Usage 🔧

This project is made for the Python 3.11 version.

👉 You can delete this file before committing your project to GitHub.

How to run this project see the following steps:

1. Clone the project.
2. Build the Docker image locally (commands see below or in the Dockerfile).
3. Run the Docker container locally (commands see below or in the Dockerfile) and debug your streamlit app locally until you are ready to deploy to Streamlit Cloud.
4. Deploy the project to Streamlit Cloud and test it.

---

Python virtualenv setup for local development 🐍

If you don't want to use Docker for local development, you can also use a Python virtual environment. How to setup a Python virtual environment for local development:

1. Install virtualenv package

pip install --upgrade virtualenv

2. Make and activate virtual environment

python -m venv .venv

or

python3 -m venv .venv

On Windows

.venv\Scripts\activate

On macOS and Linux

source .venv/bin/activate

3. Install dependencies within the virtual environment

python -m pip install --upgrade pip
pip install --upgrade -r requirements.txt

4. Develop and test your streamlit app within the virtual environment

streamlit run streamlit_app.py

5. After development, deactivate virtual environment

deactivate

---

Dockerfile for local development 🐳

This template contains a Dockerfile for local debugging and testing of the project, before deploying the project to Streamlit Cloud. This shall ease the process of developing and deploying projects to Streamlit Cloud, without endless back-and-forth trial-and-error between the local development environment, GitHub and Streamlit Cloud.

The Dockerfile is based on python:3.11-slim image and shall mimic the Streamlit Cloud runtime as closely as possible.

Hint: If you run the Dockerfile locally on a Windows host system, you have to uncomment the [server] settings in the .streamlit/config.toml file. Comment on these lines again before deploying the project to Streamlit Cloud.

Docker commands 💻

To build the docker image locally, run the following command:

docker build -t dengue --progress=plain .

Then to run the docker container locally, run the following command:

docker run -p 8501:8501 dengue

👉 For more details, look into the Dockerfile file itself.

---

Streamlit Cloud deployment ☁️

To deploy the project to Streamlit Cloud, you have to create a new project on Streamlit Cloud and connect it to your GitHub repository. How to deploy a project to Streamlit Cloud see in the official documentation here.

---

Resources 📚

See also the official documentation from Streamlit about docker deployments:

https://docs.streamlit.io/knowledge-base/tutorials/deploy/docker

Model Performance Summary

District	Best Model	RMSE Score
Ampara	Random Forest with Co-variates	4.4
Anuradhapura	Random Forest	3
Badulla	Transformer Model	4.76
Batticaloa	Random Forest with Co-variates	5.3
Colombo	Regression M. with Co-variates	16
Galle	Regression Model	6.37
Gampaha	ARIMA	15
Hambantota	ARIMA	7.3
Jaffna	Catboost Model	8.79
Kalutara	Random Forest	13.3
Kandy	Transformer Model	11.6
Kegalle	LightGBM Model	11.38
Kilinochchi	Regression Model	1.27
Kurunegela	ARIMA	8.2
Mannar	Linear Regression Model	3
Matale	Linear Regression Model	4
Matara	Catboost	9.13
Monaragala	AutoARIMA	3.64
Mullaitivu	XGBModel	0.8
Nuwara Eliya	Catboost Model	1.6
Polonnaruwa	Transformer Model	1.96
Puttalam	RandomForest	3.37
Ratnapura	Transformer Model	34
Trincomalee	Random Forest with Co-variates	4.16
Vavuniya	RandomForest	0.92

Average RMSE: 7.3