Weather Prediction Streamlit Web App

Weather prediction model predictions Web App Fronend made with Streamlit (for a cloud computing uni course - RSO).

Its a simple app that shows the value of the latest prediction and a graph of the last month predictions.

Running Locally

To run the application locally, follow these steps:

1. Install Dependencies:

   pip install -r requirements.txt

2. Set Google Application Credentials:

   export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your/credentials.json

3. Start Ray Serve Application:

   streamlit run streamlit_predict.py

Docker and GCP CloudRun Deployment

To deploy the application using Docker and Google Cloud Run, follow these steps:

1. Build the Docker Image Locally:

   docker build -t streamlit_wp_predict .

2. Run the Docker Image Locally for Testing:

   • This command runs the Docker container locally and sets the Google Cloud credentials.

   docker run -p 8080:8080 \
      -e GOOGLE_APPLICATION_CREDENTIALS=/tmp/keys/gcp_credentials.json \
      -v /path/to/your/credentials:/tmp/keys \
      streamlit_wp_predict

   Replace /path/to/your/credentials with the actual path to your Google Cloud credentials JSON file.

3. Authenticate with Google Cloud:

   gcloud auth login
   gcloud projects list --sort-by=projectId --limit=5
   gcloud config set project <project_id>
   gcloud auth configure-docker

4. Build and Tag the Image for Google Container Registry:

   docker build -t eu.gcr.io/<project_id>/streamlit_wp_predict:v1 .

5. Push the Docker Image to Google Container Registry:

   docker push eu.gcr.io/<project_id>/streamlit_wp_predict:v1

6. Deploy to Google Cloud Run:

   • Open the Google Cloud Console.
   • Navigate to Cloud Run.
   • Click on 'Create Service'.
   • Choose the image you just pushed.
   • Set any required configurations (like memory, CPU).
   • Deploy the image.