""
return self.normalizer.transliterate(phrase)
@functools.lru_cache(maxsize=1024)
def make_standard_word(self, name):
""" Create the normalised version of the input.
"""
norm = ' ' + self.transliterator.transliterate(name) + ' '
for full, abbr in self.abbreviations:
if full in norm:
norm = norm.replace(full, abbr)
return norm.strip()
def _make_standard_hnr(self, hnr):
""" Create a normalised version of a housenumber.
This function takes minor shortcuts on transliteration.
"""
if hnr.isdigit():
return hnr
return self.transliterator.transliterate(hnr)
def add_postcodes_from_db(self):
""" Add postcodes from the location_postcode table to the word table.
"""
copystr = io.StringIO()
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')
copystr.seek(0)
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):
""" Replace the search index for special phrases with the new phrases.
"""
norm_phrases = set(((self.normalize(p[0]), p[1], p[2], p[3])
for p in phrases))
with self.conn.cursor() as cur:
# Get the old phrases.
existing_phrases = set()
cur.execute("""SELECT word, class, type, operator FROM word
WHERE class != 'place'
OR (type != 'house' AND type != 'postcode')""")
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')
copystr.seek(0)
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)
LOG.info("Total phrases: %s. Added: %s. Deleted: %s",
len(norm_phrases), len(to_add), len(to_delete))
def add_country_names(self, country_code, names):
""" Add names for the given country to the search index.
"""
full_names = set((self.make_standard_word(n) for n in names))
full_names.discard('')
self._add_normalized_country_names(country_code, full_names)
def _add_normalized_country_names(self, country_code, names):
""" Add names for the given country to the search index.
"""
word_tokens = set((' ' + name for name in names))
with self.conn.cursor() as cur:
# Get existing names
cur.execute("SELECT word_token FROM word WHERE country_code = %s",
(country_code, ))
word_tokens.difference_update((t[0] for t in cur))
if word_tokens:
cur.execute("""INSERT INTO word (word_id, word_token, country_code,
search_name_count)
(SELECT nextval('seq_word'), token, '{}', 0
FROM unnest(%s) as token)
""".format(country_code), (list(word_tokens),))
def process_place(self, place):
""" Determine tokenizer information about the given place.
Returns a JSON-serialisable structure that will be handed into
the database via the token_info field.
"""
token_info = _TokenInfo(self._cache)
names = place.get('name')
if names:
full_names = set((self.make_standard_word(name) for name in names.values()))
full_names.discard('')
token_info.add_names(self.conn, full_names)
country_feature = place.get('country_feature')
if country_feature and re.fullmatch(r'[A-Za-z][A-Za-z]', country_feature):
self._add_normalized_country_names(country_feature.lower(),
full_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)
return token_info.data
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)
@staticmethod
def _split_housenumbers(hnrs):
if len(hnrs) > 1 or ',' in hnrs[0] or ';' in hnrs[0]:
# split numbers if necessary
simple_list = []
for hnr in hnrs:
simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr)))
if len(simple_list) > 1:
hnrs = list(set(simple_list))
else:
hnrs = simple_list
return hnrs
class _TokenInfo:
""" Collect token information to be sent back to the database.
"""
def __init__(self, cache):
self.cache = cache
self.data = {}
@staticmethod
def _mk_array(tokens):
return '{%s}' % ','.join((str(s) for s in tokens))
def add_names(self, conn, names):
""" 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))
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'] = ';'.join(hnrs)
def add_street(self, conn, street):
""" 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 tid is not None:
self.data['street'] = '{%d}' % tid
def add_place(self, conn, place):
""" 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])
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):
""" 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))]
if tokens:
self.data['addr'] = tokens
class _TokenCache:
""" Cache for token information to avoid repeated database queries.
This cache is not thread-safe and needs to be instantiated per
analyzer.
"""
def __init__(self):
self.names = {}
self.postcodes = set()
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.
"""
tokens = []
askdb = []
for term in terms:
token = self.housenumbers.get(term)
if token is None:
askdb.append(term)
else:
tokens.append(token)
if askdb:
with conn.cursor() as cur:
cur.execute("SELECT nr, getorcreate_hnr_id(nr) FROM unnest(%s) as nr",
(askdb, ))
for term, tid in cur:
self.housenumbers[term] = tid
tokens.append(tid)
return tokens