- Make sure all requirements are installed
- If not, run
pip install -r requirements.txt
- If not, run
- run
python scraper.py
on command line. This is written in python 3 so check your version. - You will be prompted for a unique search ID. This is the ID associated with the specific map or search region you're looking at. Examples may include:
- ?sk=115ada7c860d92c4bc132f69f6ac8e45&bb=33imuxg3vHz4y4lC
- new-york-ny
- If the extension used is a unique search region or polygon search, like the former, input 1 when prompted. Otherwise input 0.
- Output is put into a csv file with user input file name in the directory in which you're running the script. Leave out the extension when entering the file name (
test
rather thantest.csv
) - If there are any errors they will be printed at the end of the script.
Field | Notes |
---|---|
address | full street address of the property |
unit | unit number - will be N/A if not found, often properties list it as 1 bed/1 bath rather than actual number |
beds | number of bedrooms |
baths | number of bathrooms |
rent | monthly rent - if there is a range given the average of the range is taken |
sqft | square footage of the apartment |
avail | availability. 0 if unavailable, 1 if available, 2 if will be available at a future date |
pets | pet policies. given as a semicolon separated list |
parking | parking available at property |
built | year in which building was built |
renovated | year building renovated if applicable |
num_units | number of units in the building |
stories | number of floors in the building |
fitness | fitness facilities available |
outdoor | outdoor space available |
- Send requests through rotating proxy
- Integrate into server as backend for web app