Fix popularity stats and enhance path parsing for download-based analysis
- Fix database format compatibility for popularity functions - Change popularity metrics from uploads to downloads (tracks user demand) - Implement enhanced left-to-right path parsing algorithm - Add support for diverse library structures (/music/, \Artists\, etc.) - Improve artist name removal from album titles - Update UI labels to reflect download-based popularity
This commit is contained in:
Alec
+173
-94
@@ -643,12 +643,12 @@ class MainWindow(QMainWindow):
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popularitySplitter = QSplitter(Qt.Horizontal)
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# Create artists section
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artistsGroup = QGroupBox("Top Artists by Uploads")
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artistsGroup = QGroupBox("Top Artists by Downloads")
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artistsLayout = QVBoxLayout()
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self.artistsTable = QTableWidget()
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self.artistsTable.setColumnCount(3)
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self.artistsTable.setHorizontalHeaderLabels(["Artist", "Uploads", "Total Data"])
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self.artistsTable.setHorizontalHeaderLabels(["Artist", "Downloads", "Total Data"])
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self.artistsTable.horizontalHeader().setStretchLastSection(True)
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self.artistsTable.setAlternatingRowColors(True)
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self.artistsTable.setSortingEnabled(True)
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@@ -664,12 +664,12 @@ class MainWindow(QMainWindow):
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popularitySplitter.addWidget(artistsGroup)
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# Create albums section
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albumsGroup = QGroupBox("Top Albums by Uploads")
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albumsGroup = QGroupBox("Top Albums by Downloads")
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albumsLayout = QVBoxLayout()
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self.albumsTable = QTableWidget()
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self.albumsTable.setColumnCount(4)
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self.albumsTable.setHorizontalHeaderLabels(["Artist", "Album", "Uploads", "Total Data"])
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self.albumsTable.setHorizontalHeaderLabels(["Artist", "Album", "Downloads", "Total Data"])
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self.albumsTable.horizontalHeader().setStretchLastSection(True)
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self.albumsTable.setAlternatingRowColors(True)
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self.albumsTable.setSortingEnabled(True)
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@@ -1011,7 +1011,7 @@ class MainWindow(QMainWindow):
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# Check if we have data and good format compatibility
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if not artist_stats and not album_stats:
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self.showPopularityError("No successful upload transfers found.", format_info)
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self.showPopularityError("No successful download transfers found.", format_info)
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return
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elif format_info['match_percentage'] < 50:
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self.showPopularityWarning(format_info)
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@@ -1060,8 +1060,8 @@ class MainWindow(QMainWindow):
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bars = ax.barh(range(len(truncated_artists)), counts)
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ax.set_yticks(range(len(truncated_artists)))
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ax.set_yticklabels(truncated_artists, fontsize=8)
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ax.set_xlabel('Uploads')
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ax.set_title(f'Top {len(artists)} Artists by Uploads')
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ax.set_xlabel('Downloads')
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ax.set_title(f'Top {len(artists)} Artists by Downloads')
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# Add value labels on bars
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for i, (bar, count) in enumerate(zip(bars, counts)):
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@@ -1118,8 +1118,8 @@ class MainWindow(QMainWindow):
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bars = ax.barh(range(len(truncated_labels)), counts)
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ax.set_yticks(range(len(truncated_labels)))
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ax.set_yticklabels(truncated_labels, fontsize=7)
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ax.set_xlabel('Uploads')
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ax.set_title(f'Top {len(album_labels)} Albums by Uploads')
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ax.set_xlabel('Downloads')
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ax.set_title(f'Top {len(album_labels)} Albums by Downloads')
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# Add value labels on bars
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for i, (bar, count) in enumerate(zip(bars, counts)):
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@@ -1151,7 +1151,7 @@ class MainWindow(QMainWindow):
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for i, bar in enumerate(bars):
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if bar.contains(event)[0]:
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# Show tooltip with full artist name and count
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tooltip_text = f"{artists[i]}\n{counts[i]} uploads"
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tooltip_text = f"{artists[i]}\n{counts[i]} downloads"
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self.artistsCanvas.setToolTip(tooltip_text)
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return
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@@ -1167,7 +1167,7 @@ class MainWindow(QMainWindow):
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for i, bar in enumerate(bars):
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if bar.contains(event)[0]:
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# Show tooltip with full album name and count
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tooltip_text = f"{album_labels[i]}\n{counts[i]} uploads"
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tooltip_text = f"{album_labels[i]}\n{counts[i]} downloads"
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self.albumsCanvas.setToolTip(tooltip_text)
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return
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@@ -1202,25 +1202,29 @@ class MainWindow(QMainWindow):
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{message}
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How it works:
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• Analyzes successful upload transfers only
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• Extracts artist and album from file paths
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• Expected format: /path/Music/Artist/Album/Track.ext
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• Analyzes successful download transfers (what users want)
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• Smart left-to-right path parsing
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• Detects media folders (/music/, \\Artists\\, etc.)
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• Removes artist name prefixes from album titles
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Library Analysis:
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• Total files analyzed: {format_info['total_files']}
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• Compatible files: {format_info['matching_files']} ({format_info['match_percentage']:.1f}%)
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Example paths from your library:"""
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Parsing Examples:"""
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if format_info['sample_paths']:
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explanation_text += "\n\n" + "\n".join(f"• {path}" for path in format_info['sample_paths'][:5])
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if format_info.get('format_examples'):
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explanation_text += "\n\n" + "\n".join(
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f"• {ex['artist']} → {ex['album']}"
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for ex in format_info['format_examples'][:5]
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)
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if format_info['match_percentage'] < 50:
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explanation_text += f"""
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⚠️ Low compatibility detected ({format_info['match_percentage']:.1f}%)
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Your music library structure may not match the expected format.
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Consider organizing music files as: /Music/Artist/Album/Track.ext"""
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The smart parser couldn't extract artist/album info from most files.
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Check if your files are in media folders like /music/ or /audiobooks/"""
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ax.text(0.05, 0.95, explanation_text, transform=ax.transAxes,
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fontsize=9, verticalalignment='top', fontfamily='monospace',
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@@ -1229,22 +1233,31 @@ Consider organizing music files as: /Music/Artist/Album/Track.ext"""
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canvas.draw()
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def analyze_library_format(db_paths):
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"""Analyze the library format to determine if it matches expected structure"""
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"""Analyze the library format using smart left-to-right parsing"""
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total_files = 0
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matching_files = 0
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sample_paths = []
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format_examples = []
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for db_path in db_paths:
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try:
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conn = sqlite3.connect(db_path)
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cursor = conn.cursor()
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# Detect database format
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db_format = check_database_format(db_path)
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if db_format == 'new':
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success_condition = "StateDescription='Completed, Succeeded'"
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else:
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success_condition = "State LIKE 'Completed, Succeeded'"
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# Get a sample of successful upload filenames
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cursor.execute("""
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cursor.execute(f"""
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SELECT Filename
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FROM Transfers
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WHERE State = 48 AND Direction = 'Upload' AND Filename IS NOT NULL
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LIMIT 100
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WHERE {success_condition} AND Direction = 'Download' AND Filename IS NOT NULL
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LIMIT 200
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""")
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rows = cursor.fetchall()
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@@ -1252,17 +1265,17 @@ def analyze_library_format(db_paths):
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total_files += 1
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sample_paths.append(filename)
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# Check if it matches expected format: /path/Music/{Artist}/{Album}/{Track}
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if filename and '/Music/' in filename:
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try:
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parts = filename.split('/Music/')
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if len(parts) > 1:
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music_path = parts[1]
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path_parts = music_path.split('/')
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if len(path_parts) >= 2 and path_parts[0] and path_parts[1]:
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matching_files += 1
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except:
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continue
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# Use smart parsing to extract artist/album
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artist, album = parse_media_path(filename)
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if artist and album:
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matching_files += 1
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# Keep some examples for display
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if len(format_examples) < 10:
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format_examples.append({
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'path': filename,
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'artist': artist,
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'album': album
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})
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conn.close()
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@@ -1274,48 +1287,121 @@ def analyze_library_format(db_paths):
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'total_files': total_files,
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'matching_files': matching_files,
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'match_percentage': match_percentage,
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'sample_paths': sample_paths[:10] # Keep first 10 as examples
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'sample_paths': sample_paths[:10],
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'format_examples': format_examples
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}
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def parse_media_path(filepath):
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"""Smart left-to-right analysis of media file paths to extract artist and album"""
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if not filepath:
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return None, None
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# Normalize path separators (handle both single and double backslashes)
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normalized_path = filepath.replace('\\\\', '/').replace('\\', '/')
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lower_path = normalized_path.lower()
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# Find potential media indicators (case insensitive)
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media_indicators = [
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'/music/', '/audiobooks/', '/audio/', '/media/',
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'/artists/', '/musica/', '/jazz/', '/rock/', '/electronic/',
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'music/', 'artists/', 'musica/', 'jazz/', 'albums/'
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]
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path_parts = []
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# Try to find a media root
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media_start_idx = -1
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for indicator in media_indicators:
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idx = lower_path.find(indicator)
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if idx >= 0:
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media_start_idx = idx + len(indicator)
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break
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if media_start_idx >= 0:
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# Extract from media root
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media_path = normalized_path[media_start_idx:]
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path_parts = [part for part in media_path.split('/') if part]
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else:
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# No clear media indicator - use heuristic approach
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# Look for Artist/Album pattern in the path structure
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all_parts = [part for part in normalized_path.split('/') if part]
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# Filter out common system/user prefixes
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filtered_parts = []
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skip_patterns = ['@@', '!', '#', 'my files', 'downloads', 'shared', 'soulseek', 'main']
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for part in all_parts:
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part_lower = part.lower()
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should_skip = False
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for pattern in skip_patterns:
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if part_lower.startswith(pattern):
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should_skip = True
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break
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# Also skip parts that look like disk/volume identifiers
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if len(part) <= 2 or part.isdigit() or (len(part) < 8 and any(c in part for c in '-_0123456789')):
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should_skip = True
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if not should_skip:
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filtered_parts.append(part)
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# Take meaningful parts (likely Artist/Album/File or Genre/Artist/Album/File)
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if len(filtered_parts) >= 3:
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# Assume last 3 are Genre/Artist/Album or Artist/Album/File
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# If last part looks like a file, take the two before it
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if '.' in filtered_parts[-1]:
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path_parts = filtered_parts[-3:-1] # Artist and Album
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else:
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path_parts = filtered_parts[-2:] # Artist and Album
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elif len(filtered_parts) >= 2:
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path_parts = filtered_parts[-2:] # Assume Artist/Album
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# Need at least 2 parts: Artist/Album
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if len(path_parts) < 2:
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return None, None
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artist = path_parts[0]
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raw_album = path_parts[1]
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# Smart album cleaning
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cleaned_album = clean_album_name(artist, raw_album)
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return artist, cleaned_album
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def clean_album_name(artist, album):
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"""Smart cleaning of album names to remove redundant artist information"""
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"""Enhanced album name cleaning with common prefix removal"""
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if not artist or not album:
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return album
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artist_lower = artist.lower().strip()
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album_lower = album.lower().strip()
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# Common patterns to clean
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patterns_to_try = [
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# Pattern: "Artist - Album Title"
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f"{artist_lower} - ",
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f"{artist_lower} – ", # em dash
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f"{artist_lower} — ", # em dash variant
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# Pattern: "Artist: Album Title"
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f"{artist_lower}: ",
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f"{artist_lower} : ",
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# Pattern: "Artist_ Album Title" or similar separators
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f"{artist_lower}_ ",
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f"{artist_lower} _ ",
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]
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# Enhanced patterns to clean (more comprehensive)
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separators = [' - ', ' – ', ' — ', ': ', ' : ', '_ ', ' _ ', ' | ', ' / ']
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cleaned_album = album
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for pattern in patterns_to_try:
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for sep in separators:
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pattern = f"{artist_lower}{sep}"
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if album_lower.startswith(pattern):
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cleaned_album = album[len(pattern):]
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break
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# Additional cleaning: remove extra whitespace and dashes
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cleaned_album = cleaned_album.strip(' -–—_')
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# Additional cleanup patterns
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if cleaned_album == album: # No separator match, try other patterns
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# Pattern: "ArtistName AlbumTitle" (space separated)
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if album_lower.startswith(artist_lower + ' ') and len(album) > len(artist) + 1:
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potential_clean = album[len(artist) + 1:]
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# Only use if the remaining part looks like an album title
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if len(potential_clean) > 3 and not potential_clean[0].islower():
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cleaned_album = potential_clean
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# If cleaning resulted in empty string, return original
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if not cleaned_album:
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# Final cleaning: remove extra whitespace and punctuation
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cleaned_album = cleaned_album.strip(' -–—_:|/')
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# Validation: don't return empty or too-short results
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if not cleaned_album or len(cleaned_album) < 2:
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return album
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# If cleaning removed too much (less than 3 chars), return original
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if len(cleaned_album) < 3:
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# Don't clean if it removes more than 70% of the original
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if len(cleaned_album) < len(album) * 0.3:
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return album
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return cleaned_album
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@@ -1325,20 +1411,28 @@ def get_popularity_stats(db_paths, days=None):
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artist_stats = defaultdict(lambda: {'count': 0, 'bytes': 0})
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album_stats = defaultdict(lambda: {'count': 0, 'bytes': 0})
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# Create WHERE clause for time filtering
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where_clause = "WHERE State = 48 AND Direction = 'Upload'" # Only successful uploads
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params = []
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if days is not None:
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where_clause += " AND RequestedAt >= ?"
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cutoff_date = (datetime.datetime.now() - datetime.timedelta(days=days)).isoformat()
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params.append(cutoff_date)
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for db_path in db_paths:
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try:
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conn = sqlite3.connect(db_path)
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cursor = conn.cursor()
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# Detect database format
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db_format = check_database_format(db_path)
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if db_format == 'new':
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success_condition = "StateDescription='Completed, Succeeded'"
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else:
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success_condition = "State LIKE 'Completed, Succeeded'"
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# Create WHERE clause for time filtering
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where_clause = f"WHERE {success_condition} AND Direction = 'Download'" # Track what users download
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params = []
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if days is not None:
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where_clause += " AND RequestedAt >= ?"
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cutoff_date = (datetime.datetime.now() - datetime.timedelta(days=days)).isoformat()
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params.append(cutoff_date)
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query = f"""
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SELECT Filename, Size
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FROM Transfers
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@@ -1349,32 +1443,17 @@ def get_popularity_stats(db_paths, days=None):
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rows = cursor.fetchall()
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for filename, size in rows:
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# Parse filename to extract artist and album
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# Expected format: /data/Music/{Artist}/{Album}/{Track}
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if filename and '/Music/' in filename:
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try:
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parts = filename.split('/Music/')
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if len(parts) > 1:
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music_path = parts[1]
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path_parts = music_path.split('/')
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if len(path_parts) >= 2:
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artist = path_parts[0]
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raw_album = path_parts[1]
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# Clean album name to remove redundant artist info
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cleaned_album = clean_album_name(artist, raw_album)
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# Update artist stats
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artist_stats[artist]['count'] += 1
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artist_stats[artist]['bytes'] += size
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# Update album stats using cleaned album name
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album_key = (artist, cleaned_album)
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album_stats[album_key]['count'] += 1
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album_stats[album_key]['bytes'] += size
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except:
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# Skip files that don't match expected format
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continue
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# Use smart left-to-right parsing to extract artist and album
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artist, album = parse_media_path(filename)
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if artist and album:
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# Update artist stats
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artist_stats[artist]['count'] += 1
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artist_stats[artist]['bytes'] += size
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# Update album stats
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album_key = (artist, album)
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album_stats[album_key]['count'] += 1
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album_stats[album_key]['bytes'] += size
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conn.close()
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