Add requirements.txt for easier dependency installation

- Change popularity stats to analyze upload records (Direction = 'Upload')
- This shows which of your shared files are most downloaded by others
- Update error messages and explanations to reflect upload-based analysis
- Remove "NEW" labels from README features
- Clarify that popularity shows download frequency of your uploads

.gitignore

@@ -0,0 +1,2 @@
+transfers.db
+.DS_Store

LICENSE

@@ -1,21 +0,0 @@
-MIT License
-
-Copyright (c) 2025 Player6734
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.

README.md

@@ -1,2 +1,75 @@
-# slskd-stats
+# slskd Transfer Statistics
-A python script to see upload stats (kind of manual)
+
+A GUI tool to analyze upload and download statistics from your slskd transfers database.
+
+## Features
+
+- Analyzes uploads and downloads stored in the transfers.db database(s)
+- Automatically finds and combines data from multiple database files
+- Backwards compatible with both old and new database formats
+- Calculates total transfers, data transferred, and unique users
+- Shows average transfer speed and duration
+- Lists top users by data transferred
+- Shows statistics by file type
+- Filter statistics by time period (All time, Last month, Last year)
+- Artist and album popularity statistics based on download frequency of your uploads
+- Smart path parsing with enhanced library structure detection  
+- Intelligent album name cleaning (removes redundant artist names from folder names)
+- User-friendly graphical interface with summary and detailed tables
+
+## Requirements
+
+- Python 3.6+
+- SQLite3
+- PyQt5
+- matplotlib
+
+## Installation
+
+1. Clone or download this repository to your local machine
+2. Install dependencies: `pip3 install PyQt5 matplotlib`
+3. Place your `transfers.db` file in the same directory as the script, or use the file browser to select database files
+
+## Usage
+
+```bash
+# Launch the GUI application
+python3 slskd_stats_gui.py
+```
+
+With the GUI, you can:
+- Select one or more database files using the file browser
+- Choose time period from dropdown (All time, Last month, Last year)
+- Set the number of top entries to display
+- View upload and download statistics side-by-side
+- See summary statistics and detailed tables for users and file types
+- Visual time series graphs showing transfer trends over time
+- Analyze artist and album popularity based on how often others download your files with interactive charts and tables
+
+## Screenshots
+
+### Summary View
+![Summary View](Summary.png)
+
+### Visual Stats with Time Series Graphs
+![Visual Stats](Visual.png)
+
+### Popularity Stats with Artist and Album Rankings
+![Popularity Stats](Popularity.png)
+
+## Database Compatibility
+
+This tool automatically detects and works with both:
+- **Old format**: Text-based `State` column
+- **New format**: Integer `State` + `StateDescription` columns
+
+
+## About
+
+This tool is designed to work with the `transfers.db` SQLite database created by [slskd](https://github.com/slskd/slskd), a Soulseek client daemon. It helps you understand your sharing patterns and track transfer statistics.
+
+*This project was developed with assistance from AI.*
+
+## License
+
+MIT

requirements.txt

@@ -0,0 +1,2 @@
+PyQt5>=5.15.0
+matplotlib>=3.5.0

slskd-upload-stats.py

@@ -1,207 +0,0 @@
-#!/usr/bin/env python3
-"""
-SLSKD Transfer Size Analyzer
-
-A script I created to analyze SLSKD HTML and calculate accurate transfer statistics.
-After experimenting with different approaches, I found that checking the button text
-directly gives more reliable results than relying on CSS classes.
-
-I also added automatic conversion between MB and GB to make large numbers more readable.
-
-Usage:
-  python slskd_analyzer_with_gb.py <html_file>
-"""
-
-import re
-import sys
-import os
-from bs4 import BeautifulSoup
-
-def format_size(size_mb):
-    """
-    Format file size in MB or GB depending on the size.
-    
-    I added this function to make large transfer sizes more readable.
-    After dealing with multi-GB transfers, seeing something like "2458.7 MB" 
-    is less intuitive than "2.4 GB".
-    """
-    if size_mb >= 1024:
-        return f"{size_mb/1024:.2f} GB"
-    else:
-        return f"{size_mb:.1f} MB"
-
-def analyze_html(html_content):
-    """
-    Parse and analyze the SLSKD HTML content to extract transfer statistics.
-    
-    I initially tried looking only at CSS classes, but found inconsistencies in how 
-    the success/failure states were represented. Checking the actual button text with
-    "Completed, Succeeded" proved more reliable and worked across different versions.
-    """
-    soup = BeautifulSoup(html_content, 'html.parser')
-    
-    # Initialize statistics dictionary
-    stats = {
-        'successful_mb': 0,
-        'failed_mb': 0,
-        'total_mb': 0,
-        'successful_files': 0,
-        'failed_files': 0,
-        'flac_files': 0,
-        'mp3_files': 0,
-        'users': {}
-    }
-    
-    # Process each transfer card (one per user)
-    # I structured it this way to make it easier to attribute transfers to users
-    transfer_cards = soup.find_all('div', class_='ui raised card transfer-card')
-    
-    for card in transfer_cards:
-        # Extract the username from the header
-        header = card.find('div', class_='header')
-        username = header.text.strip() if header else "Unknown"
-        
-        # Initialize user statistics if not already present
-        if username not in stats['users']:
-            stats['users'][username] = {
-                'successful_mb': 0,
-                'failed_mb': 0, 
-                'total_mb': 0,
-                'successful_files': 0,
-                'failed_files': 0
-            }
-        
-        # Process all file rows for this user
-        # I tried several approaches and found traversing the rows directly was most reliable
-        rows = card.find_all('tr')
-        
-        for row in rows:
-            # Skip header rows - they have th elements
-            if row.find('th'):
-                continue
-            
-            # Extract the relevant cells
-            filename_cell = row.find('td', class_='transferlist-filename')
-            progress_cell = row.find('td', class_='transferlist-progress')
-            size_cell = row.find('td', class_='transferlist-size')
-            
-            # Skip if any required cell is missing
-            if not all([filename_cell, progress_cell, size_cell]):
-                continue
-            
-            filename = filename_cell.text.strip()
-            button = progress_cell.find('button')
-            
-            if not button:
-                continue
-                
-            # Track file types - primarily interested in audio formats
-            if filename.lower().endswith('.flac'):
-                stats['flac_files'] += 1
-            elif filename.lower().endswith('.mp3'):
-                stats['mp3_files'] += 1
-            
-            # Check success/failure status based on button text
-            # This was a key insight - looking for specific text patterns rather than
-            # relying on CSS classes which can vary across SLSKD versions/themes
-            button_text = button.text.strip()
-            is_success = 'Completed, Succeeded' in button_text
-            is_failed = 'Completed, Errored' in button_text
-            
-            # Parse size information
-            # Format is typically "X.X/Y.Y MB" where X is transferred and Y is total
-            size_text = size_cell.text.strip()
-            size_match = re.search(r'(\d+(?:\.\d+)?)/(\d+(?:\.\d+)?)', size_text)
-            
-            if not size_match:
-                continue
-                
-            transferred = float(size_match.group(1))
-            total = float(size_match.group(2))
-            
-            # Update statistics based on transfer status
-            if is_success:
-                stats['successful_mb'] += transferred
-                stats['successful_files'] += 1
-                stats['users'][username]['successful_mb'] += transferred
-                stats['users'][username]['successful_files'] += 1
-            elif is_failed:
-                # For failed transfers, I count the target size rather than the partial transfer
-                # This gives a better sense of what "should have" transferred
-                stats['failed_mb'] += total
-                stats['failed_files'] += 1
-                stats['users'][username]['failed_mb'] += total
-                stats['users'][username]['failed_files'] += 1
-            
-            stats['total_mb'] += total
-            stats['users'][username]['total_mb'] += total
-    
-    return stats
-
-def print_report(stats):
-    """
-    Format and print a comprehensive report of the transfer statistics.
-    
-    I organized this to present the most relevant information first (overall stats),
-    followed by file type breakdowns and user-specific information.
-    
-    For readability, I convert large values from MB to GB automatically.
-    """
-    print("\n===== SLSKD TRANSFER STATISTICS =====")
-    
-    print(f"\nOverall Statistics:")
-    print(f"Successfully transferred: {format_size(stats['successful_mb'])} ({stats['successful_files']} files)")
-    print(f"Failed transfers: {format_size(stats['failed_mb'])} ({stats['failed_files']} files)")
-    print(f"Total size of all files: {format_size(stats['total_mb'])} ({stats['successful_files'] + stats['failed_files']} files)")
-    
-    if stats['total_mb'] > 0:
-        success_rate = (stats['successful_mb'] / stats['total_mb']) * 100
-        print(f"Success rate: {success_rate:.1f}%")
-    
-    print(f"\nFile Type Statistics:")
-    print(f"FLAC files: {stats['flac_files']}")
-    print(f"MP3 files: {stats['mp3_files']}")
-    other_files = stats['successful_files'] + stats['failed_files'] - stats['flac_files'] - stats['mp3_files']
-    print(f"Other files: {other_files}")
-    
-    # Top users by total volume
-    print("\nTop Users by Total Transfer Volume:")
-    sorted_users_total = sorted(stats['users'].items(), key=lambda x: x[1]['total_mb'], reverse=True)
-    for i, (username, user_stats) in enumerate(sorted_users_total[:5], 1):
-        print(f"{i}. {username}: {format_size(user_stats['total_mb'])} total")
-    
-    # Top users by successful transfers
-    print("\nTop Users by Successful Transfers:")
-    sorted_users_success = sorted(stats['users'].items(), key=lambda x: x[1]['successful_mb'], reverse=True)
-    for i, (username, user_stats) in enumerate(sorted_users_success[:5], 1):
-        if user_stats['successful_mb'] > 0:
-            print(f"{i}. {username}: {format_size(user_stats['successful_mb'])} successful "
-                  f"({user_stats['successful_files']} files)")
-    
-    print("\n=====================================")
-
-def main():
-    """
-    Main entry point - handles command line arguments and file processing.
-    
-    I kept the interface simple - just provide the HTML file path as an argument.
-    This makes it easy to analyze different snapshots over time.
-    """
-    if len(sys.argv) != 2:
-        print(f"Usage: {sys.argv[0]} <html_file>")
-        sys.exit(1)
-    
-    html_file = sys.argv[1]
-    
-    if not os.path.exists(html_file):
-        print(f"Error: File {html_file} does not exist")
-        sys.exit(1)
-    
-    with open(html_file, 'r', encoding='utf-8') as f:
-        html_content = f.read()
-    
-    stats = analyze_html(html_content)
-    print_report(stats)
-
-if __name__ == "__main__":
-    main()