HomeHarvest is a real estate scraping library that extracts and formats data in the style of MLS listings.

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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 >= 3.9 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 (True/False): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
│
└── exclude_pending (True/False): If set, excludes pending properties from the results unless listing_type is 'pending'

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

├── Broker Info:
│ ├── broker
│ ├── broker_email
│ └── broker_website

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.