Zoopla

A python wrapper for the Zoopla API.


Project maintained by AnthonyBloomer Hosted on GitHub Pages — Theme by mattgraham

zoopla

A python wrapper for the Zoopla API.

Zoopla has launched an open API to allow developers to create applications using hyper local data on 27m homes, over 1m sale and rental listings, and 15 years of sold price data.

Register for a user account and apply for an instant API key.

Browse the documentation to understand how to use the API and the specifications for the individual APIs.

Installation

pip install zoopla

Tests

Install the dev requirements:

pip install -r dev-requirements.txt

Run py.test with your developer key (otherwise you won’t be able to hit the live API upon which these tests depend).

py.test --api-key=<you-api-key> tests/

Examples

Retrieve property listings for a given area.

from zoopla import Zoopla

zoopla = Zoopla(api_key='your_api_key')

search = zoopla.property_listings({
    'maximum_beds': 2,
    'page_size': 100,
    'listing_status': 'sale',
    'area': 'Blackley, Greater Manchester'
})

for result in search.listing:
    print(result.price)
    print(result.description)
    print(result.image_url)

Retrieve a list of house price estimates for the requested area.

zed_indices = zoopla.area_zed_indices({
    'area': 'Blackley, Greater Manchester',
    'output_type': 'area',
    'area_type': 'streets',
    'order': 'ascending',
    'page_number': 1,
    'page_size': 10
})

print(zed_indices.town)
print(zed_indices.results_url)

Generate a graph of values for an outcode over the previous 3 months and return the URL to the generated image.

area_graphs = zoopla.area_value_graphs({'area': 'SW11'})

print(area_graphs.average_values_graph_url)
print(area_graphs.value_trend_graph_url)

Retrieve the average sale price for houses in a particular area.

average = zoopla.average_area_sold_price({'area': 'SW11'})

print(average.average_sold_price_7year)
print(average.average_sold_price_5year)