Full Course Info

Recipe App Live

This project was an opportunity to explore Django’s straightforward and efficient development process. The focus was on designing a solid data model first, ensuring that the core logic—the “brain” of the application—was well-structured before building out the user interface. Django’s built-in ORM made managing database relationships seamless, while its automatic admin panel streamlined early testing and data management. The application was thoroughly tested using Django’s built-in testing framework, allowing for reliable validation of features and ensuring a smooth user experience. PostgreSQL was used for production and SQLite was used for local testing. Pandas and Matplotlib enabled data analysis and visualization. Deployment on Heroku, supported by dj-database-url, psycopg2-binary, gunicorn, and whitenoise, ensured a scalable and efficient hosting solution. Additionally, Pillow was integrated for handling user-uploaded images. Django’s simplicity and robust features made the development process smooth, allowing for rapid iteration and thorough testing at each stage.

Technologies used: Python, Django, JS, CSS, HTML, Heroku, Postgres, SQLite, Pandas, Matplotlib, dj-database-url, psycopg2-binary, gunicorn, whitenoise, pillow

Practice Bookstore Live

Developed a practice project to explore Django's Model-View-Template (MVT) architecture, user authentication, and data analytics. Acquired proficiency in key Django features, including the admin interface, migrations, and implementing authorization for views and templates.

Technologies used: Python, Django, JS, CSS, HTML, Heroku, Postgres, SQLite, Pandas, Matplotlib, dj-database-url, psycopg2-binary, gunicorn, whitenoise, pillow.

Recipe Console App

Developed a recipe console application that allows users to manage their favorite recipes while exploring the fundamentals of structuring a Python application. Using Python’s object-oriented features, I organized the app with classes for better modularity and maintainability. SQLAlchemy provided a flexible way to interact with databases, while MySQLclient and SQLite offered different storage options to experiment with. IPython enhanced the development process with its interactive shell, making debugging and testing more efficient. Setting up a virtual environment ensured dependency management and project isolation, reinforcing best practices for maintaining clean and portable Python applications.

Technologies used: Python, SQLAlchemy, MySQLclient, Ipython, SQLite.