README

This project is about easily finding out how much a rental property's price had declined since its peak price prior to pandemic lockdowns.

Get Started

To run this project, open crawler.ipynb as a Jupyter Notebook, and run reach cell.

Parameters

A cell near the top of crawler.ipynb contains the following parameters:

• __from_cache_file - if True, the crawler will take html from the specified cache file rather than request html from the internet.
• __targets - the source of target addresses
• __cache_dir - the location of cached html
• __data_output_file - name of the output file
• __output_dir = directory for any and all output that is written to file

Files and Folders

• crawler.ipynb does all the work
• the file specified by __targets should contain a line for each of the properties you are interested in checking. Data is the format:

    <unit #>/<street number> <street name>, 
    <suburb>, 
    <state(2-3 letter abbreviation)> <postcode>; 
    <advertised price($)>; 
    <number of bedrooms>; 
    <is this an NRAS property? (y/n)>

• • Note: Each entry should be on a single line. The above is broken over several lines for readability
  • Example:
    301/4 Pretend Place, Newtown, NSW 2067; 290; 1; y