Lending Club

A loan prediction tool based on a machine learning model using lending club data inspired by a Kaggle notebook

Skeleton using fast-api and docker inspired by Testdriven.io course and this fastapi/ml template.

Requirements

Python 3.6+

Installation

Install the required packages in your local environment (ideally virtualenv, conda, etc.).

pip install -r requirements

Setup

1. Duplicate the .env.example file and rename it to .env

2. In the .env file configure the API_KEY entry. The key is used for authenticating our API.
   A sample API key can be generated using Python REPL:

import uuid
print(str(uuid.uuid4()))

Run It

1. Start your app with:

uvicorn app.main:app

2. Go to http://localhost:8000/docs.

3. Click Authorize and enter the API key as created in the Setup step.

4. You can use the sample payload from the docs/loan_payload.json file when trying out the model using the API.

Run Tests

If you're not using tox, please install with:

pip install tox

Run your tests with:

tox

This runs tests and coverage for Python 3.6 and Flake8, Autopep8, Bandit.