feat: evaluate fetch results with "confidence"

lrx_cli/normalize.py

@@ -0,0 +1,47 @@
+"""
+Shared text normalization utilities for fuzzy matching.
+
+Used by cache key generation, cache search, and candidate selection scoring.
+"""
+
+import re
+import unicodedata
+
+# Punctuation to strip for fuzzy matching (ASCII + fullwidth + CJK brackets/symbols)
+_PUNCT_RE = re.compile(
+    r"[~!@#$%^&*()_+\-=\[\]{}|;:'\",.<>?/\\`"
+    r"～！＠＃＄％＾＆＊（）＿＋－＝【】｛｝｜；：＇＂，。＜＞？／＼｀"
+    r"「」『』《》〈〉〔〕·•‥…—–]"
+)
+_SPACE_RE = re.compile(r"\s+")
+# feat./ft./featuring and everything after (case-insensitive, word boundary)
+_FEAT_RE = re.compile(r"\s*(?:\bfeat\.?\b|\bft\.?\b|\bfeaturing\b).*", re.IGNORECASE)
+# Multi-artist separators: /, &, ×, x (surrounded by spaces), ;, 、, vs.
+_ARTIST_SEP_RE = re.compile(r"\s*(?:[/&;×、]|\bvs\.?\b|\bx\b)\s*", re.IGNORECASE)
+
+
+def normalize_for_match(s: str) -> str:
+    """Normalize a string for fuzzy comparison.
+
+    Lowercases, NFKC-normalizes (fullwidth → halfwidth), strips punctuation,
+    and collapses whitespace.
+    """
+    s = unicodedata.normalize("NFKC", s).lower()
+    s = _FEAT_RE.sub("", s)
+    s = _PUNCT_RE.sub(" ", s)
+    s = _SPACE_RE.sub(" ", s).strip()
+    return s
+
+
+def normalize_artist(s: str) -> str:
+    """Normalize an artist string: split by separators, normalize each, sort.
+
+    Splits first (on /, &, ;, ×, 、, vs., x), then strips feat./ft./featuring
+    from each part individually, so 'A feat. C / B' → ['a', 'b'] not just ['a'].
+    """
+    s = unicodedata.normalize("NFKC", s).lower()
+    parts = _ARTIST_SEP_RE.split(s)
+    normed = sorted(
+        {normalize_for_match(p) for p in parts if _FEAT_RE.sub("", p).strip()}
+    )
+    return "\0".join(normed) if normed else normalize_for_match(s)