Project with intention to provide various financial modelling efforts, as well as machine learning models that can provide a benchmark of trained predicted stock price mechanisms.

The following guide explains how to set up and run OptiML project locally on your machine. (Installing prerequisites, running locally or on Kubernetes using Docker and Minikube)

• Python 3.12+ (for local dev)
• Docker (Download & Install)
• kubectl (Install Guide)
• Minikube (Install Guide)

Or, to just clone the Project Repo by itself using Git

• in this case, just skip to Section 3: Clone the Project Repo

1. Install Docker
   • Mac:
     • Download Docker Desktop from here
   • Linux:
     • Use your distribution's package manager
   • Windows:
     • Download Docker Desktop for Windows
2. Install kubectl

   • On Mac (via Homebrew):

     brew install kubectl
     

     • else: follow the official instructions here
3. Install Minikube
   • On Mac (via Homebrew):
     • brew install minikube
     • else: follow the official minikube docs here

1. Build Docker Image

docker build -t <your-dockerhub-username>/optiml:latest .

3. Run the Image

docker run -p 8501:8501 <your-dockerhub-username>/optiml:latest

3. Visit http://localhost:8501 in your browser

1. Start Minikube

minikube start

2. Build the Docker image and Push to Docker Hub

docker build -t <your-dockerhub-username>/optiml:latest .
docker push <your-dockerhub-username>/optiml:latest

⚠️ Ensure image: <your-dockerhub-username>/optiml:latest in your deployment YAML matches this tag.

3. Apply Kubernetes Manifests

kubectl apply -f k8s/deployment.yaml
kubectl apply -f k8s/service.yaml

4. Access the app

minikube service optiml-app-service

This command automatically opens browser to the running app

5. 🔧 Troubleshooting and Additional Notes

• Image Not Updating? 🤔 Remember to rebuild and push Docker image after any code change, then use

  kubectl rollout restart deployment optiml-app
  

  to refresh the apop in Kubernetes

• Check Pod Status:

kubectl get pods
kubectl describe pod <pod-name>

• Requirements: All Python requirements are in requirements.txt
• File Structure Example:

optiml/
├── streamlit_app.py
├── requirements.txt
├── Dockerfile
├── k8s/
│   ├── deployment.yaml
│   └── service.yaml
├── app/
└── utils/

6. Environment Cleanup Do this when you want to stop running the app

• Minikube

minikube stop
minikube delete

• Kubernetes resources

kubectl delete -f k8s/deployment.yaml
kubectl delete -f k8s/service.yaml

7. *Updating the App

Skip this if plainly running app After code changes:

1. Rebuild and push Docker image
2. Restart deployment or re-apply yaml
3. Pull latest code on cluster if using CI/CD efforts Full processes and commands can be found in UPDATE_PROCESS.txt within project files.

1. Clone the Project in your console or IDE terminals

git clone https://github.com/Kazurl/OptiML.git
cd optiml

2. Set up virtual environment (recommended)

source venv/bin/activate  # mac/linux
# or
.\venv\Scripts\activate  # Windows

3. Install dependencies

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

4. Run the Streamlit app

streamlit run streamlit_app.py

5. Automatically opened in browser at http://localhost:8501