This project, the Credit Card Reward Optimizer, is designed to help users optimize their credit card usage to maximize rewards and minimize interest and fees. It utilizes the PuLP library in Python to model and solve optimization problems, providing the best strategies for credit card payments and usage.
- Optimization of Payments: Determines how to allocate payments across multiple credit cards to minimize interest.
- Rewards Maximization: Suggests which card to use for particular purchases to maximize rewards or cash back.
- User Customization: Allows users to input their own credit card balances, interest rates, and rewards schemes.
To run the Credit Card Optimizer, you need Python installed on your machine along with the following Python libraries:
- PuLP
- Pandas
- NumPy
You can install these dependencies with pip:
pip install pulp pandas numpy- Clone this repository to your local machine.
- Ensure you have Python installed, along with the required libraries.
- Run the Jupyter Notebook
Credit_Card_Optimizer_Pulp.ipynb:jupyter notebook Credit_Card_Optimizer_Pulp.ipynb
- Follow the instructions within the notebook to input your credit card details and desired payment strategies.
Contributions to the Credit Card Optimizer are welcome! Please read through our contributing guidelines to learn about our process, how to propose bugfixes and improvements, and how to build and test your changes to the project.
This project is licensed under the Creative Commons Attribution-NonCommercial (CC BY-NC) license. For more details, see LICENSE.md.
If you have any questions or want to collaborate, please contact me on Twitter at @egr_investor.
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