Impressively, FitFeed automatically generates fitness and diet plans based on your body data, records body changes, offers workout demos, and even lets you listen to music while you exercise.
- Streamlit for the web interface
- SQLite for data storage
- Matplotlib and Plotly for data visualization
- Python for backend logic
FitFeed aims to simplify fitness planning by providing personalized workout and diet plans based on user-specific body data, tracking progress over time, and enhancing workout sessions with interactive demos and music.
- Install the required Python packages:
pip install streamlit matplotlib plotly sqlite3. - Clone the repository and navigate to the project directory.
- Run the Streamlit application:
streamlit run app.py.
- Developing a full-stack application using Streamlit.
- Managing a SQLite database to store and retrieve user data.
- Creating interactive data visualizations to track fitness progress.
- Ensuring the application is user-friendly and intuitive.
- Integrating different technologies smoothly for a seamless user experience.
- Handling and visualizing data effectively to provide meaningful insights.