Welcome to the TFRRS Data Scraper project for Lehigh University Track & Field! This Python program is designed to scrape raw data from TFRRS.org regarding track and field performance metrics of Lehigh University's track team. It then organizes this data by creating a folder hierarchy where each athlete has their own directory. The collected data is used to generate performance graphs over time for each athlete's events.
- Python 3.x installed on your system.
- Basic knowledge of Python and web scraping.
To use the TFRRS Data Scraper, follow these steps:
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Configure the scraper with the desired settings in
config.py. -
Run the scraper:
python3 <respective .py file>
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The program will start scraping data from TFRRS.org and organize it in athlete-specific directories.
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Once the scraping is complete, use the data for analysis or generate performance graphs using your preferred data visualization tools.
Each athlete's data is stored in a separate directory under the data folder, with individual CSV files for each event they have participated in.
Contributions to this project are welcome. If you'd like to contribute:
- Fork the repository.
- Create a feature branch.
- Make your changes and document them.
- Test your changes thoroughly.
- Submit a pull request for review.
If you have any questions, suggestions, or issues regarding the TFRRS Data Scraper for Lehigh University Track & Field project, please feel free to contact the author:
- Author: Alex Clevenger
- Email: alexbclevenger@gmail.com
- GitHub: https://github.com/alclev Thank you for using the TFRRS Data Scraper for your track and field performance analysis needs!