datafinancemlspropertiesproptechreal-estaterealtorredfinredfin-scraperscraperscrapingwebscrapingzillowzillow-scraper
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| examples | ||
| homeharvest | ||
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| README.md | ||
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| pyproject.toml | ||
README.md
HomeHarvest is a simple, yet comprehensive, 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.
- Usage Modes:
- Python: For those who'd like to integrate scraping into their Python scripts.
- CLI: For users who prefer command-line operations.
Video Guide for HomeHarvest - updated for release v0.3.4
Installation
pip install 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",
# mls_only=True, # only fetch MLS listings
# proxy="http://user:pass@host:port" # use a proxy to change your IP address
)
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)
│
└── proxy (string): In format 'http://user:pass@host:port'
CLI
usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] [-c] location
Home Harvest Property Scraper
positional arguments:
location Location to scrape (e.g., San Francisco, CA)
options:
-l {for_sale,for_rent,sold,pending}, --listing_type {for_sale,for_rent,sold,pending}
Listing type to scrape
-o {excel,csv}, --output {excel,csv}
Output format
-f FILENAME, --filename FILENAME
Name of the output file (without extension)
-p PROXY, --proxy PROXY
Proxy to use for scraping
-d DAYS, --days DAYS Sold/listed in last _ days filter.
-r RADIUS, --radius RADIUS
Get comparable properties within _ (e.g., 0.0) miles. Only applicable for individual addresses.
-m, --mls_only If set, fetches only MLS listings.
homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
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
│ ├── sold_price
│ ├── last_sold_date
│ ├── price_per_sqft
│ └── hoa_fee
├── Location Details:
│ ├── latitude
│ ├── longitude
└── Parking Details:
└── parking_garage
Exceptions
The following exceptions may be raised when using HomeHarvest:
InvalidListingType- valid options:for_sale,for_rent,soldInvalidDate- date_from or date_to is not in the format YYYY-MM-DD
Frequently Asked Questions
Q: Encountering issues with your searches?
A: Try to broaden the parameters you're using. If problems persist, submit an issue.
Q: Received a Forbidden 403 response code?
A: This indicates that you have been blocked by Realtor.com for sending too many requests. We recommend:
- Waiting a few seconds between requests.
- Trying a VPN or using a proxy as a parameter to scrape_property() to change your IP address.