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mortgage-calc

mortgage-calc is a Django + vanilla async Javascript calculator to help potential home buyers understand whether it makes sense to buy a house. It is hosted at MortgageROI.com.

Many mortgage calculators are overly simplistic, returning to the user a simple 'buy or rent' determination without any context (e.g., why is my return higher if I keep my home for 10 years v. 2 years? why does a higher down payment help in some cases and hurt in others? what is more important for my return, home appreciation or the rent I save?).

This calculator seeks to show the user a return and the drivers of that return.

Would love any feedback, pull requests, etc.

Getting Started

Requirements: Python 3

Getting set up locally is simple. Once you've cloned the project:

  1. Run pip install requirements.txt
  2. Set up a local_settings.py file and drop it in the mortgage/ folder where the settings.py file lives
# local_settings.py

import os

# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))

# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '[YOUR_SECRET_KEY]'

# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
SECURE_SSL_REDIRECT = False

DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.sqlite3',
        'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
    }
}
  1. Run python3 manage.py migrate

Running the tests

My goal with this project is to have 100% test coverage server-side.

You may notice hard-coded values throughout the tests, e.g., self.assertEqual(response_dict['base_irr'][30], 5.37) -- since the final outcomes are reliant on so many calculations that would be tedious to recreate in tests, I've created a separate Google Sheet as a testing reference that contains the target outputs.

coverage run --source='.' manage.py test runs tests

coverage html generates the coverage files

Built With

Author

Garrett Edel LinkedIn

License

MIT License

Copyright (c) 2018 Garrett Edel

See LICENSE.txt file for details