ML model based on Somerville Happiness Survey Data Set.
- create virtual environment:
python -m venv .venv
- install dependencies:
poetry install --no-root
- launch backend:
poetry run uvicorn src.app.main:app --port=8080 --reload
- launch front-end:
poetry run streamlit run src/streamlit/ui.py --server.port 8501
- pre-commit:
poetry run pre-commit run --all-files
- unit tests:
poetry run pytest
- docker backend:
docker build -t backend-image -f Dockerfile.backend .
docker run --name backend-container -p 8080:8080 --rm backend-image
- docker frontend:
docker build -t frontend-image -f Dockerfile.frontend .
docker run --name frontend-container -p 8501:8501 --rm frontend-image
- docker compose:
docker compose build
docker compose up