91 lines
3.5 KiB
Python
91 lines
3.5 KiB
Python
# -*- coding: utf-8 -*-
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from geodata.text import _normalize
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from geodata.text.tokenize import tokenize_raw
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from geodata.text.token_types import token_types
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from geodata.encoding import safe_decode
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# String options
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NORMALIZE_STRING_LATIN_ASCII = _normalize.NORMALIZE_STRING_LATIN_ASCII
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NORMALIZE_STRING_TRANSLITERATE = _normalize.NORMALIZE_STRING_TRANSLITERATE
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NORMALIZE_STRING_STRIP_ACCENTS = _normalize.NORMALIZE_STRING_STRIP_ACCENTS
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NORMALIZE_STRING_DECOMPOSE = _normalize.NORMALIZE_STRING_DECOMPOSE
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NORMALIZE_STRING_LOWERCASE = _normalize.NORMALIZE_STRING_LOWERCASE
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NORMALIZE_STRING_TRIM = _normalize.NORMALIZE_STRING_TRIM
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NORMALIZE_STRING_REPLACE_HYPHENS = _normalize.NORMALIZE_STRING_REPLACE_HYPHENS
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DEFAULT_STRING_OPTIONS = NORMALIZE_STRING_LATIN_ASCII | \
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NORMALIZE_STRING_DECOMPOSE | \
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NORMALIZE_STRING_TRIM | \
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NORMALIZE_STRING_REPLACE_HYPHENS | \
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NORMALIZE_STRING_STRIP_ACCENTS | \
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NORMALIZE_STRING_LOWERCASE
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# Token options
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NORMALIZE_TOKEN_REPLACE_HYPHENS = _normalize.NORMALIZE_TOKEN_REPLACE_HYPHENS
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NORMALIZE_TOKEN_DELETE_HYPHENS = _normalize.NORMALIZE_TOKEN_DELETE_HYPHENS
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NORMALIZE_TOKEN_DELETE_FINAL_PERIOD = _normalize.NORMALIZE_TOKEN_DELETE_FINAL_PERIOD
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NORMALIZE_TOKEN_DELETE_ACRONYM_PERIODS = _normalize.NORMALIZE_TOKEN_DELETE_ACRONYM_PERIODS
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NORMALIZE_TOKEN_DROP_ENGLISH_POSSESSIVES = _normalize.NORMALIZE_TOKEN_DROP_ENGLISH_POSSESSIVES
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NORMALIZE_TOKEN_DELETE_OTHER_APOSTROPHE = _normalize.NORMALIZE_TOKEN_DELETE_OTHER_APOSTROPHE
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NORMALIZE_TOKEN_SPLIT_ALPHA_FROM_NUMERIC = _normalize.NORMALIZE_TOKEN_SPLIT_ALPHA_FROM_NUMERIC
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NORMALIZE_TOKEN_REPLACE_DIGITS = _normalize.NORMALIZE_TOKEN_REPLACE_DIGITS
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DEFAULT_TOKEN_OPTIONS = NORMALIZE_TOKEN_REPLACE_HYPHENS | \
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NORMALIZE_TOKEN_DELETE_FINAL_PERIOD | \
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NORMALIZE_TOKEN_DELETE_ACRONYM_PERIODS | \
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NORMALIZE_TOKEN_DROP_ENGLISH_POSSESSIVES | \
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NORMALIZE_TOKEN_DELETE_OTHER_APOSTROPHE | \
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NORMALIZE_TOKEN_REPLACE_DIGITS
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def remove_parens(tokens):
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new_tokens = []
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open_parens = 0
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for t, c in tokens:
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if c == token_types.PUNCT_OPEN:
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open_parens += 1
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elif c == token_types.PUNCT_CLOSE:
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if open_parens > 0:
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open_parens -= 1
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elif open_parens <= 0:
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new_tokens.append((t, c))
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return new_tokens
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def normalize_string(s, string_options=DEFAULT_STRING_OPTIONS):
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s = safe_decode(s)
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if string_options & _normalize.NORMALIZE_STRING_LATIN_ASCII:
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normalized = _normalize.normalize_string_latin(s, string_options)
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else:
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normalized = _normalize.normalize_string_utf8(s, string_options)
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return normalized
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def normalized_tokens(s, string_options=DEFAULT_STRING_OPTIONS,
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token_options=DEFAULT_TOKEN_OPTIONS,
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strip_parentheticals=True):
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'''
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Normalizes a string, tokenizes, and normalizes each token
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with string and token-level options.
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This version only uses libpostal's deterministic normalizations
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i.e. methods with a single output. The string tree version will
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return multiple normalized strings, each with tokens.
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Usage:
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normalized_tokens(u'St.-Barthélemy')
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'''
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normalized = normalize_string(s, string_options=string_options)
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# Tuples of (offset, len, type)
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raw_tokens = tokenize_raw(normalized)
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tokens = [(_normalize.normalize_token(normalized, t, token_options),
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token_types.from_id(t[-1])) for t in raw_tokens]
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if strip_parentheticals:
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return remove_parens(tokens)
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else:
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return tokens
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