48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
"""
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Shared text normalization utilities for fuzzy matching.
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Used by cache key generation, cache search, and candidate selection scoring.
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"""
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import re
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import unicodedata
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# Punctuation to strip for fuzzy matching (ASCII + fullwidth + CJK brackets/symbols)
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_PUNCT_RE = re.compile(
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r"[~!@#$%^&*()_+\-=\[\]{}|;:'\",.<>?/\\`"
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r"～！＠＃＄％＾＆＊（）＿＋－＝【】｛｝｜；：＇＂，。＜＞？／＼｀"
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r"「」『』《》〈〉〔〕·•‥…—–]"
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)
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_SPACE_RE = re.compile(r"\s+")
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# feat./ft./featuring and everything after (case-insensitive, word boundary)
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_FEAT_RE = re.compile(r"\s*(?:\bfeat\.?\b|\bft\.?\b|\bfeaturing\b).*", re.IGNORECASE)
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# Multi-artist separators: /, &, ×, x (surrounded by spaces), ;, 、, vs.
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_ARTIST_SEP_RE = re.compile(r"\s*(?:[/&;×、]|\bvs\.?\b|\bx\b)\s*", re.IGNORECASE)
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def normalize_for_match(s: str) -> str:
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"""Normalize a string for fuzzy comparison.
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Lowercases, NFKC-normalizes (fullwidth → halfwidth), strips punctuation,
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and collapses whitespace.
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"""
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s = unicodedata.normalize("NFKC", s).lower()
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s = _FEAT_RE.sub("", s)
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s = _PUNCT_RE.sub(" ", s)
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s = _SPACE_RE.sub(" ", s).strip()
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return s
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def normalize_artist(s: str) -> str:
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"""Normalize an artist string: split by separators, normalize each, sort.
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Splits first (on /, &, ;, ×, 、, vs., x), then strips feat./ft./featuring
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from each part individually, so 'A feat. C / B' → ['a', 'b'] not just ['a'].
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"""
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s = unicodedata.normalize("NFKC", s).lower()
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parts = _ARTIST_SEP_RE.split(s)
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normed = sorted(
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{normalize_for_match(p) for p in parts if _FEAT_RE.sub("", p).strip()}
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)
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return "\0".join(normed) if normed else normalize_for_match(s)
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