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8 Commits
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@@ -2,14 +2,10 @@
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**HomeHarvest** is a simple, yet comprehensive, real estate scraping library that extracts and formats data in the style of MLS listings.
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[](https://replit.com/@ZacharyHampton/HomeHarvestDemo)
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**Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
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*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com)** *to work with us.*
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Check out another project we wrote: ***[JobSpy](https://github.com/Bunsly/JobSpy)** – a Python package for job scraping*
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## HomeHarvest Features
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- **Source**: Fetches properties directly from **Realtor.com**.
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@@ -92,7 +88,7 @@ Optional
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│ Example: 30 (fetches properties listed/sold in the last 30 days)
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│
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├── date_from, date_to (string): Start and end dates to filter properties listed or sold, both dates are required.
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} (use this to get properties in chunks as there's a 10k result limit)
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| (use this to get properties in chunks as there's a 10k result limit)
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│ Format for both must be "YYYY-MM-DD".
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│ Example: "2023-05-01", "2023-05-15" (fetches properties listed/sold between these dates)
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│
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@@ -193,7 +189,7 @@ The following exceptions may be raised when using HomeHarvest:
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**A:** This indicates that you have been blocked by Realtor.com for sending too many requests. We recommend:
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- Waiting a few seconds between requests.
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- Trying a VPN or useing a proxy as a parameter to scrape_property() to change your IP address.
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- Trying a VPN or using a proxy as a parameter to scrape_property() to change your IP address.
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---
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@@ -34,6 +34,8 @@ class Address:
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@dataclass
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class Description:
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primary_photo: str | None = None
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alt_photos: list[str] | None = None
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style: str | None = None
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beds: int | None = None
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baths_full: int | None = None
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@@ -84,6 +84,12 @@ class RealtorScraper(Scraper):
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garage
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permalink
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}
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primary_photo {
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href
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}
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photos {
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href
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}
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}
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}"""
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@@ -152,6 +158,8 @@ class RealtorScraper(Scraper):
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else None,
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address=self._parse_address(property_info, search_type="handle_listing"),
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description=Description(
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primary_photo=property_info["primary_photo"].get("href", "").replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75"),
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alt_photos=self.process_alt_photos(property_info.get("photos", [])),
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style=property_info["basic"].get("type", "").upper(),
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beds=property_info["basic"].get("beds"),
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baths_full=property_info["basic"].get("baths_full"),
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@@ -247,6 +255,12 @@ class RealtorScraper(Scraper):
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units
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year_built
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}
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primary_photo {
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href
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}
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photos {
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href
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}
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}
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}"""
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@@ -334,6 +348,12 @@ class RealtorScraper(Scraper):
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name
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}
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}
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primary_photo {
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href
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}
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photos {
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href
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}
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}
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}
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}"""
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@@ -553,6 +573,11 @@ class RealtorScraper(Scraper):
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"radius": "{}mi".format(self.radius),
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}
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elif location_type == "postal_code":
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search_variables |= {
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"postal_code": location_info.get("postal_code"),
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}
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else: #: general search, location
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search_variables |= {
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"city": location_info.get("city"),
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@@ -621,6 +646,7 @@ class RealtorScraper(Scraper):
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@staticmethod
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def _parse_description(result: dict) -> Description:
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description_data = result.get("description", {})
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if description_data is None or not isinstance(description_data, dict):
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@@ -630,7 +656,16 @@ class RealtorScraper(Scraper):
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if style is not None:
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style = style.upper()
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primary_photo = ""
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if result and "primary_photo" in result:
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primary_photo_info = result["primary_photo"]
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if primary_photo_info and "href" in primary_photo_info:
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primary_photo_href = primary_photo_info["href"]
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primary_photo = primary_photo_href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
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return Description(
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primary_photo=primary_photo,
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alt_photos=RealtorScraper.process_alt_photos(result.get("photos")),
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style=style,
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beds=description_data.get("beds"),
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baths_full=description_data.get("baths_full"),
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@@ -643,6 +678,7 @@ class RealtorScraper(Scraper):
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stories=description_data.get("stories"),
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)
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@staticmethod
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def calculate_days_on_mls(result: dict) -> Optional[int]:
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list_date_str = result.get("list_date")
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@@ -661,3 +697,16 @@ class RealtorScraper(Scraper):
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days = (today - list_date).days
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if days >= 0:
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return days
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@staticmethod
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def process_alt_photos(photos_info):
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try:
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alt_photos = []
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if photos_info:
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for photo_info in photos_info:
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href = photo_info.get("href", "")
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alt_photo_href = href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
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alt_photos.append(alt_photo_href)
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return alt_photos
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except Exception:
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pass
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@@ -31,6 +31,8 @@ ordered_properties = [
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"stories",
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"hoa_fee",
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"parking_garage",
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"primary_photo",
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"alt_photos",
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]
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@@ -49,6 +51,8 @@ def process_result(result: Property) -> pd.DataFrame:
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prop_data["price_per_sqft"] = prop_data["prc_sqft"]
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description = result.description
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prop_data["primary_photo"] = description.primary_photo
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prop_data["alt_photos"] = ", ".join(description.alt_photos)
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prop_data["style"] = description.style
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prop_data["beds"] = description.beds
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prop_data["full_baths"] = description.baths_full
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@@ -1,6 +1,6 @@
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[tool.poetry]
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name = "homeharvest"
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version = "0.3.9"
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version = "0.3.11"
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description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
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authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
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homepage = "https://github.com/Bunsly/HomeHarvest"
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