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.

1. Clone the repository locally:

   git clone https://github.com/skekre98/NBA-Search.git
   

2. Run the following command to set up all necessary requirements:

   pip install -r requirements.txt
   

3. Run the following command to deploy the web app on your localhost:

   python main.py run
   

4. Run the following command to run the unit tests:

   python main.py test
   

   You can also add you own unit tests in test.py

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:

1. Fork the NBA-Search repo.
2. Create a new branch in you current repo from the 'master' branch with issue label.
3. 'Check out' the code with Git or GitHub Desktop
4. Check contributing.md
5. 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.