Datalyzer is an interactive Flask web application designed to enhance the learning experience of computer science students, with a focus on data structures. This project, created as part of my journey through CS50, showcases frontend and backend development skills.

1. Interactive Data Structures: Allows users to interactively explore data structures such as stacks, queues, and trees. This hands-on approach aids in understanding the operations and behaviors of these structures.

2. Curated Resources List: Provides a compilation of educational resources to further understand data structures. This list is a valuable tool for extending learning beyond the interactive elements.

3. Data Structures Quiz: An interactive quiz section to test and reinforce the understanding of data structures.

The application is built with Flask, HTML, CSS, and JavaScript, creating a responsive user interface. While initially planned, the application currently does not implement a backend database. This choice was made due to challenges encountered in integrating and managing database operations seamlessly with the frontend.

One significant challenge in the development of Datalyzer was implementing the user-submitted resources feature. The initial plan was to allow users to submit resources, which would be stored and displayed from a database. However, difficulties arose in the integration of database operations with Flask and the frontend interface. Issues included:

• Data Persistence: Without a database, persisting user submissions across sessions proved to be complex.
• Frontend-Backend Integration: Encountered challenges in seamlessly connecting the frontend form submissions with a backend database.
• User Interface: Struggled to maintain a user-friendly interface while integrating dynamic content updates.

These challenges led to the decision not to use a database for this version of the project. Instead, I focused on refining the static components and ensuring a smooth user experience.

Despite the challenges, this project provided valuable lessons in web development, particularly in understanding the complexities of full-stack development and the importance of feature scoping and project management.

To run Datalyzer:

• Clone the repository: git clone https://github.com/Bryan-Webifi-dev/Datalyzer.git
• Install required packages: pip install -r requirements.txt
• Run the application: python app.py
• Access the app in a web browser at localhost:5000.
• NOTE: Had a VERY hard time running this in the cs50 VScode codespace for some reason - let me know of any issues please!!

Datalyzer, while not fully realizing the initial vision of dynamic user interactions, stands as a testament to the learning process and the iterative nature of software development. It represents a significant step in my coding journey, embodying the core principles of problem-solving and perseverance I learned in CS50.

Looking forward, I plan to revisit the challenges faced in this project, particularly integrating a database to manage user submissions, to further enhance Datalyzer’s capabilities.