change confidence to %

lyric_search_new/constructors.py

@@ -9,7 +9,7 @@ class LyricsResult:
     song: str
     src: str
     lyrics: str
-    confidence: float
+    confidence: int
     time: float = 0.00
 
     def dict(self):

lyric_search_new/sources/cache.py

@@ -29,7 +29,7 @@ class Cache:
         self.sqlite_exts: list[str] = ['/usr/local/lib/python3.11/dist-packages/spellfix1.cpython-311-x86_64-linux-gnu.so']
         self.label: str = "Cache"
 
-    def get_matched(self, sqlite_rows: list[sqlite3.Row], matched_candidate: tuple, confidence: float) -> Optional[LyricsResult]:
+    def get_matched(self, sqlite_rows: list[sqlite3.Row], matched_candidate: tuple, confidence: int) -> Optional[LyricsResult]:
         """Get Matched Result"""
         matched_id: int = matched_candidate[0]
         for row in sqlite_rows:
@@ -148,7 +148,7 @@ class Cache:
                             best_match: tuple|None = matcher.find_best_match(input_track=input_track,
                                                             candidate_tracks=result_tracks)
                         else:
-                            best_match = (result_tracks[0], float(1))
+                            best_match = (result_tracks[0], 100)
                         if not best_match:
                             return None
                         (candidate, confidence) = best_match

lyric_search_new/utils.py

@@ -2,6 +2,7 @@
 
 from difflib import SequenceMatcher
 from typing import List, Optional, Tuple
+import logging
 import regex
 
 class TrackMatcher:
@@ -28,6 +29,8 @@ class TrackMatcher:
             Optional[Tuple[int, str, float]]: Tuple of (best matching track, similarity score)
                                        or None if no good match found
         """
+
+
         if not input_track or not candidate_tracks:
             return None
 
@@ -53,7 +56,7 @@ class TrackMatcher:
                 best_match = candidate
 
         # Return the match only if it meets the threshold
-        return (best_match, round(best_score, 2)) if best_score >= self.threshold else None
+        return (best_match, round(best_score *100)) if best_score >= self.threshold else None
 
     def _normalize_string(self, text: str) -> str:
         """