algorc

Your task is to create a Python-based utility called 'AlgorythmMaster' that leverages the 'algorc' package to provide users with an interactive experience for learning and experimenting with fundamental C algorithms. AlgorythmMaster will allow users to select from a variety of algorithms included in the 'algorc' package, input custom data, and observe the execution process and results in real-time. Here are the detailed steps and features for your project:

1. **Setup Environment**: Ensure you have Python installed along with the 'algorc' package. You might need to install it via pip if not already available.
2. **User Interface**: Develop a simple yet effective command-line interface (CLI) where users can navigate through different options. The UI should be intuitive and easy to use, guiding users through selecting algorithms, entering data, and viewing results.
3. **Algorithm Selection**: Implement a feature within the CLI that lists all 15 algorithms provided by the 'algorc' package. Users should be able to choose any algorithm they wish to run.
4. **Data Input**: Allow users to input custom data for the selected algorithm. This could include arrays, strings, or other relevant inputs depending on the nature of the algorithm.
5. **Execution and Visualization**: Once the user selects an algorithm and provides necessary data, execute the chosen algorithm using the 'algorc' package. Display the step-by-step execution process and final output in a readable format. Consider adding visual aids like ASCII diagrams or color-coded outputs to enhance understanding.
6. **Performance Metrics**: Include performance metrics such as time taken for execution and memory usage for each algorithm run. This helps users understand the efficiency of different algorithms.
7. **Help and Documentation**: Provide comprehensive help documentation accessible from the CLI. This should cover how to use the tool, what each algorithm does, and common pitfalls or best practices related to algorithmic thinking.
8. **Testing and Validation**: Ensure thorough testing of all functionalities to guarantee reliability and accuracy of results. Use sample data sets provided in the 'algorc' package documentation for validation.
9. **Customization Options**: Offer customization options where possible, such as setting specific parameters for certain algorithms or choosing between different sorting methods.

By following these guidelines, you'll develop a powerful educational tool that not only executes algorithms but also enhances understanding of their inner workings and performance characteristics.