datafinancemlspropertiesproptechreal-estaterealtorredfinredfin-scraperscraperscrapingwebscrapingzillowzillow-scraper
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- updated docs - classified exception |
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.github/workflows | ||
examples | ||
homeharvest | ||
tests | ||
.gitignore | ||
.pre-commit-config.yaml | ||
LICENSE | ||
README.md | ||
poetry.lock | ||
pyproject.toml |
README.md
HomeHarvest is a real estate scraping library that extracts and formats data in the style of MLS listings.
Not technical? Try out the web scraping tool on our site at tryhomeharvest.com.
Looking to build a data-focused software product? Book a call to work with us.
HomeHarvest Features
- Source: Fetches properties directly from Realtor.com.
- Data Format: Structures data to resemble MLS listings.
- Export Flexibility: Options to save as either CSV or Excel.
Video Guide for HomeHarvest - updated for release v0.3.4
Installation
pip install -U homeharvest
Python version >= 3.10 required
Usage
Python
from homeharvest import scrape_property
from datetime import datetime
# Generate filename based on current timestamp
current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"HomeHarvest_{current_timestamp}.csv"
properties = scrape_property(
location="San Diego, CA",
listing_type="sold", # or (for_sale, for_rent, pending)
past_days=30, # sold in last 30 days - listed in last 30 days if (for_sale, for_rent)
# date_from="2023-05-01", # alternative to past_days
# date_to="2023-05-28",
# foreclosure=True
# mls_only=True, # only fetch MLS listings
)
print(f"Number of properties: {len(properties)}")
# Export to csv
properties.to_csv(filename, index=False)
print(properties.head())
Output
>>> properties.head()
MLS MLS # Status Style ... COEDate LotSFApx PrcSqft Stories
0 SDCA 230018348 SOLD CONDOS ... 2023-10-03 290110 803 2
1 SDCA 230016614 SOLD TOWNHOMES ... 2023-10-03 None 838 3
2 SDCA 230016367 SOLD CONDOS ... 2023-10-03 30056 649 1
3 MRCA NDP2306335 SOLD SINGLE_FAMILY ... 2023-10-03 7519 661 2
4 SDCA 230014532 SOLD CONDOS ... 2023-10-03 None 752 1
[5 rows x 22 columns]
Parameters for scrape_property()
Required
├── location (str): The address in various formats - this could be just a zip code, a full address, or city/state, etc.
└── listing_type (option): Choose the type of listing.
- 'for_rent'
- 'for_sale'
- 'sold'
- 'pending'
Optional
├── radius (decimal): Radius in miles to find comparable properties based on individual addresses.
│ Example: 5.5 (fetches properties within a 5.5-mile radius if location is set to a specific address; otherwise, ignored)
│
├── past_days (integer): Number of past days to filter properties. Utilizes 'last_sold_date' for 'sold' listing types, and 'list_date' for others (for_rent, for_sale).
│ Example: 30 (fetches properties listed/sold in the last 30 days)
│
├── date_from, date_to (string): Start and end dates to filter properties listed or sold, both dates are required.
| (use this to get properties in chunks as there's a 10k result limit)
│ Format for both must be "YYYY-MM-DD".
│ Example: "2023-05-01", "2023-05-15" (fetches properties listed/sold between these dates)
│
├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
│
├── foreclosure (True/False): If set, fetches only foreclosures
│
└── proxy (string): In format 'http://user:pass@host:port'
│
└── extra_property_data (bool): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
Property Schema
Property
├── Basic Information:
│ ├── property_url
│ ├── mls
│ ├── mls_id
│ └── status
├── Address Details:
│ ├── street
│ ├── unit
│ ├── city
│ ├── state
│ └── zip_code
├── Property Description:
│ ├── style
│ ├── beds
│ ├── full_baths
│ ├── half_baths
│ ├── sqft
│ ├── year_built
│ ├── stories
│ └── lot_sqft
├── Property Listing Details:
│ ├── days_on_mls
│ ├── list_price
│ ├── list_date
│ ├── pending_date
│ ├── sold_price
│ ├── last_sold_date
│ ├── price_per_sqft
│ ├── parking_garage
│ └── hoa_fee
├── Location Details:
│ ├── latitude
│ ├── longitude
│ ├── nearby_schools
├── Agent Info:
│ ├── agent
│ ├── agent_email
│ └── agent_phone
Exceptions
The following exceptions may be raised when using HomeHarvest:
InvalidListingType
- valid options:for_sale
,for_rent
,sold
InvalidDate
- date_from or date_to is not in the format YYYY-MM-DD.AuthenticationError
- Realtor.com token request failed.