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https://github.com/Bunsly/HomeHarvest.git
synced 2026-03-04 19:44:29 -08:00
Add flexible listing_type support and last_update_date field
- Add support for str, list[str], and None as listing_type values - Single string: maintains backward compatibility (e.g., "for_sale") - List of strings: returns properties matching ANY status (OR logic) - None: returns all property types (omits status filter) - Expand ListingType enum with all GraphQL HomeStatus values - Add OFF_MARKET, NEW_COMMUNITY, OTHER, READY_TO_BUILD - Add last_update_date field support - Add to GraphQL query, Property model, and processors - Add to sort validation and datetime field sorting - Field description: "Last time the home was updated" - Update GraphQL query construction to support status arrays - Single type: status: for_sale - Multiple types: status: [for_sale, sold] - None: omit status parameter entirely - Update validation logic to handle new parameter types 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
@@ -8,7 +8,7 @@ from typing import Union, Optional, List
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def scrape_property(
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location: str,
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listing_type: str = "for_sale",
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listing_type: str | list[str] | None = None,
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return_type: str = "pandas",
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property_type: Optional[List[str]] = None,
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radius: float = None,
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@@ -47,7 +47,9 @@ def scrape_property(
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Scrape properties from Realtor.com based on a given location and listing type.
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:param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
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:param listing_type: Listing Type (for_sale, for_rent, sold, pending)
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:param listing_type: Listing Type - can be a string, list of strings, or None.
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Options: for_sale, for_rent, sold, pending, off_market, new_community, other, ready_to_build
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Examples: "for_sale", ["for_sale", "pending"], None (returns all types)
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:param return_type: Return type (pandas, pydantic, raw)
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:param property_type: Property Type (single_family, multi_family, condos, condo_townhome_rowhome_coop, condo_townhome, townhomes, duplex_triplex, farm, land, mobile)
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:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
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@@ -73,7 +75,7 @@ def scrape_property(
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:param price_min, price_max: Filter by listing price
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:param lot_sqft_min, lot_sqft_max: Filter by lot size
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:param year_built_min, year_built_max: Filter by year built
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:param sort_by: Sort results by field (list_date, sold_date, list_price, sqft, beds, baths)
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:param sort_by: Sort results by field (list_date, sold_date, list_price, sqft, beds, baths, last_update_date)
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:param sort_direction: Sort direction (asc, desc)
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"""
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validate_input(listing_type)
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@@ -88,9 +90,17 @@ def scrape_property(
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)
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validate_sort(sort_by, sort_direction)
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# Convert listing_type to appropriate format
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if listing_type is None:
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converted_listing_type = None
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elif isinstance(listing_type, list):
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converted_listing_type = [ListingType(lt.upper()) for lt in listing_type]
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else:
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converted_listing_type = ListingType(listing_type.upper())
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scraper_input = ScraperInput(
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location=location,
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listing_type=ListingType(listing_type.upper()),
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listing_type=converted_listing_type,
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return_type=ReturnType(return_type.lower()),
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property_type=[SearchPropertyType[prop.upper()] for prop in property_type] if property_type else None,
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proxy=proxy,
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@@ -13,7 +13,7 @@ from pydantic import BaseModel
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class ScraperInput(BaseModel):
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location: str
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listing_type: ListingType
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listing_type: ListingType | list[ListingType] | None
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property_type: list[SearchPropertyType] | None = None
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radius: float | None = None
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mls_only: bool | None = False
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@@ -43,6 +43,10 @@ class ListingType(Enum):
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FOR_RENT = "FOR_RENT"
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PENDING = "PENDING"
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SOLD = "SOLD"
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OFF_MARKET = "OFF_MARKET"
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NEW_COMMUNITY = "NEW_COMMUNITY"
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OTHER = "OTHER"
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READY_TO_BUILD = "READY_TO_BUILD"
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class PropertyType(Enum):
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@@ -193,6 +197,7 @@ class Property(BaseModel):
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pending_date: datetime | None = Field(None, description="The date listing went into pending state")
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last_sold_date: datetime | None = Field(None, description="Last time the Home was sold")
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last_status_change_date: datetime | None = Field(None, description="Last time the status of the listing changed")
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last_update_date: datetime | None = Field(None, description="Last time the home was updated")
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prc_sqft: int | None = None
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new_construction: bool | None = Field(None, description="Search for new construction homes")
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hoa_fee: int | None = Field(None, description="Search for homes where HOA fee is known and falls within specified range")
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@@ -46,9 +46,17 @@ class RealtorScraper(Scraper):
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super().__init__(scraper_input)
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def handle_location(self):
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# Get client_id from listing_type
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if self.listing_type is None:
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client_id = "for-sale"
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elif isinstance(self.listing_type, list):
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client_id = self.listing_type[0].value.lower().replace("_", "-") if self.listing_type else "for-sale"
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else:
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client_id = self.listing_type.value.lower().replace("_", "-")
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params = {
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"input": self.location,
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"client_id": self.listing_type.value.lower().replace("_", "-"),
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"client_id": client_id,
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"limit": "1",
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"area_types": "city,state,county,postal_code,address,street,neighborhood,school,school_district,university,park",
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}
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@@ -134,14 +142,25 @@ class RealtorScraper(Scraper):
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date_param = ""
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# Determine date field based on listing type
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if self.listing_type == ListingType.SOLD:
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date_field = "sold_date"
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elif self.listing_type in [ListingType.FOR_SALE, ListingType.FOR_RENT]:
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date_field = "list_date"
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else: # PENDING
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# Skip server-side date filtering for PENDING as both pending_date and contract_date
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# filters are broken in the API. Client-side filtering will be applied later.
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date_field = None
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# Convert listing_type to list for uniform handling
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if self.listing_type is None:
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listing_types = []
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date_field = None # When no listing_type is specified, skip date filtering
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elif isinstance(self.listing_type, list):
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listing_types = self.listing_type
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# For multiple types, we'll use a general date field or skip
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date_field = None # Skip date filtering for mixed types
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else:
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listing_types = [self.listing_type]
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# Determine date field for single type
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if self.listing_type == ListingType.SOLD:
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date_field = "sold_date"
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elif self.listing_type in [ListingType.FOR_SALE, ListingType.FOR_RENT]:
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date_field = "list_date"
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else: # PENDING or other types
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# Skip server-side date filtering for PENDING as both pending_date and contract_date
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# filters are broken in the API. Client-side filtering will be applied later.
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date_field = None
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# Build date parameter (expand to full days if hour-based filtering is used)
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if date_field:
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@@ -250,13 +269,15 @@ class RealtorScraper(Scraper):
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# Build sort parameter
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if self.sort_by:
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sort_param = f"sort: [{{ field: {self.sort_by}, direction: {self.sort_direction} }}]"
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elif self.listing_type == ListingType.SOLD:
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elif isinstance(self.listing_type, ListingType) and self.listing_type == ListingType.SOLD:
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sort_param = "sort: [{ field: sold_date, direction: desc }]"
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else:
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sort_param = "" #: prioritize normal fractal sort from realtor
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# Handle PENDING with or_filters (applies if PENDING is in the list or is the single type)
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has_pending = ListingType.PENDING in listing_types
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pending_or_contingent_param = (
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"or_filters: { contingent: true, pending: true }" if self.listing_type == ListingType.PENDING else ""
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"or_filters: { contingent: true, pending: true }" if has_pending else ""
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)
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# Build bucket parameter (only use fractal sort if no custom sort is specified)
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@@ -264,7 +285,27 @@ class RealtorScraper(Scraper):
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if not self.sort_by:
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bucket_param = 'bucket: { sort: "fractal_v1.1.3_fr" }'
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listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
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# Build status parameter
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# For PENDING, we need to query as FOR_SALE with or_filters for pending/contingent
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status_types = []
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for lt in listing_types:
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if lt == ListingType.PENDING:
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if ListingType.FOR_SALE not in status_types:
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status_types.append(ListingType.FOR_SALE)
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else:
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if lt not in status_types:
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status_types.append(lt)
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# Build status parameter string
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if status_types:
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status_values = [st.value.lower() for st in status_types]
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if len(status_values) == 1:
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status_param = f"status: {status_values[0]}"
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else:
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status_param = f"status: [{', '.join(status_values)}]"
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else:
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status_param = "" # No status parameter means return all types
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is_foreclosure = ""
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if variables.get("foreclosure") is True:
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@@ -285,7 +326,7 @@ class RealtorScraper(Scraper):
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coordinates: $coordinates
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radius: $radius
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}
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status: %s
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%s
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%s
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%s
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%s
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@@ -297,7 +338,7 @@ class RealtorScraper(Scraper):
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) %s
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}""" % (
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is_foreclosure,
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listing_type.value.lower(),
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status_param,
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date_param,
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property_type_param,
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property_filters_param,
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@@ -320,7 +361,7 @@ class RealtorScraper(Scraper):
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county: $county
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postal_code: $postal_code
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state_code: $state_code
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status: %s
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%s
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%s
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%s
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%s
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@@ -333,7 +374,7 @@ class RealtorScraper(Scraper):
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) %s
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}""" % (
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is_foreclosure,
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listing_type.value.lower(),
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status_param,
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date_param,
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property_type_param,
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property_filters_param,
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@@ -781,7 +822,7 @@ class RealtorScraper(Scraper):
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return (1, 0) if self.sort_direction == "desc" else (1, float('inf'))
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# For datetime fields, convert string to datetime for proper sorting
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if self.sort_by in ['list_date', 'sold_date', 'pending_date']:
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if self.sort_by in ['list_date', 'sold_date', 'pending_date', 'last_update_date']:
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if isinstance(value, str):
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try:
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from datetime import datetime
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@@ -126,6 +126,7 @@ def process_property(result: dict, mls_only: bool = False, extra_property_data:
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last_sold_date=(datetime.fromisoformat(result["last_sold_date"].replace('Z', '+00:00') if result["last_sold_date"].endswith('Z') else result["last_sold_date"]) if result.get("last_sold_date") else None),
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pending_date=(datetime.fromisoformat(result["pending_date"].replace('Z', '+00:00') if result["pending_date"].endswith('Z') else result["pending_date"]) if result.get("pending_date") else None),
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last_status_change_date=(datetime.fromisoformat(result["last_status_change_date"].replace('Z', '+00:00') if result["last_status_change_date"].endswith('Z') else result["last_status_change_date"]) if result.get("last_status_change_date") else None),
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last_update_date=(datetime.fromisoformat(result["last_update_date"].replace('Z', '+00:00') if result["last_update_date"].endswith('Z') else result["last_update_date"]) if result.get("last_update_date") else None),
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new_construction=result["flags"].get("is_new_construction") is True,
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hoa_fee=(result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) else None),
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latitude=(result["location"]["address"]["coordinate"].get("lat") if able_to_get_lat_long else None),
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@@ -10,6 +10,7 @@ _SEARCH_HOMES_DATA_BASE = """{
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last_sold_price
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last_sold_date
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last_status_change_date
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last_update_date
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list_price
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list_price_max
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list_price_min
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@@ -38,6 +38,7 @@ ordered_properties = [
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"last_sold_date",
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"last_sold_price",
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"last_status_change_date",
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"last_update_date",
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"assessed_value",
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"estimated_value",
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"tax",
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@@ -156,9 +157,17 @@ def process_result(result: Property) -> pd.DataFrame:
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return properties_df[ordered_properties]
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def validate_input(listing_type: str) -> None:
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if listing_type.upper() not in ListingType.__members__:
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raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
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def validate_input(listing_type: str | list[str] | None) -> None:
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if listing_type is None:
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return # None is valid - returns all types
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if isinstance(listing_type, list):
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for lt in listing_type:
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if lt.upper() not in ListingType.__members__:
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raise InvalidListingType(f"Provided listing type, '{lt}', does not exist.")
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else:
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if listing_type.upper() not in ListingType.__members__:
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raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
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def validate_dates(date_from: str | None, date_to: str | None) -> None:
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@@ -259,7 +268,7 @@ def validate_filters(
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def validate_sort(sort_by: str | None, sort_direction: str | None = "desc") -> None:
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"""Validate sort parameters."""
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valid_sort_fields = ["list_date", "sold_date", "list_price", "sqft", "beds", "baths"]
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valid_sort_fields = ["list_date", "sold_date", "list_price", "sqft", "beds", "baths", "last_update_date"]
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valid_directions = ["asc", "desc"]
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if sort_by and sort_by not in valid_sort_fields:
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