If you don't have the model from the previous chapter, run 05-deploy.ipynb
to generate the pickle file.
First, install flask:
pip install flask
Run the service:
python churn_serving.py
Test it from python:
import requests
url = 'http://localhost:9696/predict'
response = requests.post(url, json=customer)
result = response.json()
Install pipenv
:
pip install pipenv
Install the depencencies from the Pipfile:
pipenv install
Enter the pipenv virtual environment:
pipenv shell
And run the code:
python churn_serving.py
Alternatively, you can do both steps with one command:
pipenv run python churn_serving.py
Now you can use the same code for testing the model locally.
Build the image (defined in Dockerfile)
docker build -t churn-prediction .
Run it:
docker run -it -p 9696:9696 churn-prediction:latest