Iris_ml_project/docs/getting-started.md

Getting Started

Prerequisites

• Docker
• Python 3.7+

Installation

1. Clone the repository
2. Build the Docker image:

docker build -t iris-ml-predictor .

3. Run the container:

docker run -p 8000:8000 iris-ml-predictor

Development

To set up a development environment:

1. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

3. Run the application:

uvicorn main:app --reload

The application will be available at http://localhost:8000.

Testing

Run the tests using:

pytest test_integration.py test_unit.py

Deployment

The application includes a GitHub Actions workflow for CI/CD in the .github/workflows/deploy.yml file.