Covidash is an open source, community driven, COVID-19 dashboard that not only shows the daily statistics of the growing pandemic, but also forecasts the growth of the pandemic.
- The program will run without any issues on any computer, but for a smooth performance, it is recommended to use a system with atleast 4 GB memory, and atleast 2 CPU cores.
- Either Python or Docker must be installed.
- Both npm and Node JS have to be installed to view the documentation.
- You can use git to clone the repository, or you can download the zip file.
- Run the following commands on a UNIX based system.
chmod +x deploy.sh
./deploy.sh
- Open a browser and navigate to localhost:8050, and you will see the dashboard.
- Run the following commands on a UNIX based system to get the python environment ready. We are using venv here, as its very simple to get started with.
python3 -m venv env # Use python instead of python3 if the command throws an error
source env/bin/activate
pip install -r requirements.txt
- Now start the app with the following commands.
cd src/
flask run
- Open a browser and navigate to localhost:8050, and you will see the dashboard.
- Run the following commands in Anaconda Prompt to create the environment.
cd covidash
conda env create -f environment_windows.yml
conda activate covid
- Now start the app with the following commands
cd src
python app.py
- Open a browser and navigate to localhost:8050, and you will see the dashboard.
- Follow the steps in the Linux/macOS section.
- Follow the steps in the Linux/macOS section.
- Run the following commands to start the docusaurus project and navigate to localhost:3000 on your browser.
cd covidocs
npm start
- All the visuals and the dashboard were built solely using Python.
- Plotly and Plotly Dash were the frameworks used to create the visualizations and make the web app.
- Keras is the framework used to make the predictive model (CNN) that forecasts the cases for the next seven days. We chose Keras as it offered the most flexibility along with ease of learning and experimentation.