cf197456deaaaff104eab02885c2b97cbd859edb
- New Popularity Stats tab showing top artists and albums by upload count - Interactive charts with truncated names and hover tooltips - Smart album name cleaning to remove redundant artist prefixes - Library format detection and user-friendly error messages - Configurable top entries display (5-50, default 10) - Read-only tables to prevent accidental data modification - Centered charts with proper label spacing - Removed mplcursors dependency for better compatibility - Updated README with new features and screenshot
slskd Transfer Statistics
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)
- NEW: Artist and album popularity statistics based on successful uploads
- Smart 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
- Clone or download this repository to your local machine
- Install dependencies:
pip3 install PyQt5 matplotlib - Place your
transfers.dbfile in the same directory as the script, or use the file browser to select database files
Usage
# 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
- NEW: Visual time series graphs showing transfer trends over time
- NEW: Analyze artist and album popularity with interactive charts and tables
Screenshots
Summary View
Visual Stats with Time Series Graphs
Popularity Stats with Artist and Album Rankings
Database Compatibility
This tool automatically detects and works with both:
- Old format: Text-based
Statecolumn - New format: Integer
State+StateDescriptioncolumns
About
This tool is designed to work with the transfers.db SQLite database created by 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
Description
This tool is designed to work with the
transfers.db SQLite database created by slskd, a Soulseek client daemon.
Languages
Python
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