Trace is a project developed and maintained by putrinaq under the auspices of Universiti Malaysia Sarawak (UNIMAS). Built primarily in Python, Trace is designed to provide robust solutions for trace analysis, data tracking, or research-driven applications. The project aims to support both academic research and practical implementations in data analysis and event tracing.
Trace enables users and researchers at UNIMAS and beyond to efficiently analyze, process, and visualize trace data. Whether for educational, research, or industrial use, Trace provides a flexible and extensible platform adaptable to various trace data scenarios.
- Modular Architecture: Easily extend Trace for new research or industry use cases.
- Python Ecosystem: Built with Python for speed, flexibility, and rich library support.
- Data Scalability: Handles large-scale datasets and complex trace scenarios.
- Easy Integration: Plug in your own analysis modules or adapt existing ones.
- Community & Academic Focus: Developed at UNIMAS, with an open invitation to the global research community.
- Python 3.8 or later
- Cross-platform: Works on Windows, macOS, and Linux
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Clone the repository:
git clone https://github.com/trace-unimas/Trace.git cd Trace -
Install dependencies:
pip install -r requirements.txt
If
requirements.txtis not present, please manually install dependencies as needed.
To get started, run:
python main.py [options]- Main Maintainer: putrinaq
- Project Repository: https://github.com/trace-unimas/Trace
- Live Website https://unimas-trace.com
- Institution: Universiti Malaysia Sarawak (UNIMAS)