Rent Scout – Investing with Python

I started a new project on github rent_scout where I will be using python as a tool to explore real estate investing. My current plan goes as follows: Use python to scrape the web for properties to sell, rent in a given area, and as much data about the real costs of purchasing a property as a rental. The plan will revolve around the idea of trying to use readily available information to try to find markets and properties that would turn the largest guaranteed return on investment.

Real estate investing is a good hedge against inflation and can be largely done with the banks money. Ideally every property would be cashflow positive from day one but that might not be possible. The plan is to build a tool that models real estate investments and can offer some metric to assist in investing in the best the market has to offer at the best times. I know there are always risks in investing and that no model can be completely trusted, but I believe that by understanding as much as I can about the process I can gain a real advantage over other small time real estate inverters.

The plan would then be to find properties that could be purchased as long term investments, handed over to a good property management company, and ideally in 15-30 years you would have a property that you could sell. The reason for this is there are many costs involved in each real estate transaction and unless I got into a really bad deal it would make more sense to ride out anything the market does so long as I can generate enough from rent to pay off the property. Then once the property is paid off I would have real passive income.

The first thing to model is house prices and rent prices. The next step is building a tool that can scrape the web for this information. To start I’ve written a simple python script to calculate the monthly payment of a loan and the total cost of that loan. Once I have rent and housing prices I need to do some digging to find out all the real costs in owning a home and renting (including what good property management companies are available in the market I’m researching). I need to find out the tax codes in each state and area I’m interested in and build that into the model. I need to model the tax benefits of paying interest and so forth. Here are my next steps:

  1. Costs of owning a home (ask friends, read books, google, etc.)
  2. Hidden costs of mortgages and how to get the best mortgage
  3. Web scraper for houses listed in an area and their attributes
  4. Web scraper for rental prices and availability (supply) in a market
  5. Research what makes rentals more desirable

Leave a Reply

Your email address will not be published. Required fields are marked *