74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
import os
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import sys
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import mutagen
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if len(sys.argv) != 2:
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print("Usage: python3 MusicLibVisualizing/main.py <path_to_your_music_library>")
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sys.exit(1)
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music_library = sys.argv[1]
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music_data = []
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from tqdm import tqdm
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for root, dirs, files in tqdm(list(os.walk(music_library)), desc="Walking folders", unit="folders"):
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for file in tqdm(files, desc=f"Processing folder {root}", unit="files"):
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if file.endswith(('.mp3', '.flac', '.opus')):
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try:
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audio = mutagen.File(os.path.join(root, file))
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#print(f"Processing {file}")
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#print(audio.info)
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music_data.append({
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"title": audio.get('title', ['Unknown'])[0],
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"artist": audio.get('artist', ['Unknown'])[0],
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"album": audio.get('album', ['Unknown'])[0],
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"genre": audio.get('genre', ['Unknown'])[0],
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"length": audio.info.length,
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#"bitrate": audio.info.bitrate
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})
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except Exception as e:
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print(f"Error processing {file}: {e}")
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print(f"Found a total of {len(music_data)} files.")
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import pandas as pd
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df = pd.DataFrame(music_data)
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import seaborn as sns
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import matplotlib.pyplot as plt
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plt.figure(figsize=(10, 6))
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sns.histplot(df['length'], bins=30, kde=True)
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plt.title('Track Length Distribution')
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plt.xlabel('Length (seconds)')
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plt.ylabel('Count')
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plt.show()
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top_artists = df['artist'].value_counts().head(10)
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plt.figure(figsize=(10, 6))
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sns.barplot(x=top_artists.values, y=top_artists.index)
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plt.title('Top 10 Most Frequent Artists')
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plt.xlabel('Number of Tracks')
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plt.show()
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genre_counts = df['genre'].value_counts()
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plt.figure(figsize=(10, 6))
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genre_counts.plot.pie(autopct='%1.1f%%')
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plt.title('Genre Distribution')
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plt.ylabel('')
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plt.show()
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avg_length_by_genre = df.groupby('genre')['length'].mean().sort_values()
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plt.figure(figsize=(10, 6))
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sns.barplot(x=avg_length_by_genre.values, y=avg_length_by_genre.index)
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plt.title('Average Song Length by Genre')
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plt.xlabel('Average Length (seconds)')
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plt.show()
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