Alec
9c0a4e0ff2
- 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
75 lines
2.4 KiB
Markdown
75 lines
2.4 KiB
Markdown
# 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)
|
|
- 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
|
|
|
|
|
|
### 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 `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 |