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remove legacy tokenizer and direct tests

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Sarah Hoffmann 2024-09-21 11:38:08 +02:00
parent e92e03e2e6
commit b87d6226fb
9 changed files with 0 additions and 2360 deletions
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426
lib-sql/tokenizer/legacy_tokenizer.sql
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@ -1,426 +0,0 @@
-- 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.
-- Get tokens used for searching the given place.
--
-- These are the tokens that will be saved in the search_name table.
CREATE OR REPLACE FUNCTION token_get_name_search_tokens(info JSONB)
RETURNS INTEGER[]
AS $$
SELECT (info->>'names')::INTEGER[]
$$ LANGUAGE SQL IMMUTABLE STRICT;
-- Get tokens for matching the place name against others.
--
-- This should usually be restricted to full name tokens.
CREATE OR REPLACE FUNCTION token_get_name_match_tokens(info JSONB)
RETURNS INTEGER[]
AS $$
SELECT (info->>'names')::INTEGER[]
$$ LANGUAGE SQL IMMUTABLE STRICT;
-- Return the housenumber tokens applicable for the place.
CREATE OR REPLACE FUNCTION token_get_housenumber_search_tokens(info JSONB)
RETURNS INTEGER[]
AS $$
SELECT (info->>'hnr_tokens')::INTEGER[]
$$ LANGUAGE SQL IMMUTABLE STRICT;
-- Return the housenumber in the form that it can be matched during search.
CREATE OR REPLACE FUNCTION token_normalized_housenumber(info JSONB)
RETURNS TEXT
AS $$
SELECT info->>'hnr';
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_is_street_address(info JSONB)
RETURNS BOOLEAN
AS $$
SELECT info->>'street' is not null or info->>'place_search' is null;
$$ LANGUAGE SQL IMMUTABLE;
CREATE OR REPLACE FUNCTION token_has_addr_street(info JSONB)
RETURNS BOOLEAN
AS $$
SELECT info->>'street' is not null and info->>'street' != '{}';
$$ LANGUAGE SQL IMMUTABLE;
CREATE OR REPLACE FUNCTION token_has_addr_place(info JSONB)
RETURNS BOOLEAN
AS $$
SELECT info->>'place_match' is not null;
$$ LANGUAGE SQL IMMUTABLE;
CREATE OR REPLACE FUNCTION token_matches_street(info JSONB, street_tokens INTEGER[])
RETURNS BOOLEAN
AS $$
SELECT (info->>'street')::INTEGER[] && street_tokens
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_matches_place(info JSONB, place_tokens INTEGER[])
RETURNS BOOLEAN
AS $$
SELECT (info->>'place_match')::INTEGER[] && place_tokens
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_addr_place_search_tokens(info JSONB)
RETURNS INTEGER[]
AS $$
SELECT (info->>'place_search')::INTEGER[]
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_get_address_keys(info JSONB)
RETURNS SETOF TEXT
AS $$
SELECT * FROM jsonb_object_keys(info->'addr');
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_get_address_search_tokens(info JSONB, key TEXT)
RETURNS INTEGER[]
AS $$
SELECT (info->'addr'->key->>0)::INTEGER[];
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_matches_address(info JSONB, key TEXT, tokens INTEGER[])
RETURNS BOOLEAN
AS $$
SELECT (info->'addr'->key->>1)::INTEGER[] && tokens;
$$ LANGUAGE SQL IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION token_get_postcode(info JSONB)
RETURNS TEXT
AS $$
SELECT info->>'postcode';
$$ LANGUAGE SQL IMMUTABLE STRICT;
-- Return token info that should be saved permanently in the database.
CREATE OR REPLACE FUNCTION token_strip_info(info JSONB)
RETURNS JSONB
AS $$
SELECT NULL::JSONB;
$$ LANGUAGE SQL IMMUTABLE STRICT;
--------------- private functions ----------------------------------------------
-- Functions for term normalisation and access to the 'word' table.
CREATE OR REPLACE FUNCTION transliteration(text) RETURNS text
AS '{{ modulepath }}/nominatim.so', 'transliteration'
LANGUAGE c IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION gettokenstring(text) RETURNS text
AS '{{ modulepath }}/nominatim.so', 'gettokenstring'
LANGUAGE c IMMUTABLE STRICT;
CREATE OR REPLACE FUNCTION make_standard_name(name TEXT) RETURNS TEXT
AS $$
DECLARE
o TEXT;
BEGIN
o := public.gettokenstring(public.transliteration(name));
RETURN trim(substr(o,1,length(o)));
END;
$$
LANGUAGE plpgsql IMMUTABLE;
-- returns NULL if the word is too common
CREATE OR REPLACE FUNCTION getorcreate_word_id(lookup_word TEXT)
RETURNS INTEGER
AS $$
DECLARE
lookup_token TEXT;
return_word_id INTEGER;
count INTEGER;
BEGIN
lookup_token := trim(lookup_word);
SELECT min(word_id), max(search_name_count) FROM word
WHERE word_token = lookup_token and class is null and type is null
INTO return_word_id, count;
IF return_word_id IS NULL THEN
return_word_id := nextval('seq_word');
INSERT INTO word VALUES (return_word_id, lookup_token, null, null, null, null, 0);
ELSE
IF count > {{ max_word_freq }} THEN
return_word_id := NULL;
END IF;
END IF;
RETURN return_word_id;
END;
$$
LANGUAGE plpgsql;
-- Create housenumber tokens from an OSM addr:housenumber.
-- The housnumber is split at comma and semicolon as necessary.
-- The function returns the normalized form of the housenumber suitable
-- for comparison.
CREATE OR REPLACE FUNCTION create_housenumbers(housenumbers TEXT[],
OUT tokens TEXT,
OUT normtext TEXT)
AS $$
BEGIN
SELECT array_to_string(array_agg(trans), ';'), array_agg(tid)::TEXT
INTO normtext, tokens
FROM (SELECT lookup_word as trans, getorcreate_housenumber_id(lookup_word) as tid
FROM (SELECT make_standard_name(h) as lookup_word
FROM unnest(housenumbers) h) x) y;
END;
$$ LANGUAGE plpgsql STABLE STRICT;
CREATE OR REPLACE FUNCTION getorcreate_housenumber_id(lookup_word TEXT)
RETURNS INTEGER
AS $$
DECLARE
lookup_token TEXT;
return_word_id INTEGER;
BEGIN
lookup_token := ' ' || trim(lookup_word);
SELECT min(word_id) FROM word
WHERE word_token = lookup_token and class='place' and type='house'
INTO return_word_id;
IF return_word_id IS NULL THEN
return_word_id := nextval('seq_word');
INSERT INTO word VALUES (return_word_id, lookup_token, null,
'place', 'house', null, 0);
END IF;
RETURN return_word_id;
END;
$$
LANGUAGE plpgsql;
CREATE OR REPLACE FUNCTION create_postcode_id(postcode TEXT)
RETURNS BOOLEAN
AS $$
DECLARE
r RECORD;
lookup_token TEXT;
return_word_id INTEGER;
BEGIN
lookup_token := ' ' || make_standard_name(postcode);
FOR r IN
SELECT word_id FROM word
WHERE word_token = lookup_token and word = postcode
and class='place' and type='postcode'
LOOP
RETURN false;
END LOOP;
INSERT INTO word VALUES (nextval('seq_word'), lookup_token, postcode,
'place', 'postcode', null, 0);
RETURN true;
END;
$$
LANGUAGE plpgsql;
CREATE OR REPLACE FUNCTION getorcreate_name_id(lookup_word TEXT, src_word TEXT)
RETURNS INTEGER
AS $$
DECLARE
lookup_token TEXT;
nospace_lookup_token TEXT;
return_word_id INTEGER;
BEGIN
lookup_token := ' '||trim(lookup_word);
SELECT min(word_id) FROM word
WHERE word_token = lookup_token and class is null and type is null
INTO return_word_id;
IF return_word_id IS NULL THEN
return_word_id := nextval('seq_word');
INSERT INTO word VALUES (return_word_id, lookup_token, src_word,
null, null, null, 0);
END IF;
RETURN return_word_id;
END;
$$
LANGUAGE plpgsql;
-- Normalize a string and lookup its word ids (partial words).
CREATE OR REPLACE FUNCTION addr_ids_from_name(lookup_word TEXT)
RETURNS INTEGER[]
AS $$
DECLARE
words TEXT[];
id INTEGER;
return_word_id INTEGER[];
word_ids INTEGER[];
j INTEGER;
BEGIN
words := string_to_array(make_standard_name(lookup_word), ' ');
IF array_upper(words, 1) IS NOT NULL THEN
FOR j IN 1..array_upper(words, 1) LOOP
IF (words[j] != '') THEN
SELECT array_agg(word_id) INTO word_ids
FROM word
WHERE word_token = words[j] and class is null and type is null;
IF word_ids IS NULL THEN
id := nextval('seq_word');
INSERT INTO word VALUES (id, words[j], null, null, null, null, 0);
return_word_id := return_word_id || id;
ELSE
return_word_id := array_merge(return_word_id, word_ids);
END IF;
END IF;
END LOOP;
END IF;
RETURN return_word_id;
END;
$$
LANGUAGE plpgsql;
-- Normalize a string and look up its name ids (full words).
CREATE OR REPLACE FUNCTION word_ids_from_name(lookup_word TEXT)
RETURNS INTEGER[]
AS $$
DECLARE
lookup_token TEXT;
return_word_ids INTEGER[];
BEGIN
lookup_token := ' '|| make_standard_name(lookup_word);
SELECT array_agg(word_id) FROM word
WHERE word_token = lookup_token and class is null and type is null
INTO return_word_ids;
RETURN return_word_ids;
END;
$$
LANGUAGE plpgsql STABLE STRICT;
CREATE OR REPLACE FUNCTION make_keywords(src HSTORE)
RETURNS INTEGER[]
AS $$
DECLARE
result INTEGER[];
s TEXT;
w INTEGER;
words TEXT[];
value TEXT;
j INTEGER;
BEGIN
result := '{}'::INTEGER[];
FOR value IN SELECT unnest(regexp_split_to_array(svals(src), E'[,;]')) LOOP
-- full name
s := make_standard_name(value);
w := getorcreate_name_id(s, value);
IF not(ARRAY[w] <@ result) THEN
result := result || w;
END IF;
-- partial single-word terms
words := string_to_array(s, ' ');
IF array_upper(words, 1) IS NOT NULL THEN
FOR j IN 1..array_upper(words, 1) LOOP
IF (words[j] != '') THEN
w = getorcreate_word_id(words[j]);
IF w IS NOT NULL AND NOT (ARRAY[w] <@ result) THEN
result := result || w;
END IF;
END IF;
END LOOP;
END IF;
-- consider parts before an opening bracket a full word as well
words := regexp_split_to_array(value, E'[(]');
IF array_upper(words, 1) > 1 THEN
s := make_standard_name(words[1]);
IF s != '' THEN
w := getorcreate_name_id(s, words[1]);
IF w IS NOT NULL AND NOT (ARRAY[w] <@ result) THEN
result := result || w;
END IF;
END IF;
END IF;
s := regexp_replace(value, '市$', '');
IF s != value THEN
s := make_standard_name(s);
IF s != '' THEN
w := getorcreate_name_id(s, value);
IF NOT (ARRAY[w] <@ result) THEN
result := result || w;
END IF;
END IF;
END IF;
END LOOP;
RETURN result;
END;
$$
LANGUAGE plpgsql;
CREATE OR REPLACE FUNCTION precompute_words(src TEXT)
RETURNS INTEGER
AS $$
DECLARE
s TEXT;
w INTEGER;
words TEXT[];
i INTEGER;
j INTEGER;
BEGIN
s := make_standard_name(src);
w := getorcreate_name_id(s, src);
w := getorcreate_word_id(s);
words := string_to_array(s, ' ');
IF array_upper(words, 1) IS NOT NULL THEN
FOR j IN 1..array_upper(words, 1) LOOP
IF (words[j] != '') THEN
w := getorcreate_word_id(words[j]);
END IF;
END LOOP;
END IF;
words := regexp_split_to_array(src, E'[,;()]');
IF array_upper(words, 1) != 1 THEN
FOR j IN 1..array_upper(words, 1) LOOP
s := make_standard_name(words[j]);
IF s != '' THEN
w := getorcreate_word_id(s);
END IF;
END LOOP;
END IF;
s := regexp_replace(src, '市$', '');
IF s != src THEN
s := make_standard_name(s);
IF s != '' THEN
w := getorcreate_name_id(s, src);
END IF;
END IF;
RETURN 1;
END;
$$
LANGUAGE plpgsql;

10
lib-sql/tokenizer/legacy_tokenizer_indices.sql
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@ -1,10 +0,0 @@
-- 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.
-- Required for details lookup.
CREATE INDEX IF NOT EXISTS idx_word_word_id
ON word USING BTREE (word_id) {{db.tablespace.search_index}};

28
lib-sql/tokenizer/legacy_tokenizer_tables.sql
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-- 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.
DROP TABLE IF EXISTS word;
CREATE TABLE word (
word_id INTEGER,
word_token text NOT NULL,
word text,
class text,
type text,
country_code varchar(2),
search_name_count INTEGER,
operator TEXT
) {{db.tablespace.search_data}};
CREATE INDEX idx_word_word_token ON word
USING BTREE (word_token) {{db.tablespace.search_index}};
CREATE INDEX idx_word_word ON word
USING BTREE (word) {{db.tablespace.search_index}} WHERE word is not null;
GRANT SELECT ON word TO "{{config.DATABASE_WEBUSER}}";
DROP SEQUENCE IF EXISTS seq_word;
CREATE SEQUENCE seq_word start 1;
GRANT SELECT ON seq_word to "{{config.DATABASE_WEBUSER}}";

273
src/nominatim_api/search/legacy_tokenizer.py
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# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2024 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Implementation of query analysis for the legacy tokenizer.
"""
from typing import Tuple, Dict, List, Optional, Iterator, Any, cast
from copy import copy
from collections import defaultdict
import dataclasses
import sqlalchemy as sa
from ..typing import SaRow
from ..connection import SearchConnection
from ..logging import log
from . import query as qmod
from .query_analyzer_factory import AbstractQueryAnalyzer
def yield_words(terms: List[str], start: int) -> Iterator[Tuple[str, qmod.TokenRange]]:
""" Return all combinations of words in the terms list after the
given position.
"""
total = len(terms)
for first in range(start, total):
word = terms[first]
yield word, qmod.TokenRange(first, first + 1)
for last in range(first + 1, min(first + 20, total)):
word = ' '.join((word, terms[last]))
yield word, qmod.TokenRange(first, last + 1)
@dataclasses.dataclass
class LegacyToken(qmod.Token):
""" Specialised token for legacy tokenizer.
"""
word_token: str
category: Optional[Tuple[str, str]]
country: Optional[str]
operator: Optional[str]
@property
def info(self) -> Dict[str, Any]:
""" Dictionary of additional properties of the token.
Should only be used for debugging purposes.
"""
return {'category': self.category,
'country': self.country,
'operator': self.operator}
def get_category(self) -> Tuple[str, str]:
assert self.category
return self.category
class LegacyQueryAnalyzer(AbstractQueryAnalyzer):
""" Converter for query strings into a tokenized query
using the tokens created by a legacy tokenizer.
"""
def __init__(self, conn: SearchConnection) -> None:
self.conn = conn
async def setup(self) -> None:
""" Set up static data structures needed for the analysis.
"""
self.max_word_freq = int(await self.conn.get_property('tokenizer_maxwordfreq'))
if 'word' not in self.conn.t.meta.tables:
sa.Table('word', self.conn.t.meta,
sa.Column('word_id', sa.Integer),
sa.Column('word_token', sa.Text, nullable=False),
sa.Column('word', sa.Text),
sa.Column('class', sa.Text),
sa.Column('type', sa.Text),
sa.Column('country_code', sa.Text),
sa.Column('search_name_count', sa.Integer),
sa.Column('operator', sa.Text))
async def analyze_query(self, phrases: List[qmod.Phrase]) -> qmod.QueryStruct:
""" Analyze the given list of phrases and return the
tokenized query.
"""
log().section('Analyze query (using Legacy tokenizer)')
normalized = []
if phrases:
for row in await self.conn.execute(sa.select(*(sa.func.make_standard_name(p.text)
for p in phrases))):
normalized = [qmod.Phrase(p.ptype, r) for r, p in zip(row, phrases) if r]
break
query = qmod.QueryStruct(normalized)
log().var_dump('Normalized query', query.source)
if not query.source:
return query
parts, words = self.split_query(query)
lookup_words = list(words.keys())
log().var_dump('Split query', parts)
log().var_dump('Extracted words', lookup_words)
for row in await self.lookup_in_db(lookup_words):
for trange in words[row.word_token.strip()]:
token, ttype = self.make_token(row)
if ttype == qmod.TokenType.NEAR_ITEM:
if trange.start == 0:
query.add_token(trange, qmod.TokenType.NEAR_ITEM, token)
elif ttype == qmod.TokenType.QUALIFIER:
query.add_token(trange, qmod.TokenType.QUALIFIER, token)
if trange.start == 0 or trange.end == query.num_token_slots():
token = copy(token)
token.penalty += 0.1 * (query.num_token_slots())
query.add_token(trange, qmod.TokenType.NEAR_ITEM, token)
elif ttype != qmod.TokenType.PARTIAL or trange.start + 1 == trange.end:
query.add_token(trange, ttype, token)
self.add_extra_tokens(query, parts)
self.rerank_tokens(query)
log().table_dump('Word tokens', _dump_word_tokens(query))
return query
def normalize_text(self, text: str) -> str:
""" Bring the given text into a normalized form.
This only removes case, so some difference with the normalization
in the phrase remains.
"""
return text.lower()
def split_query(self, query: qmod.QueryStruct) -> Tuple[List[str],
Dict[str, List[qmod.TokenRange]]]:
""" Transliterate the phrases and split them into tokens.
Returns a list of transliterated tokens and a dictionary
of words for lookup together with their position.
"""
parts: List[str] = []
phrase_start = 0
words = defaultdict(list)
for phrase in query.source:
query.nodes[-1].ptype = phrase.ptype
for trans in phrase.text.split(' '):
if trans:
for term in trans.split(' '):
if term:
parts.append(trans)
query.add_node(qmod.BreakType.TOKEN, phrase.ptype)
query.nodes[-1].btype = qmod.BreakType.WORD
query.nodes[-1].btype = qmod.BreakType.PHRASE
for word, wrange in yield_words(parts, phrase_start):
words[word].append(wrange)
phrase_start = len(parts)
query.nodes[-1].btype = qmod.BreakType.END
return parts, words
async def lookup_in_db(self, words: List[str]) -> 'sa.Result[Any]':
""" Return the token information from the database for the
given word tokens.
"""
t = self.conn.t.meta.tables['word']
sql = t.select().where(t.c.word_token.in_(words + [' ' + w for w in words]))
return await self.conn.execute(sql)
def make_token(self, row: SaRow) -> Tuple[LegacyToken, qmod.TokenType]:
""" Create a LegacyToken from the row of the word table.
Also determines the type of token.
"""
penalty = 0.0
is_indexed = True
rowclass = getattr(row, 'class')
if row.country_code is not None:
ttype = qmod.TokenType.COUNTRY
lookup_word = row.country_code
elif rowclass is not None:
if rowclass == 'place' and row.type == 'house':
ttype = qmod.TokenType.HOUSENUMBER
lookup_word = row.word_token[1:]
elif rowclass == 'place' and row.type == 'postcode':
ttype = qmod.TokenType.POSTCODE
lookup_word = row.word
else:
ttype = qmod.TokenType.NEAR_ITEM if row.operator in ('in', 'near')\
else qmod.TokenType.QUALIFIER
lookup_word = row.word
elif row.word_token.startswith(' '):
ttype = qmod.TokenType.WORD
lookup_word = row.word or row.word_token[1:]
else:
ttype = qmod.TokenType.PARTIAL
lookup_word = row.word_token
penalty = 0.21
if row.search_name_count > self.max_word_freq:
is_indexed = False
return LegacyToken(penalty=penalty, token=row.word_id,
count=max(1, row.search_name_count or 1),
addr_count=1, # not supported
lookup_word=lookup_word,
word_token=row.word_token.strip(),
category=(rowclass, row.type) if rowclass is not None else None,
country=row.country_code,
operator=row.operator,
is_indexed=is_indexed),\
ttype
def add_extra_tokens(self, query: qmod.QueryStruct, parts: List[str]) -> None:
""" Add tokens to query that are not saved in the database.
"""
for part, node, i in zip(parts, query.nodes, range(1000)):
if len(part) <= 4 and part.isdigit()\
and not node.has_tokens(i+1, qmod.TokenType.HOUSENUMBER):
query.add_token(qmod.TokenRange(i, i+1), qmod.TokenType.HOUSENUMBER,
LegacyToken(penalty=0.5, token=0, count=1, addr_count=1,
lookup_word=part, word_token=part,
category=None, country=None,
operator=None, is_indexed=True))
def rerank_tokens(self, query: qmod.QueryStruct) -> None:
""" Add penalties to tokens that depend on presence of other token.
"""
for _, node, tlist in query.iter_token_lists():
if tlist.ttype == qmod.TokenType.POSTCODE:
for repl in node.starting:
if repl.end == tlist.end and repl.ttype != qmod.TokenType.POSTCODE \
and (repl.ttype != qmod.TokenType.HOUSENUMBER
or len(tlist.tokens[0].lookup_word) > 4):
repl.add_penalty(0.39)
elif tlist.ttype == qmod.TokenType.HOUSENUMBER \
and len(tlist.tokens[0].lookup_word) <= 3:
if any(c.isdigit() for c in tlist.tokens[0].lookup_word):
for repl in node.starting:
if repl.end == tlist.end and repl.ttype != qmod.TokenType.HOUSENUMBER:
repl.add_penalty(0.5 - tlist.tokens[0].penalty)
def _dump_word_tokens(query: qmod.QueryStruct) -> Iterator[List[Any]]:
yield ['type', 'token', 'word_token', 'lookup_word', 'penalty', 'count', 'info', 'indexed']
for node in query.nodes:
for tlist in node.starting:
for token in tlist.tokens:
t = cast(LegacyToken, token)
yield [tlist.ttype.name, t.token, t.word_token or '',
t.lookup_word or '', t.penalty, t.count, t.info,
'Y' if t.is_indexed else 'N']
async def create_query_analyzer(conn: SearchConnection) -> AbstractQueryAnalyzer:
""" Create and set up a new query analyzer for a database based
on the ICU tokenizer.
"""
out = LegacyQueryAnalyzer(conn)
await out.setup()
return out

666
src/nominatim_db/tokenizer/legacy_tokenizer.py
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@ -1,666 +0,0 @@
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2024 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Tokenizer implementing normalisation as used before Nominatim 4.
"""
from typing import Optional, Sequence, List, Tuple, Mapping, Any, Callable, \
cast, Dict, Set, Iterable
from collections import OrderedDict
import logging
from pathlib import Path
import re
import shutil
from icu import Transliterator
import psycopg
from psycopg import sql as pysql
from ..errors import UsageError
from ..db.connection import connect, Connection, drop_tables, table_exists,\
execute_scalar, register_hstore
from ..config import Configuration
from ..db import properties
from ..db import utils as db_utils
from ..db.sql_preprocessor import SQLPreprocessor
from ..data.place_info import PlaceInfo
from .base import AbstractAnalyzer, AbstractTokenizer
DBCFG_NORMALIZATION = "tokenizer_normalization"
DBCFG_MAXWORDFREQ = "tokenizer_maxwordfreq"
LOG = logging.getLogger()
def create(dsn: str, data_dir: Path) -> 'LegacyTokenizer':
""" Create a new instance of the tokenizer provided by this module.
"""
LOG.warning('WARNING: the legacy tokenizer is deprecated '
'and will be removed in Nominatim 5.0.')
return LegacyTokenizer(dsn, data_dir)
def _install_module(config_module_path: str, src_dir: Optional[Path], module_dir: Path) -> str:
""" Copies the PostgreSQL normalisation module into the project
directory if necessary. For historical reasons the module is
saved in the '/module' subdirectory and not with the other tokenizer
data.
The function detects when the installation is run from the
build directory. It doesn't touch the module in that case.
"""
# Custom module locations are simply used as is.
if config_module_path:
LOG.info("Using custom path for database module at '%s'", config_module_path)
return config_module_path
# Otherwise a source dir must be given.
if src_dir is None:
raise UsageError("The legacy tokenizer cannot be used with the Nominatim pip module.")
# Compatibility mode for builddir installations.
if module_dir.exists() and src_dir.samefile(module_dir):
LOG.info('Running from build directory. Leaving database module as is.')
return str(module_dir)
# In any other case install the module in the project directory.
if not module_dir.exists():
module_dir.mkdir()
destfile = module_dir / 'nominatim.so'
shutil.copy(str(src_dir / 'nominatim.so'), str(destfile))
destfile.chmod(0o755)
LOG.info('Database module installed at %s', str(destfile))
return str(module_dir)
def _check_module(module_dir: str, conn: Connection) -> None:
""" Try to use the PostgreSQL module to confirm that it is correctly
installed and accessible from PostgreSQL.
"""
with conn.cursor() as cur:
try:
cur.execute(pysql.SQL("""CREATE FUNCTION nominatim_test_import_func(text)
RETURNS text AS {}, 'transliteration'
LANGUAGE c IMMUTABLE STRICT;
DROP FUNCTION nominatim_test_import_func(text)
""").format(pysql.Literal(f'{module_dir}/nominatim.so')))
except psycopg.DatabaseError as err:
LOG.fatal("Error accessing database module: %s", err)
raise UsageError("Database module cannot be accessed.") from err
class LegacyTokenizer(AbstractTokenizer):
""" The legacy tokenizer uses a special PostgreSQL module to normalize
names and queries. The tokenizer thus implements normalization through
calls to the database.
"""
def __init__(self, dsn: str, data_dir: Path) -> None:
self.dsn = dsn
self.data_dir = data_dir
self.normalization: Optional[str] = None
def init_new_db(self, config: Configuration, init_db: bool = True) -> None:
""" 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.
"""
assert config.project_dir is not None
module_dir = _install_module(config.DATABASE_MODULE_PATH,
config.lib_dir.module,
config.project_dir / 'module')
self.normalization = config.TERM_NORMALIZATION
with connect(self.dsn) as conn:
_check_module(module_dir, conn)
self._save_config(conn, config)
conn.commit()
if init_db:
self.update_sql_functions(config)
self._init_db_tables(config)
def init_from_project(self, config: Configuration) -> None:
""" Initialise the tokenizer from the project directory.
"""
assert config.project_dir is not None
with connect(self.dsn) as conn:
self.normalization = properties.get_property(conn, DBCFG_NORMALIZATION)
if not (config.project_dir / 'module' / 'nominatim.so').exists():
_install_module(config.DATABASE_MODULE_PATH,
config.lib_dir.module,
config.project_dir / 'module')
def finalize_import(self, config: Configuration) -> None:
""" 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: Configuration) -> None:
""" Reimport the SQL functions for this tokenizer.
"""
assert config.project_dir is not None
with connect(self.dsn) as conn:
max_word_freq = properties.get_property(conn, DBCFG_MAXWORDFREQ)
modulepath = config.DATABASE_MODULE_PATH or \
str((config.project_dir / 'module').resolve())
sqlp = SQLPreprocessor(conn, config)
sqlp.run_sql_file(conn, 'tokenizer/legacy_tokenizer.sql',
max_word_freq=max_word_freq,
modulepath=modulepath)
def check_database(self, _: Configuration) -> Optional[str]:
""" Check that the tokenizer is set up correctly.
"""
hint = """\
The Postgresql extension nominatim.so was not correctly loaded.
Error: {error}
Hints:
* Check the output of the CMmake/make installation step
* Does nominatim.so exist?
* Does nominatim.so exist on the database server?
* Can nominatim.so be accessed by the database user?
"""
with connect(self.dsn) as conn:
try:
out = execute_scalar(conn, "SELECT make_standard_name('a')")
except psycopg.Error as err:
return hint.format(error=str(err))
if out != 'a':
return hint.format(error='Unexpected result for make_standard_name()')
return None
def migrate_database(self, config: Configuration) -> None:
""" Initialise the project directory of an existing database for
use with this tokenizer.
This is a special migration function for updating existing databases
to new software versions.
"""
assert config.project_dir is not None
self.normalization = config.TERM_NORMALIZATION
module_dir = _install_module(config.DATABASE_MODULE_PATH,
config.lib_dir.module,
config.project_dir / 'module')
with connect(self.dsn) as conn:
_check_module(module_dir, conn)
self._save_config(conn, config)
def update_statistics(self, config: Configuration, threads: int = 1) -> None:
""" Recompute the frequency of full words.
"""
with connect(self.dsn) as conn:
if table_exists(conn, 'search_name'):
drop_tables(conn, "word_frequencies")
with conn.cursor() as cur:
LOG.info("Computing word frequencies")
cur.execute("""CREATE TEMP TABLE word_frequencies AS
SELECT unnest(name_vector) as id, count(*)
FROM search_name GROUP BY id""")
cur.execute("CREATE INDEX ON word_frequencies(id)")
LOG.info("Update word table with recomputed frequencies")
cur.execute("""UPDATE word SET search_name_count = count
FROM word_frequencies
WHERE word_token like ' %' and word_id = id""")
drop_tables(conn, "word_frequencies")
conn.commit()
def update_word_tokens(self) -> None:
""" No house-keeping implemented for the legacy tokenizer.
"""
LOG.info("No tokenizer clean-up available.")
def name_analyzer(self) -> 'LegacyNameAnalyzer':
""" 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.
"""
normalizer = Transliterator.createFromRules("phrase normalizer",
self.normalization)
return LegacyNameAnalyzer(self.dsn, normalizer)
def most_frequent_words(self, conn: Connection, num: int) -> List[str]:
""" Return a list of the `num` most frequent full words
in the database.
"""
with conn.cursor() as cur:
cur.execute(""" SELECT word FROM word WHERE word is not null
ORDER BY search_name_count DESC LIMIT %s""", (num,))
return list(s[0] for s in cur)
def _init_db_tables(self, config: Configuration) -> None:
""" 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")
db_utils.execute_file(self.dsn, config.lib_dir.data / 'words.sql')
def _save_config(self, conn: Connection, config: Configuration) -> None:
""" Save the configuration that needs to remain stable for the given
database as database properties.
"""
assert self.normalization is not None
properties.set_property(conn, DBCFG_NORMALIZATION, self.normalization)
properties.set_property(conn, DBCFG_MAXWORDFREQ, config.MAX_WORD_FREQUENCY)
class LegacyNameAnalyzer(AbstractAnalyzer):
""" The legacy analyzer uses the special Postgresql module for
splitting names.
Each instance opens a connection to the database to request the
normalization.
"""
def __init__(self, dsn: str, normalizer: Any):
self.conn: Optional[Connection] = connect(dsn)
self.conn.autocommit = True
self.normalizer = normalizer
register_hstore(self.conn)
self._cache = _TokenCache(self.conn)
def close(self) -> None:
""" Free all resources used by the analyzer.
"""
if self.conn:
self.conn.close()
self.conn = None
def get_word_token_info(self, words: Sequence[str]) -> List[Tuple[str, str, int]]:
""" 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.
"""
assert self.conn is not None
with self.conn.cursor() as cur:
cur.execute("""SELECT t.term, word_token, word_id
FROM word, (SELECT unnest(%s::TEXT[]) as term) t
WHERE word_token = (CASE
WHEN left(t.term, 1) = '#' THEN
' ' || make_standard_name(substring(t.term from 2))
ELSE
make_standard_name(t.term)
END)
and class is null and country_code is null""",
(words, ))
return [(r[0], r[1], r[2]) for r in cur]
def normalize(self, phrase: str) -> str:
""" Normalize the given phrase, i.e. remove all properties that
are irrelevant for search.
"""
return cast(str, self.normalizer.transliterate(phrase))
def normalize_postcode(self, postcode: str) -> str:
""" 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 update_postcodes_from_db(self) -> None:
""" Update postcode tokens in the word table from the location_postcode
table.
"""
assert self.conn is not None
with self.conn.cursor() as cur:
# 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""")
to_delete = []
to_add = []
for postcode, word in cur:
if postcode is None:
to_delete.append(word)
else:
to_add.append(postcode)
if to_delete:
cur.execute("""DELETE FROM WORD
WHERE class ='place' and type = 'postcode'
and word = any(%s)
""", (to_delete, ))
if to_add:
cur.execute("""SELECT count(create_postcode_id(pc))
FROM unnest(%s::text[]) as pc
""", (to_add, ))
def update_special_phrases(self, phrases: Iterable[Tuple[str, str, str, str]],
should_replace: bool) -> None:
""" Replace the search index for special phrases with the new phrases.
"""
assert self.conn is not None
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 as cls, 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:
cur.executemany(
""" INSERT INTO word (word_id, word_token, word, class, type,
search_name_count, operator)
(SELECT nextval('seq_word'), ' ' || make_standard_name(name), name,
class, type, 0,
CASE WHEN op in ('in', 'near') THEN op ELSE null END
FROM (VALUES (%s, %s, %s, %s)) as v(name, class, type, op))""",
to_add)
if to_delete and should_replace:
cur.executemany(
""" DELETE FROM word
USING (VALUES (%s, %s, %s, %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: str, names: Mapping[str, str]) -> None:
""" Add names for the given country to the search index.
"""
assert self.conn is not None
with self.conn.cursor() as cur:
cur.execute(
"""INSERT INTO word (word_id, word_token, country_code)
(SELECT nextval('seq_word'), lookup_token, %s
FROM (SELECT DISTINCT ' ' || make_standard_name(n) as lookup_token
FROM unnest(%s::TEXT[])n) y
WHERE NOT EXISTS(SELECT * FROM word
WHERE word_token = lookup_token and country_code = %s))
""", (country_code, list(names.values()), country_code))
def process_place(self, place: PlaceInfo) -> Mapping[str, Any]:
""" Determine tokenizer information about the given place.
Returns a JSON-serialisable structure that will be handed into
the database via the token_info field.
"""
assert self.conn is not None
token_info = _TokenInfo(self._cache)
names = place.name
if names:
token_info.add_names(self.conn, names)
if place.is_country():
assert place.country_code is not None
self.add_country_names(place.country_code, names)
address = place.address
if address:
self._process_place_address(token_info, address)
return token_info.data
def _process_place_address(self, token_info: '_TokenInfo', address: Mapping[str, str]) -> None:
assert self.conn is not None
hnrs = []
addr_terms = []
for key, value in address.items():
if key == 'postcode':
# Make sure the normalized postcode is present in the word table.
if re.search(r'[:,;]', value) is None:
norm_pc = self.normalize_postcode(value)
token_info.set_postcode(norm_pc)
self._cache.add_postcode(self.conn, norm_pc)
elif key in ('housenumber', 'streetnumber', 'conscriptionnumber'):
hnrs.append(value)
elif key == 'street':
token_info.add_street(self.conn, value)
elif key == 'place':
token_info.add_place(self.conn, value)
elif not key.startswith('_') \
and key not in ('country', 'full', 'inclusion'):
addr_terms.append((key, value))
if hnrs:
token_info.add_housenumbers(self.conn, hnrs)
if addr_terms:
token_info.add_address_terms(self.conn, addr_terms)
class _TokenInfo:
""" Collect token information to be sent back to the database.
"""
def __init__(self, cache: '_TokenCache') -> None:
self.cache = cache
self.data: Dict[str, Any] = {}
def add_names(self, conn: Connection, names: Mapping[str, str]) -> None:
""" Add token information for the names of the place.
"""
# Create the token IDs for all names.
self.data['names'] = execute_scalar(conn, "SELECT make_keywords(%s)::text",
(names, ))
def add_housenumbers(self, conn: Connection, hnrs: Sequence[str]) -> None:
""" Extract housenumber information from the address.
"""
if len(hnrs) == 1:
token = self.cache.get_housenumber(hnrs[0])
if token is not None:
self.data['hnr_tokens'] = token
self.data['hnr'] = hnrs[0]
return
# split numbers if necessary
simple_list: List[str] = []
for hnr in hnrs:
simple_list.extend((x.strip() for x in re.split(r'[;,]', hnr)))
if len(simple_list) > 1:
simple_list = list(set(simple_list))
with conn.cursor() as cur:
cur.execute("SELECT * FROM create_housenumbers(%s)", (simple_list, ))
result = cur.fetchone()
assert result is not None
self.data['hnr_tokens'], self.data['hnr'] = result
def set_postcode(self, postcode: str) -> None:
""" Set or replace the postcode token with the given value.
"""
self.data['postcode'] = postcode
def add_street(self, conn: Connection, street: str) -> None:
""" Add addr:street match terms.
"""
def _get_street(name: str) -> Optional[str]:
return cast(Optional[str],
execute_scalar(conn, "SELECT word_ids_from_name(%s)::text", (name, )))
tokens = self.cache.streets.get(street, _get_street)
self.data['street'] = tokens or '{}'
def add_place(self, conn: Connection, place: str) -> None:
""" Add addr:place search and match terms.
"""
def _get_place(name: str) -> Tuple[List[int], List[int]]:
with conn.cursor() as cur:
cur.execute("""SELECT make_keywords(hstore('name' , %s))::text,
word_ids_from_name(%s)::text""",
(name, name))
return cast(Tuple[List[int], List[int]], cur.fetchone())
self.data['place_search'], self.data['place_match'] = \
self.cache.places.get(place, _get_place)
def add_address_terms(self, conn: Connection, terms: Sequence[Tuple[str, str]]) -> None:
""" Add additional address terms.
"""
def _get_address_term(name: str) -> Tuple[List[int], List[int]]:
with conn.cursor() as cur:
cur.execute("""SELECT addr_ids_from_name(%s)::text,
word_ids_from_name(%s)::text""",
(name, name))
return cast(Tuple[List[int], List[int]], cur.fetchone())
tokens = {}
for key, value in terms:
items = self.cache.address_terms.get(value, _get_address_term)
if items[0] or items[1]:
tokens[key] = items
if tokens:
self.data['addr'] = tokens
class _LRU:
""" Least recently used cache that accepts a generator function to
produce the item when there is a cache miss.
"""
def __init__(self, maxsize: int = 128):
self.data: 'OrderedDict[str, Any]' = OrderedDict()
self.maxsize = maxsize
def get(self, key: str, generator: Callable[[str], Any]) -> Any:
""" Get the item with the given key from the cache. If nothing
is found in the cache, generate the value through the
generator function and store it in the cache.
"""
value = self.data.get(key)
if value is not None:
self.data.move_to_end(key)
else:
value = generator(key)
if len(self.data) >= self.maxsize:
self.data.popitem(last=False)
self.data[key] = value
return value
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, conn: Connection):
# various LRU caches
self.streets = _LRU(maxsize=256)
self.places = _LRU(maxsize=128)
self.address_terms = _LRU(maxsize=1024)
# Lookup houseunumbers up to 100 and cache them
with conn.cursor() as cur:
cur.execute("""SELECT i, ARRAY[getorcreate_housenumber_id(i::text)]::text
FROM generate_series(1, 100) as i""")
self._cached_housenumbers: Dict[str, str] = {str(r[0]): r[1] for r in cur}
# For postcodes remember the ones that have already been added
self.postcodes: Set[str] = set()
def get_housenumber(self, number: str) -> Optional[str]:
""" Get a housenumber token from the cache.
"""
return self._cached_housenumbers.get(number)
def add_postcode(self, conn: Connection, postcode: str) -> None:
""" Make sure the given postcode is in the database.
"""
if postcode not in self.postcodes:
with conn.cursor() as cur:
cur.execute('SELECT create_postcode_id(%s)', (postcode, ))
self.postcodes.add(postcode)

241
test/python/api/search/test_legacy_query_analyzer.py
View File

@ -1,241 +0,0 @@
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2024 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Tests for query analyzer for legacy tokenizer.
"""
import pytest
import pytest_asyncio
from nominatim_api import NominatimAPIAsync
from nominatim_api.search.query import Phrase, PhraseType, TokenType, BreakType
import nominatim_api.search.legacy_tokenizer as tok
from nominatim_api.logging import set_log_output, get_and_disable
async def add_word(conn, word_id, word_token, word, count):
t = conn.t.meta.tables['word']
await conn.execute(t.insert(), {'word_id': word_id,
'word_token': word_token,
'search_name_count': count,
'word': word})
async def add_housenumber(conn, word_id, hnr):
t = conn.t.meta.tables['word']
await conn.execute(t.insert(), {'word_id': word_id,
'word_token': ' ' + hnr,
'word': hnr,
'class': 'place',
'type': 'house'})
async def add_postcode(conn, word_id, postcode):
t = conn.t.meta.tables['word']
await conn.execute(t.insert(), {'word_id': word_id,
'word_token': ' ' + postcode,
'word': postcode,
'class': 'place',
'type': 'postcode'})
async def add_special_term(conn, word_id, word_token, cls, typ, op):
t = conn.t.meta.tables['word']
await conn.execute(t.insert(), {'word_id': word_id,
'word_token': word_token,
'word': word_token,
'class': cls,
'type': typ,
'operator': op})
def make_phrase(query):
return [Phrase(PhraseType.NONE, s) for s in query.split(',')]
@pytest_asyncio.fixture
async def conn(table_factory, temp_db_cursor):
""" Create an asynchronous SQLAlchemy engine for the test DB.
"""
table_factory('nominatim_properties',
definition='property TEXT, value TEXT',
content=(('tokenizer_maxwordfreq', '10000'), ))
table_factory('word',
definition="""word_id INT, word_token TEXT, word TEXT,
class TEXT, type TEXT, country_code TEXT,
search_name_count INT, operator TEXT
""")
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION make_standard_name(name TEXT)
RETURNS TEXT AS $$ SELECT lower(name); $$ LANGUAGE SQL;""")
async with NominatimAPIAsync() as api:
async with api.begin() as conn:
yield conn
@pytest.mark.asyncio
async def test_empty_phrase(conn):
ana = await tok.create_query_analyzer(conn)
query = await ana.analyze_query([])
assert len(query.source) == 0
assert query.num_token_slots() == 0
@pytest.mark.asyncio
async def test_single_phrase_with_unknown_terms(conn):
ana = await tok.create_query_analyzer(conn)
await add_word(conn, 1, 'foo', 'FOO', 3)
query = await ana.analyze_query(make_phrase('foo BAR'))
assert len(query.source) == 1
assert query.source[0].ptype == PhraseType.NONE
assert query.source[0].text == 'foo bar'
assert query.num_token_slots() == 2
assert len(query.nodes[0].starting) == 1
assert not query.nodes[1].starting
@pytest.mark.asyncio
async def test_multiple_phrases(conn):
ana = await tok.create_query_analyzer(conn)
await add_word(conn, 1, 'one', 'one', 13)
await add_word(conn, 2, 'two', 'two', 45)
await add_word(conn, 100, 'one two', 'one two', 3)
await add_word(conn, 3, 'three', 'three', 4584)
query = await ana.analyze_query(make_phrase('one two,three'))
assert len(query.source) == 2
@pytest.mark.asyncio
async def test_housenumber_token(conn):
ana = await tok.create_query_analyzer(conn)
await add_housenumber(conn, 556, '45 a')
query = await ana.analyze_query(make_phrase('45 A'))
assert query.num_token_slots() == 2
assert len(query.nodes[0].starting) == 2
query.nodes[0].starting.sort(key=lambda tl: tl.end)
hn1 = query.nodes[0].starting[0]
assert hn1.ttype == TokenType.HOUSENUMBER
assert hn1.end == 1
assert hn1.tokens[0].token == 0
hn2 = query.nodes[0].starting[1]
assert hn2.ttype == TokenType.HOUSENUMBER
assert hn2.end == 2
assert hn2.tokens[0].token == 556
@pytest.mark.asyncio
async def test_postcode_token(conn):
ana = await tok.create_query_analyzer(conn)
await add_postcode(conn, 34, '45ax')
query = await ana.analyze_query(make_phrase('45AX'))
assert query.num_token_slots() == 1
assert [tl.ttype for tl in query.nodes[0].starting] == [TokenType.POSTCODE]
@pytest.mark.asyncio
async def test_partial_tokens(conn):
ana = await tok.create_query_analyzer(conn)
await add_word(conn, 1, ' foo', 'foo', 99)
await add_word(conn, 1, 'foo', 'FOO', 99)
await add_word(conn, 1, 'bar', 'FOO', 990000)
query = await ana.analyze_query(make_phrase('foo bar'))
assert query.num_token_slots() == 2
first = query.nodes[0].starting
first.sort(key=lambda tl: tl.tokens[0].penalty)
assert [tl.ttype for tl in first] == [TokenType.WORD, TokenType.PARTIAL]
assert all(tl.tokens[0].lookup_word == 'foo' for tl in first)
second = query.nodes[1].starting
assert [tl.ttype for tl in second] == [TokenType.PARTIAL]
assert not second[0].tokens[0].is_indexed
@pytest.mark.asyncio
@pytest.mark.parametrize('term,order', [('23456', ['POSTCODE', 'HOUSENUMBER', 'WORD', 'PARTIAL']),
('3', ['HOUSENUMBER', 'POSTCODE', 'WORD', 'PARTIAL'])
])
async def test_penalty_postcodes_and_housenumbers(conn, term, order):
ana = await tok.create_query_analyzer(conn)
await add_postcode(conn, 1, term)
await add_housenumber(conn, 2, term)
await add_word(conn, 3, term, term, 5)
await add_word(conn, 4, ' ' + term, term, 1)
query = await ana.analyze_query(make_phrase(term))
assert query.num_token_slots() == 1
torder = [(tl.tokens[0].penalty, tl.ttype.name) for tl in query.nodes[0].starting]
torder.sort()
assert [t[1] for t in torder] == order
@pytest.mark.asyncio
async def test_category_words_only_at_beginning(conn):
ana = await tok.create_query_analyzer(conn)
await add_special_term(conn, 1, 'foo', 'amenity', 'restaurant', 'in')
await add_word(conn, 2, ' bar', 'BAR', 1)
query = await ana.analyze_query(make_phrase('foo BAR foo'))
assert query.num_token_slots() == 3
assert len(query.nodes[0].starting) == 1
assert query.nodes[0].starting[0].ttype == TokenType.NEAR_ITEM
assert not query.nodes[2].starting
@pytest.mark.asyncio
async def test_qualifier_words(conn):
ana = await tok.create_query_analyzer(conn)
await add_special_term(conn, 1, 'foo', 'amenity', 'restaurant', '-')
await add_word(conn, 2, ' bar', 'w', None)
query = await ana.analyze_query(make_phrase('foo BAR foo BAR foo'))
assert query.num_token_slots() == 5
assert set(t.ttype for t in query.nodes[0].starting) == {TokenType.NEAR_ITEM, TokenType.QUALIFIER}
assert set(t.ttype for t in query.nodes[2].starting) == {TokenType.QUALIFIER}
assert set(t.ttype for t in query.nodes[4].starting) == {TokenType.NEAR_ITEM, TokenType.QUALIFIER}
@pytest.mark.asyncio
@pytest.mark.parametrize('logtype', ['text', 'html'])
async def test_log_output(conn, logtype):
ana = await tok.create_query_analyzer(conn)
await add_word(conn, 1, 'foo', 'FOO', 99)
set_log_output(logtype)
await ana.analyze_query(make_phrase('foo'))
assert get_and_disable()

99
test/python/mock_legacy_word_table.py
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@ -1,99 +0,0 @@
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2024 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Legacy word table for testing with functions to prefil and test contents
of the table.
"""
from nominatim_db.db.connection import execute_scalar
class MockLegacyWordTable:
""" A word table for testing using legacy word table structure.
"""
def __init__(self, conn):
self.conn = conn
with conn.cursor() as cur:
cur.execute("""CREATE TABLE word (word_id INTEGER,
word_token text,
word text,
class text,
type text,
country_code varchar(2),
search_name_count INTEGER,
operator TEXT)""")
conn.commit()
def add_full_word(self, word_id, word, word_token=None):
with self.conn.cursor() as cur:
cur.execute("""INSERT INTO word (word_id, word_token, word)
VALUES (%s, %s, %s)
""", (word_id, ' ' + (word_token or word), word))
self.conn.commit()
def add_special(self, word_token, word, cls, typ, oper):
with self.conn.cursor() as cur:
cur.execute("""INSERT INTO word (word_token, word, class, type, operator)
VALUES (%s, %s, %s, %s, %s)
""", (word_token, word, cls, typ, oper))
self.conn.commit()
def add_country(self, country_code, word_token):
with self.conn.cursor() as cur:
cur.execute("INSERT INTO word (word_token, country_code) VALUES(%s, %s)",
(word_token, country_code))
self.conn.commit()
def add_postcode(self, word_token, postcode):
with self.conn.cursor() as cur:
cur.execute("""INSERT INTO word (word_token, word, class, type)
VALUES (%s, %s, 'place', 'postcode')
""", (word_token, postcode))
self.conn.commit()
def count(self):
return execute_scalar(self.conn, "SELECT count(*) FROM word")
def count_special(self):
return execute_scalar(self.conn, "SELECT count(*) FROM word WHERE class != 'place'")
def get_special(self):
with self.conn.cursor() as cur:
cur.execute("""SELECT word_token, word, class as cls, type, operator
FROM word WHERE class != 'place'""")
result = set((tuple(row) for row in cur))
assert len(result) == cur.rowcount, "Word table has duplicates."
return result
def get_country(self):
with self.conn.cursor() as cur:
cur.execute("""SELECT country_code, word_token
FROM word WHERE country_code is not null""")
result = set((tuple(row) for row in cur))
assert len(result) == cur.rowcount, "Word table has duplicates."
return result
def get_postcodes(self):
with self.conn.cursor() as cur:
cur.execute("""SELECT word FROM word
WHERE class = 'place' and type = 'postcode'""")
return set((row[0] for row in cur))
def get_partial_words(self):
with self.conn.cursor() as cur:
cur.execute("""SELECT word_token, search_name_count FROM word
WHERE class is null and country_code is null
and not word_token like ' %'""")
return set((tuple(row) for row in cur))

591
test/python/tokenizer/test_legacy.py
View File

@ -1,591 +0,0 @@
# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2024 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Test for legacy tokenizer.
"""
import shutil
import re
import pytest
from nominatim_db.data.place_info import PlaceInfo
from nominatim_db.tokenizer import legacy_tokenizer
from nominatim_db.db import properties
from nominatim_db.errors import UsageError
from mock_legacy_word_table import MockLegacyWordTable
# Force use of legacy word table
@pytest.fixture
def word_table(temp_db_conn):
return MockLegacyWordTable(temp_db_conn)
@pytest.fixture
def test_config(project_env, tmp_path):
module_dir = tmp_path / 'module_src'
module_dir.mkdir()
(module_dir / 'nominatim.so').write_text('TEST nominatim.so')
project_env.lib_dir.module = module_dir
sqldir = tmp_path / 'sql'
sqldir.mkdir()
(sqldir / 'tokenizer').mkdir()
# Get the original SQL but replace make_standard_name to avoid module use.
init_sql = (project_env.lib_dir.sql / 'tokenizer' / 'legacy_tokenizer.sql').read_text()
for fn in ('transliteration', 'gettokenstring'):
init_sql = re.sub(f'CREATE OR REPLACE FUNCTION {fn}[^;]*;',
'', init_sql, re.DOTALL)
init_sql += """
CREATE OR REPLACE FUNCTION make_standard_name(name TEXT)
RETURNS TEXT AS $$ SELECT lower(name); $$ LANGUAGE SQL;
"""
# Also load util functions. Some are needed by the tokenizer.
init_sql += (project_env.lib_dir.sql / 'functions' / 'utils.sql').read_text()
(sqldir / 'tokenizer' / 'legacy_tokenizer.sql').write_text(init_sql)
(sqldir / 'words.sql').write_text("SELECT 'a'")
shutil.copy(str(project_env.lib_dir.sql / 'tokenizer' / 'legacy_tokenizer_tables.sql'),
str(sqldir / 'tokenizer' / 'legacy_tokenizer_tables.sql'))
project_env.lib_dir.sql = sqldir
project_env.lib_dir.data = sqldir
return project_env
@pytest.fixture
def tokenizer_factory(dsn, tmp_path, property_table):
(tmp_path / 'tokenizer').mkdir()
def _maker():
return legacy_tokenizer.create(dsn, tmp_path / 'tokenizer')
return _maker
@pytest.fixture
def tokenizer_setup(tokenizer_factory, test_config, monkeypatch, sql_preprocessor):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
@pytest.fixture
def analyzer(tokenizer_factory, test_config, monkeypatch, sql_preprocessor,
word_table, temp_db_with_extensions, tmp_path):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
monkeypatch.setenv('NOMINATIM_TERM_NORMALIZATION', ':: lower();')
tok = tokenizer_factory()
tok.init_new_db(test_config)
monkeypatch.undo()
with tok.name_analyzer() as analyzer:
yield analyzer
@pytest.fixture
def make_standard_name(temp_db_cursor):
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION make_standard_name(name TEXT)
RETURNS TEXT AS $$ SELECT '#' || lower(name) || '#'; $$ LANGUAGE SQL""")
@pytest.fixture
def create_postcode_id(temp_db_cursor):
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION create_postcode_id(postcode TEXT)
RETURNS BOOLEAN AS $$
INSERT INTO word (word_token, word, class, type)
VALUES (' ' || postcode, postcode, 'place', 'postcode')
RETURNING True;
$$ LANGUAGE SQL""")
def test_init_new(tokenizer_factory, test_config, monkeypatch,
temp_db_conn, sql_preprocessor):
monkeypatch.setenv('NOMINATIM_TERM_NORMALIZATION', 'xxvv')
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
assert properties.get_property(temp_db_conn, legacy_tokenizer.DBCFG_NORMALIZATION) == 'xxvv'
outfile = test_config.project_dir / 'module' / 'nominatim.so'
assert outfile.exists()
assert outfile.read_text() == 'TEST nominatim.so'
assert outfile.stat().st_mode == 33261
def test_init_module_load_failed(tokenizer_factory, test_config):
tok = tokenizer_factory()
with pytest.raises(UsageError):
tok.init_new_db(test_config)
def test_init_module_custom(tokenizer_factory, test_config,
monkeypatch, tmp_path, sql_preprocessor):
module_dir = (tmp_path / 'custom').resolve()
module_dir.mkdir()
(module_dir/ 'nominatim.so').write_text('CUSTOM nomiantim.so')
monkeypatch.setenv('NOMINATIM_DATABASE_MODULE_PATH', str(module_dir))
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
assert not (test_config.project_dir / 'module').exists()
def test_init_from_project(tokenizer_setup, tokenizer_factory, test_config):
tok = tokenizer_factory()
tok.init_from_project(test_config)
assert tok.normalization is not None
def test_update_sql_functions(sql_preprocessor, temp_db_conn,
tokenizer_factory, test_config, table_factory,
monkeypatch, temp_db_cursor):
monkeypatch.setenv('NOMINATIM_MAX_WORD_FREQUENCY', '1133')
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
monkeypatch.undo()
assert properties.get_property(temp_db_conn, legacy_tokenizer.DBCFG_MAXWORDFREQ) == '1133'
table_factory('test', 'txt TEXT')
func_file = test_config.lib_dir.sql / 'tokenizer' / 'legacy_tokenizer.sql'
func_file.write_text("""INSERT INTO test VALUES ('{{max_word_freq}}'),
('{{modulepath}}')""")
tok.update_sql_functions(test_config)
test_content = temp_db_cursor.row_set('SELECT * FROM test')
assert test_content == set((('1133', ), (str(test_config.project_dir / 'module'), )))
def test_finalize_import(tokenizer_factory, temp_db_conn,
temp_db_cursor, test_config, monkeypatch,
sql_preprocessor_cfg):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
func_file = test_config.lib_dir.sql / 'tokenizer' / 'legacy_tokenizer_indices.sql'
func_file.write_text("""CREATE FUNCTION test() RETURNS TEXT
AS $$ SELECT 'b'::text $$ LANGUAGE SQL""")
tok = tokenizer_factory()
tok.init_new_db(test_config)
tok.finalize_import(test_config)
temp_db_cursor.scalar('SELECT test()') == 'b'
def test_migrate_database(tokenizer_factory, test_config, temp_db_conn, monkeypatch):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.migrate_database(test_config)
assert properties.get_property(temp_db_conn, legacy_tokenizer.DBCFG_MAXWORDFREQ) is not None
assert properties.get_property(temp_db_conn, legacy_tokenizer.DBCFG_NORMALIZATION) is not None
outfile = test_config.project_dir / 'module' / 'nominatim.so'
assert outfile.exists()
assert outfile.read_text() == 'TEST nominatim.so'
assert outfile.stat().st_mode == 33261
def test_check_database(test_config, tokenizer_factory, monkeypatch,
temp_db_cursor, sql_preprocessor_cfg):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
assert tok.check_database(False) is None
def test_check_database_no_tokenizer(test_config, tokenizer_factory):
tok = tokenizer_factory()
assert tok.check_database(False) is not None
def test_check_database_bad_setup(test_config, tokenizer_factory, monkeypatch,
temp_db_cursor, sql_preprocessor_cfg):
monkeypatch.setattr(legacy_tokenizer, '_check_module', lambda m, c: None)
tok = tokenizer_factory()
tok.init_new_db(test_config)
# Inject a bad transliteration.
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION make_standard_name(name TEXT)
RETURNS TEXT AS $$ SELECT 'garbage'::text; $$ LANGUAGE SQL""")
assert tok.check_database(False) is not None
def test_update_statistics_reverse_only(word_table, tokenizer_factory, test_config):
tok = tokenizer_factory()
tok.update_statistics(test_config)
def test_update_statistics(word_table, table_factory, temp_db_cursor, tokenizer_factory, test_config):
word_table.add_full_word(1000, 'hello')
table_factory('search_name',
'place_id BIGINT, name_vector INT[]',
[(12, [1000])])
tok = tokenizer_factory()
tok.update_statistics(test_config)
assert temp_db_cursor.scalar("""SELECT count(*) FROM word
WHERE word_token like ' %' and
search_name_count > 0""") > 0
def test_update_word_tokens(tokenizer_factory):
tok = tokenizer_factory()
# This is a noop and should just pass.
tok.update_word_tokens()
def test_normalize(analyzer):
assert analyzer.normalize('TEsT') == 'test'
def test_update_postcodes_from_db_empty(analyzer, table_factory, word_table,
create_postcode_id):
table_factory('location_postcode', 'postcode TEXT',
content=(('1234',), ('12 34',), ('AB23',), ('1234',)))
analyzer.update_postcodes_from_db()
assert word_table.get_postcodes() == {'1234', '12 34', 'AB23'}
def test_update_postcodes_from_db_add_and_remove(analyzer, table_factory, word_table,
create_postcode_id):
table_factory('location_postcode', 'postcode TEXT',
content=(('1234',), ('45BC', ), ('XX45', )))
word_table.add_postcode(' 1234', '1234')
word_table.add_postcode(' 5678', '5678')
analyzer.update_postcodes_from_db()
assert word_table.get_postcodes() == {'1234', '45BC', 'XX45'}
def test_update_special_phrase_empty_table(analyzer, word_table, make_standard_name):
analyzer.update_special_phrases([
("König bei", "amenity", "royal", "near"),
("Könige", "amenity", "royal", "-"),
("könige", "amenity", "royal", "-"),
("strasse", "highway", "primary", "in")
], True)
assert word_table.get_special() \
== set(((' #könig bei#', 'könig bei', 'amenity', 'royal', 'near'),
(' #könige#', 'könige', 'amenity', 'royal', None),
(' #strasse#', 'strasse', 'highway', 'primary', 'in')))
def test_update_special_phrase_delete_all(analyzer, word_table, make_standard_name):
word_table.add_special(' #foo#', 'foo', 'amenity', 'prison', 'in')
word_table.add_special(' #bar#', 'bar', 'highway', 'road', None)
assert word_table.count_special() == 2
analyzer.update_special_phrases([], True)
assert word_table.count_special() == 0
def test_update_special_phrases_no_replace(analyzer, word_table, make_standard_name):
word_table.add_special(' #foo#', 'foo', 'amenity', 'prison', 'in')
word_table.add_special(' #bar#', 'bar', 'highway', 'road', None)
assert word_table.count_special() == 2
analyzer.update_special_phrases([], False)
assert word_table.count_special() == 2
def test_update_special_phrase_modify(analyzer, word_table, make_standard_name):
word_table.add_special(' #foo#', 'foo', 'amenity', 'prison', 'in')
word_table.add_special(' #bar#', 'bar', 'highway', 'road', None)
assert word_table.count_special() == 2
analyzer.update_special_phrases([
('prison', 'amenity', 'prison', 'in'),
('bar', 'highway', 'road', '-'),
('garden', 'leisure', 'garden', 'near')
], True)
assert word_table.get_special() \
== set(((' #prison#', 'prison', 'amenity', 'prison', 'in'),
(' #bar#', 'bar', 'highway', 'road', None),
(' #garden#', 'garden', 'leisure', 'garden', 'near')))
def test_add_country_names(analyzer, word_table, make_standard_name):
analyzer.add_country_names('de', {'name': 'Germany',
'name:de': 'Deutschland',
'short_name': 'germany'})
assert word_table.get_country() \
== {('de', ' #germany#'),
('de', ' #deutschland#')}
def test_add_more_country_names(analyzer, word_table, make_standard_name):
word_table.add_country('fr', ' #france#')
word_table.add_country('it', ' #italy#')
word_table.add_country('it', ' #itala#')
analyzer.add_country_names('it', {'name': 'Italy', 'ref': 'IT'})
assert word_table.get_country() \
== {('fr', ' #france#'),
('it', ' #italy#'),
('it', ' #itala#'),
('it', ' #it#')}
@pytest.mark.parametrize('pcode', ['12345', 'AB 123', '34-345'])
def test_process_place_postcode(analyzer, create_postcode_id, word_table, pcode):
analyzer.process_place(PlaceInfo({'address': {'postcode' : pcode}}))
assert word_table.get_postcodes() == {pcode, }
@pytest.mark.parametrize('pcode', ['12:23', 'ab;cd;f', '123;836'])
def test_process_place_bad_postcode(analyzer, create_postcode_id, word_table, pcode):
analyzer.process_place(PlaceInfo({'address': {'postcode' : pcode}}))
assert not word_table.get_postcodes()
class TestHousenumberName:
@staticmethod
@pytest.fixture(autouse=True)
def setup_create_housenumbers(temp_db_cursor):
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION create_housenumbers(
housenumbers TEXT[],
OUT tokens TEXT, OUT normtext TEXT)
AS $$
SELECT housenumbers::TEXT, array_to_string(housenumbers, ';')
$$ LANGUAGE SQL""")
@staticmethod
@pytest.mark.parametrize('hnr', ['123a', '1', '101'])
def test_process_place_housenumbers_simple(analyzer, hnr):
info = analyzer.process_place(PlaceInfo({'address': {'housenumber' : hnr}}))
assert info['hnr'] == hnr
assert info['hnr_tokens'].startswith("{")
@staticmethod
def test_process_place_housenumbers_lists(analyzer):
info = analyzer.process_place(PlaceInfo({'address': {'conscriptionnumber' : '1; 2;3'}}))
assert set(info['hnr'].split(';')) == set(('1', '2', '3'))
@staticmethod
def test_process_place_housenumbers_duplicates(analyzer):
info = analyzer.process_place(PlaceInfo({'address': {'housenumber' : '134',
'conscriptionnumber' : '134',
'streetnumber' : '99a'}}))
assert set(info['hnr'].split(';')) == set(('134', '99a'))
class TestPlaceNames:
@pytest.fixture(autouse=True)
def setup(self, analyzer):
self.analyzer = analyzer
def expect_name_terms(self, info, *expected_terms):
tokens = self.analyzer.get_word_token_info(list(expected_terms))
for token in tokens:
assert token[2] is not None, "No token for {0}".format(token)
assert eval(info['names']) == set((t[2] for t in tokens)),\
f"Expected: {tokens}\nGot: {info['names']}"
def process_named_place(self, names):
return self.analyzer.process_place(PlaceInfo({'name': names}))
def test_simple_names(self):
info = self.process_named_place({'name': 'Soft bAr', 'ref': '34'})
self.expect_name_terms(info, '#Soft bAr', '#34', 'Soft', 'bAr', '34')
@pytest.mark.parametrize('sep', [',' , ';'])
def test_names_with_separator(self, sep):
info = self.process_named_place({'name': sep.join(('New York', 'Big Apple'))})
self.expect_name_terms(info, '#New York', '#Big Apple',
'new', 'york', 'big', 'apple')
def test_full_names_with_bracket(self):
info = self.process_named_place({'name': 'Houseboat (left)'})
self.expect_name_terms(info, '#Houseboat (left)', '#Houseboat',
'houseboat', '(left)')
def test_country_name(self, word_table):
place = PlaceInfo({'name' : {'name': 'Norge'},
'country_code': 'no',
'rank_address': 4,
'class': 'boundary',
'type': 'administrative'})
info = self.analyzer.process_place(place)
self.expect_name_terms(info, '#norge', 'norge')
assert word_table.get_country() == {('no', ' norge')}
class TestPlaceAddress:
@pytest.fixture(autouse=True)
def setup(self, analyzer):
self.analyzer = analyzer
@pytest.fixture
def getorcreate_hnr_id(self, temp_db_cursor):
temp_db_cursor.execute("""CREATE SEQUENCE seq_hnr start 1;
CREATE OR REPLACE FUNCTION getorcreate_housenumber_id(lookup_word TEXT)
RETURNS INTEGER AS $$
SELECT -nextval('seq_hnr')::INTEGER; $$ LANGUAGE SQL""")
def process_address(self, **kwargs):
return self.analyzer.process_place(PlaceInfo({'address': kwargs}))
def name_token_set(self, *expected_terms):
tokens = self.analyzer.get_word_token_info(list(expected_terms))
for token in tokens:
assert token[2] is not None, "No token for {0}".format(token)
return set((t[2] for t in tokens))
@pytest.mark.parametrize('pcode', ['12345', 'AB 123', '34-345'])
def test_process_place_postcode(self, word_table, pcode):
self.process_address(postcode=pcode)
assert word_table.get_postcodes() == {pcode, }
@pytest.mark.parametrize('pcode', ['12:23', 'ab;cd;f', '123;836'])
def test_process_place_bad_postcode(self, word_table, pcode):
self.process_address(postcode=pcode)
assert not word_table.get_postcodes()
@pytest.mark.parametrize('hnr', ['123a', '0', '101'])
def test_process_place_housenumbers_simple(self, hnr, getorcreate_hnr_id):
info = self.process_address(housenumber=hnr)
assert info['hnr'] == hnr.lower()
assert info['hnr_tokens'] == "{-1}"
def test_process_place_housenumbers_lists(self, getorcreate_hnr_id):
info = self.process_address(conscriptionnumber='1; 2;3')
assert set(info['hnr'].split(';')) == set(('1', '2', '3'))
assert info['hnr_tokens'] == "{-1,-2,-3}"
def test_process_place_housenumbers_duplicates(self, getorcreate_hnr_id):
info = self.process_address(housenumber='134',
conscriptionnumber='134',
streetnumber='99A')
assert set(info['hnr'].split(';')) == set(('134', '99a'))
assert info['hnr_tokens'] == "{-1,-2}"
def test_process_place_street(self):
# legacy tokenizer only indexes known names
self.analyzer.process_place(PlaceInfo({'name': {'name' : 'Grand Road'}}))
info = self.process_address(street='Grand Road')
assert eval(info['street']) == self.name_token_set('#Grand Road')
def test_process_place_street_empty(self):
info = self.process_address(street='🜵')
assert info['street'] == '{}'
def test_process_place_place(self):
self.analyzer.process_place(PlaceInfo({'name': {'name' : 'Honu Lulu'}}))
info = self.process_address(place='Honu Lulu')
assert eval(info['place_search']) == self.name_token_set('#Honu Lulu',
'Honu', 'Lulu')
assert eval(info['place_match']) == self.name_token_set('#Honu Lulu')
def test_process_place_place_empty(self):
info = self.process_address(place='🜵')
assert 'place' not in info
def test_process_place_address_terms(self):
for name in ('Zwickau', 'Haupstraße', 'Sachsen'):
self.analyzer.process_place(PlaceInfo({'name': {'name' : name}}))
info = self.process_address(country='de', city='Zwickau', state='Sachsen',
suburb='Zwickau', street='Hauptstr',
full='right behind the church')
city = self.name_token_set('ZWICKAU')
state = self.name_token_set('SACHSEN')
print(info)
result = {k: eval(v[0]) for k,v in info['addr'].items()}
assert result == {'city': city, 'suburb': city, 'state': state}
def test_process_place_address_terms_empty(self):
info = self.process_address(country='de', city=' ', street='Hauptstr',
full='right behind the church')
assert 'addr' not in info

26
test/python/tools/test_migration.py
View File

@ -14,8 +14,6 @@ from nominatim_db.errors import UsageError
from nominatim_db.db.connection import server_version_tuple
import nominatim_db.version
from mock_legacy_word_table import MockLegacyWordTable
class DummyTokenizer:
def update_sql_functions(self, config):
@ -28,10 +26,6 @@ def postprocess_mock(monkeypatch):
monkeypatch.setattr(migration.tokenizer_factory, 'get_tokenizer_for_db',
lambda *args: DummyTokenizer())
@pytest.fixture
def legacy_word_table(temp_db_conn):
return MockLegacyWordTable(temp_db_conn)
def test_no_migration_old_versions(temp_db_with_extensions, table_factory, def_config):
table_factory('country_name', 'name HSTORE, country_code TEXT')
@ -145,26 +139,6 @@ def test_add_nominatim_property_table_repeat(temp_db_conn, temp_db_cursor,
assert temp_db_cursor.table_exists('nominatim_properties')
def test_change_housenumber_transliteration(temp_db_conn, temp_db_cursor,
legacy_word_table, placex_table):
placex_table.add(housenumber='3A')
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION make_standard_name(name TEXT)
RETURNS TEXT AS $$ SELECT lower(name) $$ LANGUAGE SQL """)
temp_db_cursor.execute("""CREATE OR REPLACE FUNCTION getorcreate_housenumber_id(lookup_word TEXT)
RETURNS INTEGER AS $$ SELECT 4325 $$ LANGUAGE SQL """)
migration.change_housenumber_transliteration(temp_db_conn)
temp_db_conn.commit()
assert temp_db_cursor.scalar('SELECT housenumber from placex') == '3a'
migration.change_housenumber_transliteration(temp_db_conn)
temp_db_conn.commit()
assert temp_db_cursor.scalar('SELECT housenumber from placex') == '3a'
def test_switch_placenode_geometry_index(temp_db_conn, temp_db_cursor, placex_table):
temp_db_cursor.execute("""CREATE INDEX idx_placex_adminname
ON placex (place_id)""")