hoopstats can be accessed here on PyPi.
This project serves as a proof of concept (POC) for web scraping NBA data from Basketball Reference. The primary motivation is to explore the intersection of data science and software engineering by building a reliable NBA-focused Python package. The long-term objective of this project is to evolve into the backend of a full-stack application, providing users with seamless access to NBA statistics through an intuitive and user-friendly interface.
- Scrape NBA player statistics from Basketball Reference
- Access detailed game logs and player splits
- Convenient API for querying player and game data
To install HoopStats, you can use pip:
pip install hoopstatsHere's a basic example of how to use HoopStats:
from hoopstats import PlayerScraper
# Initialize the scraper with player names
player_scraper = PlayerScraper(first_name="Lonzo", last_name="Ball")
# Access the player's data
print(player_scraper.url)
# Access the player's game log stats, based on a given year
print(player_scraper.get_game_log_by_year(2024))To review full functionality of the code, look under the services folder.
To run the tests for HoopStats, use the following command:
pytest --cov=.Make sure to add tests for any new features or bug fixes.
This project is licensed under the MIT License. See the LICENSE file for details.
Author: Calvin Min (2024)