Skip to main content

Zillow scraper in Python

Overview

This project is an open-source tool developed in Python for extracting product information from Zillow. It's designed to be easy to use, making it an ideal solution for developers looking for Zillow product data.

Features

  • Full search support
  • Extracts detailed product information from Zillow
  • Implemented in Python just because it's popular
  • Easy to integrate with existing Python projects

Important

  • Use rotating residential proxies, zillow will block if you make multiple requests with the same IP,

Install

$ pip install pyzill

Examples

import pyzill
import json
ne_lat = 38.602951833355434
ne_long = -87.22283859375
sw_lat = 23.42674607019482
sw_long = -112.93084640625
pagination = 1
#pagination is for the list that you see at the right when searching
#you don't need to iterate over all the pages because zillow sends the whole data on mapresults at once on the first page
#however the maximum result zillow returns is 500, so if mapResults is 500
#try playing with the zoom or moving the coordinates, pagination won't help because you will always get at maximum 500 results
pagination = 1
proxy_url = pyzill.parse_proxy("[proxy_ip or proxy_domain]","[proxy_port]","[proxy_username]","[proxy_password]")
results_sold = pyzill.sold(pagination, 
              search_value="miami",
              min_beds=1,max_beds=1,
              min_bathrooms=None,max_bathrooms=None,
              min_price=10000,max_price=None,
              ne_lat=ne_lat,ne_long=ne_long,sw_lat=sw_lat,sw_long=sw_long,
              zoom_value=5,
              proxy_url=proxy_url)
              
results_sale = pyzill.for_sale(pagination, 
              search_value="",
              min_beds=None,max_beds=None,
              min_bathrooms=3,max_bathrooms=None,
              min_price=None,max_price=None,
              ne_lat=ne_lat,ne_long=ne_long,sw_lat=sw_lat,sw_long=sw_long,
              zoom_value=10,
              proxy_url=proxy_url)

results_rent = pyzill.for_rent(pagination, 
              search_value="",is_entire_place=False,is_room=True,
              min_beds=1,max_beds=None,
              min_bathrooms=None,max_bathrooms=None,
              min_price=10000,max_price=None,
              ne_lat=ne_lat,ne_long=ne_long,sw_lat=sw_lat,sw_long=sw_long,
              zoom_value=15,
              proxy_url=proxy_url)
jsondata_sold = json.dumps(results_sold)
jsondata_sale = json.dumps(results_sale)
jsondata_rent = json.dumps(results_rent)
f = open("./jsondata_sold.json", "w")
f.write(jsondata_sold)
f.close()
f = open("./jsondata_sale.json", "w")
f.write(jsondata_sale)
f.close()
f = open("./jsondata_rent.json", "w")
f.write(jsondata_rent)
f.close()

For homes

import pyzill
import json
property_url="https://www.zillow.com/homedetails/858-Shady-Grove-Ln-Harrah-OK-73045/339897685_zpid/"
proxy_url = pyzill.parse_proxy("[proxy_ip or proxy_domain]","[proxy_port]","[proxy_username]","[proxy_password]")
data = pyzill.get_from_home_url(property_url,proxy_url)
jsondata = json.dumps(data)
f = open("details.json", "w")
f.write(jsondata)
f.close()
import pyzill
import json
property_id=2056016566
proxy_url = pyzill.parse_proxy("[proxy_ip or proxy_domain]","[proxy_port]","[proxy_username]","[proxy_password]")
data = pyzill.get_from_home_id(property_id,proxy_url)
jsondata = json.dumps(data)
f = open("details.json", "w")
f.write(jsondata)
f.close()

For departments

import pyzill
import json
property_url="https://www.zillow.com/apartments/kissimmee-fl/the-nexus-at-overbrook/9DSWrh/"
proxy_url = pyzill.parse_proxy("[proxy_ip or proxy_domain]","[proxy_port]","[proxy_username]","[proxy_password]")
data = pyzill.get_from_deparment_url(property_url,proxy_url)
jsondata = json.dumps(data)
f = open("details.json", "w")
f.write(jsondata)
f.close()
import pyzill
import json
property_id="CgKZT4"
proxy_url = pyzill.parse_proxy("[proxy_ip or proxy_domain]","[proxy_port]","[proxy_username]","[proxy_password]")
data = pyzill.get_from_deparment_id(property_id,proxy_url)
jsondata = json.dumps(data)
f = open("details.json", "w")
f.write(jsondata)
f.close()

Metadata

Release files for pyzill 1.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyzill 1.0.3
File Size Uploaded Provenance Actions
pyzill-1.0.3.tar.gz 7.9 kB Without provenance Details for pyzill-1.0.3.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for pyzill 1.0.3
File Interpreter ABI Platform Actions
pyzill-1.0.3-py3-none-any.whl Python 3 none any Details for pyzill-1.0.3-py3-none-any.whl

Total release size: 15.9 kB

Release files / pyzill-1.0.3.tar.gz

Download URL pyzill-1.0.3.tar.gz
Size 7.9 kB
Tags Source
SHA-256 checksum
How to use checksums
0e3e947229f0efc9fcb973d48a81eb79cd0408ccf65b232b325e48a136dc9021
BLAKE2b-256 checksum
How to use checksums
6ba54042b8c8f38379b889755a51e79b05f9743a4dbcc3face80e9a6ebf14af9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.3

Release files / pyzill-1.0.3-py3-none-any.whl

Download URL pyzill-1.0.3-py3-none-any.whl
Size 8.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3e3bab66d23dedfbac3ed11c13f535ddce28434298ab981f6197dc48c025eae6
BLAKE2b-256 checksum
How to use checksums
c22dcd602205af00992803516d8feec85ae319625d23cf9954ce4892400f3a29
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.3

Security for pyzill 1.0.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page