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import json |
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from collections import Counter |
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import pandas as pd |
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from bs4 import BeautifulSoup |
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import argparse |
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import os |
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def load_json(file_path): |
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try: |
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with open(file_path, 'r', encoding='utf-8') as f: |
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data = json.load(f) |
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song_titles = [ |
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f"{entry['title'].replace('Watched ', '')} - {entry['subtitles'][0]['name'].replace(' - Topic', '') if 'subtitles' in entry else 'Unknown Artist'}" |
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for entry in data if 'header' in entry and entry['header'] == "YouTube Music" |
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] |
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return song_titles |
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except Exception as e: |
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print(f"Error loading JSON file: {e}") |
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return [] |
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def load_html(file_path): |
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try: |
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with open(file_path, 'r', encoding='utf-8') as f: |
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html_content = f.read() |
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soup = BeautifulSoup(html_content, 'html.parser') |
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song_titles = [] |
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outer_cells = soup.find_all('div', class_='outer-cell mdl-cell mdl-cell--12-col mdl-shadow--2dp') |
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for cell in outer_cells: |
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header = cell.find('div', class_='header-cell mdl-cell mdl-cell--12-col') |
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if header and 'YouTube Music' in header.get_text(): |
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content_cells = cell.find_all('div', class_='content-cell mdl-cell mdl-cell--6-col mdl-typography--body-1') |
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if len(content_cells) > 0: |
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song_title_element = content_cells[0].find('a') |
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artist_elements = content_cells[0].find_all('a') |
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if song_title_element and len(artist_elements) > 1: |
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song_title = song_title_element.get_text() |
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artist = artist_elements[1].get_text().replace(' - Topic', '') |
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song_titles.append(f"{song_title} - {artist}") |
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return song_titles |
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except Exception as e: |
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print(f"Error loading HTML file: {e}") |
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return [] |
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def export_top_songs(df, amount, export_format): |
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output_file = f'top_{amount}_songs.{export_format}' |
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try: |
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if export_format == 'txt': |
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with open(output_file, 'w', encoding='utf-8') as f: |
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for index, row in df.iterrows(): |
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title, artist = row['Song'].rsplit(' - ', 1) |
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f.write(f"{index + 1}: {title} - {artist}. {row['Plays']} plays\n") |
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elif export_format == 'json': |
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json_data = [ |
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{"index": index + 1, "Title": row['Song'].rsplit(' - ', 1)[0], "Artist": row['Song'].rsplit(' - ', 1)[1], "Plays": row['Plays']} |
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for index, row in df.iterrows() |
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] |
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with open(output_file, 'w', encoding='utf-8') as f: |
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json.dump(json_data, f, ensure_ascii=False, indent=4) |
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elif export_format == 'csv': |
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with open(output_file, 'w', encoding='utf-8') as f: |
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f.write("Count,Title,Artist,Plays\n") |
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for index, row in df.iterrows(): |
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title, artist = row['Song'].rsplit(' - ', 1) |
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f.write(f"{index + 1},{title},{artist},{row['Plays']}\n") |
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print(f"Top {amount} most listened-to songs have been exported to {output_file}.") |
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except Exception as e: |
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print(f"Error exporting top songs: {e}") |
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def figure_top_songs(df): |
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import matplotlib.pyplot as plt |
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import seaborn as sns |
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# Use seaborn color palette |
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colors = sns.color_palette("viridis", len(df.head(10))) |
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df_top_10 = df.head(10) |
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df_top_10.plot(kind='barh', x='Song', y='Plays', legend=False, color=colors) |
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plt.title(f"Top 10 Most Played Songs", fontsize=14) |
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plt.xlabel("Number of Plays", fontsize=12) |
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plt.ylabel("Song", fontsize=12) |
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plt.gca().invert_yaxis() |
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plt.tight_layout() |
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# Set the window title |
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manager = plt.get_current_fig_manager() |
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manager.set_window_title('Top 10 Most Played Songs') |
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# Save the figure as a PNG file |
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plt.savefig('top_10_songs.png', bbox_inches='tight') |
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print("The graph have been saved as top_10_songs.png.") |
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plt.show() |
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def determine_file_type(file_path): |
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json_file = f"{file_path}.json" |
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html_file = f"{file_path}.html" |
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if file_path.endswith('.json'): |
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return 'json', file_path |
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elif file_path.endswith('.html'): |
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return 'html', file_path |
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elif os.path.exists(json_file): |
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return 'json', json_file |
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elif os.path.exists(html_file): |
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return 'html', html_file |
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else: |
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print("No valid input file found. Please provide a valid JSON or HTML file.") |
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return None, None |
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def main(): |
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parser = argparse.ArgumentParser(description='Process YouTube Music history.') |
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parser.add_argument('--file_path', type=str, default='watch-history', help='Path to the input file without extension') |
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parser.add_argument('--export_format', type=str, choices=['txt', 'json', 'csv'], default='txt', help='Export format for the top songs') |
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parser.add_argument('--amount', type=int, default=10, help='Number of top songs to export') |
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parser.add_argument('--figure', action='store_true', help='Figure the top 10 most played songs') |
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args = parser.parse_args() |
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file_type, file_path_with_extension = determine_file_type(args.file_path) |
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if not file_type: |
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return |
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if file_type == 'json': |
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song_titles = load_json(file_path_with_extension) |
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elif file_type == 'html': |
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song_titles = load_html(file_path_with_extension) |
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if not song_titles: |
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print("No song titles found. Please check the input file.") |
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return |
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song_counts = Counter(song_titles) |
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top_songs = song_counts.most_common(args.amount) |
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df = pd.DataFrame(top_songs, columns=['Song', 'Plays']) |
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export_top_songs(df, args.amount, args.export_format) |
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if args.figure: |
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try: |
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figure_top_songs(df) |
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except ImportError: |
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print("matplotlib and seaborn are not installed. Please install them to use the figuring feature.") |
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print("You can install them using the command: pip install matplotlib seaborn") |
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if __name__ == '__main__': |
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main() |
