In this project, we used regression model and imported dataset from kaggle to train it. We used Flask to build a light-weight web framework to predict the future population in China. And then we deploy our service in GCP and used locust to load test it.

The introduction video of our project: https://youtu.be/zTXA0Jn-ezI

1. Clone the repo

[email protected]:xzhnshng/IDS721-group-project.git

2. Create & enter python virtual environment

# first cd to the project directory
# create virtual environment
python -m venv env

# enter the virtual environment
source env/bin/activate

3. Setup - Install the required packages

make all

4. Train the model

python model.py

5. Run the application

python main.py

The dataset is from https://www.kaggle.com/datasets/anandhuh/population-data-china

# create image
docker build -t population-predictor:latest .

# create and run container
docker run --rm -p 5000:5000 --name population-predictor-app population-predictor:latest

Now you can access service on http://127.0.0.1:5000/

1. Create a new project and check if the project correct and set working project if not. In this step you need to record the , which will be used in next steps:

   gcloud projects describe $GOOGLE_CLOUD_PROJECT
   

   gcloud config set project $GOOGLE_CLOUD_PROJECT 
   

2. Paste command below on the GCP shell:

git clone [email protected]:xzhnshng/IDS721-group-project.git

3. In the project folder, build the containerized flask application image:

   gcloud builds submit --tag gcr.io/<PROJECT-ID>/app 
   

4. Last step, deploy the image on the cloud run service:

gcloud run deploy --image gcr.io/<PROJECT-ID>/app --platform managed

And you will need to name your service and select region you want to deploy.

Lastly, you can see the service running on the given URL:

I used https://locust.io/ to start load testing for the flask project.

1. Download locust

   pip3 install locust
   

2. Write locustfile.py:

   import time
   from locust import HttpUser, task, between
   
   class QuickstartUser(HttpUser):
   
       @task
       def submitForm(self):
           self.client.post("/predict", {"Year":"2024"})
   

3. Run "locust". Once you’ve started Locust, open up a browser and point it to http://localhost:8089. You will be greeted with something like this:

4. Here is our test result.