This project encapsulates a microservice that calculates the risk of the customer based on information given from a POST request coming from a Form.

You may use it as a boilerplate for a microservice that handles api requests and returns the result with a DB registry holding the operation.
This code can be used as it's open source

Technologies used:

• Python
• Flask
• Python-dotenv
• Flask-pymongo
• Dnspython
• MongoDB Atlas
• Pipenv

Configuration:

After cloning the repository, install the dependencies:

pip install

or

pipenv install

Then proceed with the creation of your .Env file to store your environment variables, for Flask and MongoDB Atlas:

# .env File:

MONGO_URI_BASE=mongodb+srv://
# Keep the : after the user-name for concatenation
MONGO_USER=<your_username>:
MONGO_PASS=<your_pass>
MONGO_CLUSTER=@<your Cluster Name>.mongodb.net/
MONGO_DBNAME=<your desired database name>
MONGO_DBOPTIONS=?retryWrites=true&w=majority

# .flaskenv File:

FLASK_APP=app
FLASK_RUN_PORT=<your_desired_port>
FLASK_ENV=development

Usage:

If you want to test using the structure designed for this solution here's the Json Source-Code:

This input:

{
  "age": 35,
  "dependents": 2,
  "house": {"ownership_status": "owned"},
  "income": 0,
  "marital_status": "married",
  "risk_questions": [0, 1, 0],
  "vehicle": {"year": 2018}
}

Should output:

{
  "auto": "regular",
  "disability": "ineligible",
  "home": "economic",
  "life": "regular"
}

Run the server by using:

flask run

or

python \run.py

Screens:

I've added to the user model at the Database the new entity risk, which will hold all the information of the algorithm passage

Here's the Insomnia settings used for this test, the entry-point for the route tested is:

baseurl/api/user/application

Important: This should be used with an operator linking to the user model, so it should be a variable endpoint at a more refined solution. Expand with that in mind.