Housenumber fields with lots of text are likely bad data. So is
data with many changes from letter to digit. Exclude them from adding
optional spaces.
RE_NON_DIGIT = re.compile('[^0-9]')
RE_DIGIT_ALPHA = re.compile(r'(\d)\s*([^\d\s␣])')
RE_ALPHA_DIGIT = re.compile(r'([^\s\d␣])\s*(\d)')
RE_NON_DIGIT = re.compile('[^0-9]')
RE_DIGIT_ALPHA = re.compile(r'(\d)\s*([^\d\s␣])')
RE_ALPHA_DIGIT = re.compile(r'([^\s\d␣])\s*(\d)')
+RE_NAMED_PART = re.compile(r'[a-z]{4}')
### Configuration section
### Configuration section
-def configure(rules, normalization_rules):
+def configure(rules, normalization_rules): # pylint: disable=W0613
""" All behaviour is currently hard-coded.
"""
return None
### Analysis section
""" All behaviour is currently hard-coded.
"""
return None
### Analysis section
-def create(normalizer, transliterator, config):
+def create(normalizer, transliterator, config): # pylint: disable=W0613
""" Create a new token analysis instance for this module.
"""
return HousenumberTokenAnalysis(normalizer, transliterator)
""" Create a new token analysis instance for this module.
"""
return HousenumberTokenAnalysis(normalizer, transliterator)
return name
norm = self.trans.transliterate(self.norm.transliterate(name))
return name
norm = self.trans.transliterate(self.norm.transliterate(name))
- norm = RE_DIGIT_ALPHA.sub(r'\1␣\2', norm)
- norm = RE_ALPHA_DIGIT.sub(r'\1␣\2', norm)
+ # If there is a significant non-numeric part, use as is.
+ if RE_NAMED_PART.search(norm) is None:
+ # Otherwise add optional spaces between digits and letters.
+ (norm_opt, cnt1) = RE_DIGIT_ALPHA.subn(r'\1␣\2', norm)
+ (norm_opt, cnt2) = RE_ALPHA_DIGIT.subn(r'\1␣\2', norm_opt)
+ # Avoid creating too many variants per number.
+ if cnt1 + cnt2 <= 4:
+ return norm_opt