{"id":23145918,"url":"https://github.com/patrickjnr/streamlitmemcleaner","last_synced_at":"2026-04-28T11:03:24.239Z","repository":{"id":268275870,"uuid":"903825460","full_name":"PatrickJnr/StreamLitMemCleaner","owner":"PatrickJnr","description":"Memory Cleanup Utility is a Streamlit-based application that monitors, analyzes, and cleans system memory. 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This tool helps identify memory bottlenecks, perform cleanup tasks, and maintain historical data on memory usage.\n\n---\n\n## Demo\n\nWatch the demo of the Memory Cleanup Utility:\n\n[Demo Video](https://github.com/user-attachments/assets/aa79d784-5d22-470e-a597-fe407e9e069d)\n\n---\n\n## Features\n\n- **Memory Monitoring**: Displays your system's total, free, cached, and used memory.\n- **Cleanup Commands**: Executes memory cleanup tasks, including clearing:\n  - Modified page list\n  - Standby list\n  - Priority 0 standby list\n  - Working sets\n- **Historical Data Visualization**:\n  - Tracks memory usage over time.\n  - Visualizes data in easy-to-read charts.\n- **Integration with EmptyStandbyList.exe**: Uses the executable to perform memory cleanup tasks.\n- **Custom CSS Styling**: Personalize the application UI with external CSS files.\n- **Version Checking**: Manually check for application updates.\n- **Git Commit Hash Display**: Shows the current Git commit hash in the app footer.\n\n---\n\n## Installation\n\n### Prerequisites\n\n1. Install [Python 3.9+](https://www.python.org/downloads/).\n2. Install the required Python libraries:\n   ```bash\n   pip install streamlit pandas matplotlib requests\n   ```\n3. Download the `EmptyStandbyList.exe` file. If not already present, the app will prompt you to download it during runtime.\n\n### Method 1: Clone the Repository\n\n1. Clone this repository:\n   ```bash\n   git clone https://github.com/PatrickJnr/StreamLitMemCleaner.git\n   ```\n2. Navigate to the project directory:\n   ```bash\n   cd StreamLitMemCleaner\n   ```\n3. Start the application:\n   ```bash\n   streamlit run memcleaner.py\n   ```\n4. The app should automatically open in your browser at `http://localhost:8501`.\n\n### Method 2: Download the Latest Release\n\n1. Download the latest release from the [releases tab](https://github.com/PatrickJnr/StreamLitMemCleaner/releases).\n2. Extract the downloaded archive.\n3. Navigate to the extracted directory.\n4. Ensure you have Python 3.9+ and the required libraries installed (see prerequisites above).\n5. Start the application using the command:\n   ```bash\n   streamlit run memcleaner.py\n   ```\n6. The app should automatically open in your browser at `http://localhost:8501`.\n\n### Method 3: Run the Application Using `run.bat` (Windows Only)\n\nFor ease of use, a `run.bat` file is included in the repository. This script will:\n\n- Install the required Python dependencies.\n- Run the application automatically.\n\nTo use the `run.bat` file:\n\n1. Download or clone the repository.\n2. Navigate to the project directory.\n3. Double-click the `run.bat` file to start the application.\n\n---\n\n## Usage\n\n### Memory Monitoring\n- View system memory statistics, including:\n  - Total memory\n  - Free memory\n  - Cached memory\n\n### Cleanup Tasks\n- Select from various cleanup options to free up system memory.\n- Track the amount of memory freed after executing commands.\n- Warnings are displayed if all cleanup options are selected simultaneously.\n\n### Historical Data\n- Analyze historical memory usage with detailed tables and charts.\n- Manage memory history by deleting data that exceeds a specified maximum row count.\n\n---\n\n## Development\n\nTo contribute or debug:\n\n1. Use Git for version control.\n2. Run the app in a local development environment.\n3. Ensure changes pass tests before submitting a pull request.\n\nThe **Latest Commit Hash** is automatically displayed in the app footer for reference.\n\n---\n\n## Help\n\nFor troubleshooting and support:\n\n- Check the **Help** section in the app footer.\n- Report issues or ask questions on the [GitHub Issues page](link_to_github_issues).\n\n---\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n\n---\n\n## Credits\n\nThis application utilizes the following libraries and tools:\n\n- [Streamlit](https://streamlit.io/) - For building the app interface and functionality.\n- [Matplotlib](https://matplotlib.org/) - For visualizing memory usage data in charts.\n- [Pandas](https://pandas.pydata.org/) - For handling and processing memory usage data.\n- [Requests](https://requests.readthedocs.io/en/master/) - For making HTTP requests to retrieve updates and other data.\n- [Python](https://www.python.org/) - The underlying programming language.\n\nSpecial thanks to contributors and the open-source community for their support.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatrickjnr%2Fstreamlitmemcleaner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpatrickjnr%2Fstreamlitmemcleaner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpatrickjnr%2Fstreamlitmemcleaner/lists"}