def configure(rules, normalization_rules):
""" Extract and preprocess the configuration for this module.
"""
- rules = rules.get('variants')
+ config = {}
+
+ config['replacements'], config['chars'] = _get_variant_config(rules.get('variants'),
+ normalization_rules)
+ config['variant_only'] = rules.get('mode', '') == 'variant-only'
+
+ return config
+
+
+def _get_variant_config(rules, normalization_rules):
+ """ Convert the variant definition from the configuration into
+ replacement sets.
+ """
immediate = defaultdict(list)
chars = set()
immediate[variant.source].append(replstr)
chars.update(variant.source)
- return {'replacements': list(immediate.items()),
- 'chars': ''.join(chars)}
+ return list(immediate.items()), ''.join(chars)
class _VariantMaker:
decompose = parts[1] is None
src_terms = [self._parse_variant_word(t) for t in parts[0].split(',')]
- repl_terms = (self.norm.transliterate(t.strip()) for t in parts[3].split(','))
+ repl_terms = (self.norm.transliterate(t).strip() for t in parts[3].split(','))
# If the source should be kept, add a 1:1 replacement
if parts[2] == '-':
match = re.fullmatch(r'([~^]?)([^~$^]*)([~$]?)', name)
if match is None or (match.group(1) == '~' and match.group(3) == '~'):
raise UsageError("Invalid variant word descriptor '{}'".format(name))
- norm_name = self.norm.transliterate(match.group(2))
+ norm_name = self.norm.transliterate(match.group(2)).strip()
if not norm_name:
return None
### Analysis section
-def create(norm_rules, trans_rules, config):
+def create(transliterator, config):
""" Create a new token analysis instance for this module.
"""
- return GenericTokenAnalysis(norm_rules, trans_rules, config)
+ return GenericTokenAnalysis(transliterator, config)
class GenericTokenAnalysis:
and provides the functions to apply the transformations.
"""
- def __init__(self, norm_rules, trans_rules, config):
- self.normalizer = Transliterator.createFromRules("icu_normalization",
- norm_rules)
- self.to_ascii = Transliterator.createFromRules("icu_to_ascii",
- trans_rules +
- ";[:Space:]+ > ' '")
- self.search = Transliterator.createFromRules("icu_search",
- norm_rules + trans_rules)
+ def __init__(self, to_ascii, config):
+ self.to_ascii = to_ascii
+ self.variant_only = config['variant_only']
# Set up datrie
- self.replacements = datrie.Trie(config['chars'])
- for src, repllist in config['replacements']:
- self.replacements[src] = repllist
-
+ if config['replacements']:
+ self.replacements = datrie.Trie(config['chars'])
+ for src, repllist in config['replacements']:
+ self.replacements[src] = repllist
+ else:
+ self.replacements = None
- def get_normalized(self, name):
- """ Normalize the given name, i.e. remove all elements not relevant
- for search.
- """
- return self.normalizer.transliterate(name).strip()
def get_variants_ascii(self, norm_name):
""" Compute the spelling variants for the given normalized name
partials = ['']
startpos = 0
- pos = 0
- force_space = False
- while pos < len(baseform):
- full, repl = self.replacements.longest_prefix_item(baseform[pos:],
- (None, None))
- if full is not None:
- done = baseform[startpos:pos]
- partials = [v + done + r
- for v, r in itertools.product(partials, repl)
- if not force_space or r.startswith(' ')]
- if len(partials) > 128:
- # If too many variants are produced, they are unlikely
- # to be helpful. Only use the original term.
- startpos = 0
- break
- startpos = pos + len(full)
- if full[-1] == ' ':
- startpos -= 1
- force_space = True
- pos = startpos
- else:
- pos += 1
- force_space = False
+ if self.replacements is not None:
+ pos = 0
+ force_space = False
+ while pos < len(baseform):
+ full, repl = self.replacements.longest_prefix_item(baseform[pos:],
+ (None, None))
+ if full is not None:
+ done = baseform[startpos:pos]
+ partials = [v + done + r
+ for v, r in itertools.product(partials, repl)
+ if not force_space or r.startswith(' ')]
+ if len(partials) > 128:
+ # If too many variants are produced, they are unlikely
+ # to be helpful. Only use the original term.
+ startpos = 0
+ break
+ startpos = pos + len(full)
+ if full[-1] == ' ':
+ startpos -= 1
+ force_space = True
+ pos = startpos
+ else:
+ pos += 1
+ force_space = False
# No variants detected? Fast return.
if startpos == 0:
+ if self.variant_only:
+ return []
+
trans_name = self.to_ascii.transliterate(norm_name).strip()
return [trans_name] if trans_name else []
- return self._compute_result_set(partials, baseform[startpos:])
+ return self._compute_result_set(partials, baseform[startpos:],
+ norm_name if self.variant_only else '')
- def _compute_result_set(self, partials, prefix):
+ def _compute_result_set(self, partials, prefix, exclude):
results = set()
for variant in partials:
- vname = variant + prefix
- trans_name = self.to_ascii.transliterate(vname[1:-1]).strip()
- if trans_name:
- results.add(trans_name)
+ vname = (variant + prefix)[1:-1].strip()
+ if vname != exclude:
+ trans_name = self.to_ascii.transliterate(vname).strip()
+ if trans_name:
+ results.add(trans_name)
return list(results)
-
-
- def get_search_normalized(self, name):
- """ Return the normalized version of the name (including transliteration)
- to be applied at search time.
- """
- return self.search.transliterate(' ' + name + ' ').strip()
projects / nominatim.git / blobdiff