This is an NBA Analytics website with multiple components such as a chatbot, blogs, and predictions. All the data for the site is being scraped from Basketball Reference.
-
Clone the repository locally:
git clone https://github.com/skekre98/NBA-Search.git -
Run the following command to set up all necessary requirements:
pip install -r requirements.txt -
Run the following command to deploy the web app on your localhost:
python main.py run
- Run the following command to run the unit tests:
You can also add you own unit tests in test.py
python main.py test
There is a lot to do so contributions are really appreciated! This is a great project for early stage developers to work with.
To begin it is recommended starting with issues labelled good first issue.
How to get started:
- Fork the NBA-Search repo.
- Create a new branch in you current repo from the 'master' branch with issue label.
- 'Check out' the code with Git or GitHub Desktop
- Check contributing.md
- Push commits and create a Pull Request (PR) to NBA-Search
- Flask - The framework used to build the web app.
- Beautiful Soup - The HTML parser used for web scraping.
- Sklearn - The machine learning library used to implement information retrieval.
- Pandas - The python library used for data manipulation.