- version bump

- Replace /suggest REST endpoint with GraphQL Search_suggestions query
- Use search_location field instead of individual city/county/state/postal_code fields
- Fix coordinate order to [lon, lat] (GeoJSON standard) for radius searches
- Extract mpr_id from addr: prefix for single address lookups

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

README.md

@@ -84,7 +84,7 @@ properties = scrape_property(
 #### Sorting & Listing Types
 ```py
 # Sort options: list_price, list_date, sqft, beds, baths, last_update_date
-# Listing types: "for_sale", "for_rent", "sold", "pending", list, or None (all)
+# Listing types: "for_sale", "for_rent", "sold", "pending", "off_market", list, or None (common types)
 properties = scrape_property(
     location="Miami, FL",
     listing_type=["for_sale", "pending"],  # Single string, list, or None
@@ -94,6 +94,17 @@ properties = scrape_property(
 )
 ```
 
+#### Pagination Control
+```py
+# Sequential mode with early termination (more efficient for narrow filters)
+properties = scrape_property(
+    location="Los Angeles, CA",
+    listing_type="for_sale",
+    updated_in_past_hours=2,  # Narrow time window
+    parallel=False  # Fetch pages sequentially, stop when filters no longer match
+)
+```
+
 ## Output
 ```plaintext
 >>> properties.head()
@@ -147,7 +158,7 @@ Required
 │    - 'other'
 │    - 'ready_to_build'
 │    - List of strings returns properties matching ANY status: ['for_sale', 'pending']
-│    - None returns all listing types
+│    - None returns common listing types (for_sale, for_rent, sold, pending, off_market)
 │
 Optional
 ├── property_type (list): Choose the type of properties.
@@ -234,7 +245,9 @@ Optional
 │
 ├── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
 │
-└── offset (integer): Starting position for pagination within the 10k limit. Use with limit to fetch results in chunks.
+├── offset (integer): Starting position for pagination within the 10k limit. Use with limit to fetch results in chunks.
+│
+└── parallel (True/False): Controls pagination strategy. Default is True (fetch pages in parallel for speed). Set to False for sequential fetching with early termination (useful for rate limiting or narrow time windows).
 ```
 
 ### Property Schema

homeharvest/__init__.py

@@ -48,6 +48,8 @@ def scrape_property(
     # New sorting parameters
     sort_by: str = None,
     sort_direction: str = "desc",
+    # Pagination control
+    parallel: bool = True,
 ) -> Union[pd.DataFrame, list[dict], list[Property]]:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
@@ -96,6 +98,9 @@ def scrape_property(
     :param year_built_min, year_built_max: Filter by year built
     :param sort_by: Sort results by field (list_date, sold_date, list_price, sqft, beds, baths, last_update_date)
     :param sort_direction: Sort direction (asc, desc)
+    :param parallel: Controls pagination strategy. True (default) = fetch all pages in parallel for maximum speed.
+        False = fetch pages sequentially with early termination checks (useful for rate limiting or narrow time windows).
+        Sequential mode will stop paginating as soon as time-based filters indicate no more matches are possible.
 
     Note: past_days and past_hours also accept timedelta objects for more Pythonic usage.
     """
@@ -190,6 +195,8 @@ def scrape_property(
         # New sorting
         sort_by=sort_by,
         sort_direction=sort_direction,
+        # Pagination control
+        parallel=parallel,
     )
 
     site = RealtorScraper(scraper_input)

homeharvest/core/scrapers/__init__.py

@@ -55,6 +55,9 @@ class ScraperInput(BaseModel):
     sort_by: str | None = None
     sort_direction: str = "desc"
 
+    # Pagination control
+    parallel: bool = True
+
 
 class Scraper:
     session = None
@@ -78,21 +81,21 @@ class Scraper:
             Scraper.session.mount("https://", adapter)
             Scraper.session.headers.update(
                 {
-                    "accept": "application/json, text/javascript",
-                    "accept-language": "en-US,en;q=0.9",
-                    "cache-control": "no-cache",
-                    "content-type": "application/json",
-                    "origin": "https://www.realtor.com",
-                    "pragma": "no-cache",
-                    "priority": "u=1, i",
-                    "rdc-ab-tests": "commute_travel_time_variation:v1",
-                    "sec-ch-ua": '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
-                    "sec-ch-ua-mobile": "?0",
-                    "sec-ch-ua-platform": '"Windows"',
-                    "sec-fetch-dest": "empty",
-                    "sec-fetch-mode": "cors",
-                    "sec-fetch-site": "same-origin",
-                    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36",
+                    'sec-ch-ua-platform': '"macOS"',
+                    'rdc-client-name': 'rdc-search-for-sale-desktop',
+                    'sec-ch-ua': '"Chromium";v="142", "Google Chrome";v="142", "Not_A Brand";v="99"',
+                    'sec-ch-ua-mobile': '?0',
+                    'rdc-client-version': '0.1.0',
+                    'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/142.0.0.0 Safari/537.36',
+                    'accept': 'application/json',
+                    'content-type': 'application/json',
+                    'origin': 'https://www.realtor.com',
+                    'sec-fetch-site': 'same-site',
+                    'sec-fetch-mode': 'cors',
+                    'sec-fetch-dest': 'empty',
+                    'referer': 'https://www.realtor.com/',
+                    'accept-language': 'en-US,en;q=0.9',
+                    'priority': 'u=1, i',
                 }
             )
 
@@ -141,6 +144,9 @@ class Scraper:
         self.sort_by = scraper_input.sort_by
         self.sort_direction = scraper_input.sort_direction
 
+        # Pagination control
+        self.parallel = scraper_input.parallel
+
     def search(self) -> list[Union[Property | dict]]: ...
 
     @staticmethod

homeharvest/core/scrapers/realtor/__init__.py

@@ -35,10 +35,7 @@ from .processors import (
 
 
 class RealtorScraper(Scraper):
-    SEARCH_GQL_URL = "https://www.realtor.com/api/v1/rdc_search_srp?client_id=rdc-search-new-communities&schema=vesta"
-    PROPERTY_URL = "https://www.realtor.com/realestateandhomes-detail/"
-    PROPERTY_GQL = "https://graph.realtor.com/graphql"
-    ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
+    SEARCH_GQL_URL = "https://api.frontdoor.realtor.com/graphql"
     NUM_PROPERTY_WORKERS = 20
     DEFAULT_PAGE_SIZE = 200
 
@@ -46,33 +43,70 @@ class RealtorScraper(Scraper):
         super().__init__(scraper_input)
 
     def handle_location(self):
-        # Get client_id from listing_type
-        if self.listing_type is None:
-            client_id = "for-sale"
-        elif isinstance(self.listing_type, list):
-            client_id = self.listing_type[0].value.lower().replace("_", "-") if self.listing_type else "for-sale"
-        else:
-            client_id = self.listing_type.value.lower().replace("_", "-")
+        query = """query Search_suggestions($searchInput: SearchSuggestionsInput!) {
+            search_suggestions(search_input: $searchInput) {
+                geo_results {
+                    type
+                    text
+                    geo {
+                        _id
+                        area_type
+                        city
+                        state_code
+                        postal_code
+                        county
+                        centroid { lat lon }
+                        slug_id
+                        geo_id
+                    }
+                }
+            }
+        }"""
 
-        params = {
-            "input": self.location,
-            "client_id": client_id,
-            "limit": "1",
-            "area_types": "city,state,county,postal_code,address,street,neighborhood,school,school_district,university,park",
+        variables = {
+            "searchInput": {
+                "search_term": self.location
+            }
         }
 
-        response = self.session.get(
-            self.ADDRESS_AUTOCOMPLETE_URL,
-            params=params,
-        )
+        payload = {
+            "query": query,
+            "variables": variables,
+        }
+
+        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
         response_json = response.json()
 
-        result = response_json["autocomplete"]
-
-        if not result:
+        if (
+            response_json is None
+            or "data" not in response_json
+            or response_json["data"] is None
+            or "search_suggestions" not in response_json["data"]
+            or response_json["data"]["search_suggestions"] is None
+            or "geo_results" not in response_json["data"]["search_suggestions"]
+            or not response_json["data"]["search_suggestions"]["geo_results"]
+        ):
             return None
 
-        return result[0]
+        geo_result = response_json["data"]["search_suggestions"]["geo_results"][0]
+        geo = geo_result.get("geo", {})
+
+        result = {
+            "text": geo_result.get("text"),
+            "area_type": geo.get("area_type"),
+            "city": geo.get("city"),
+            "state_code": geo.get("state_code"),
+            "postal_code": geo.get("postal_code"),
+            "county": geo.get("county"),
+            "centroid": geo.get("centroid"),
+        }
+
+        if geo.get("area_type") == "address":
+            geo_id = geo.get("_id", "")
+            if geo_id.startswith("addr:"):
+                result["mpr_id"] = geo_id.replace("addr:", "")
+
+        return result
 
     def get_latest_listing_id(self, property_id: str) -> str | None:
         query = """query Property($property_id: ID!) {
@@ -108,6 +142,7 @@ class RealtorScraper(Scraper):
             return property_info["listings"][0]["listing_id"]
 
     def handle_home(self, property_id: str) -> list[Property]:
+        """Fetch single home with proper error handling."""
         query = (
             """query Home($property_id: ID!) {
                     home(property_id: $property_id) %s
@@ -116,23 +151,33 @@ class RealtorScraper(Scraper):
         )
 
         variables = {"property_id": property_id}
-        payload = {
-            "query": query,
-            "variables": variables,
-        }
+        payload = {"query": query, "variables": variables}
 
-        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
-        response_json = response.json()
+        try:
+            response = self.session.post(self.SEARCH_GQL_URL, json=payload)
+            data = response.json()
 
-        property_info = response_json["data"]["home"]
+            # Check for errors or missing data
+            if "errors" in data or "data" not in data:
+                return []
 
-        if self.return_type != ReturnType.raw:
-            return [process_property(property_info, self.mls_only, self.extra_property_data, 
-                                   self.exclude_pending, self.listing_type, get_key, process_extra_property_details)]
-        else:
-            return [property_info]
+            if data["data"] is None or "home" not in data["data"]:
+                return []
 
+            property_info = data["data"]["home"]
+            if property_info is None:
+                return []
 
+            # Process based on return type
+            if self.return_type != ReturnType.raw:
+                return [process_property(property_info, self.mls_only, self.extra_property_data,
+                                       self.exclude_pending, self.listing_type, get_key,
+                                       process_extra_property_details)]
+            else:
+                return [property_info]
+
+        except Exception:
+            return []
 
     def general_search(self, variables: dict, search_type: str) -> Dict[str, Union[int, Union[list[Property], list[dict]]]]:
         """
@@ -144,7 +189,15 @@ class RealtorScraper(Scraper):
         # Determine date field based on listing type
         # Convert listing_type to list for uniform handling
         if self.listing_type is None:
-            listing_types = []
+            # When None, return all common listing types as documented
+            # Note: NEW_COMMUNITY, OTHER, and READY_TO_BUILD are excluded as they typically return no results
+            listing_types = [
+                ListingType.FOR_SALE,
+                ListingType.FOR_RENT,
+                ListingType.SOLD,
+                ListingType.PENDING,
+                ListingType.OFF_MARKET,
+            ]
             date_field = None  # When no listing_type is specified, skip date filtering
         elif isinstance(self.listing_type, list):
             listing_types = self.listing_type
@@ -277,10 +330,14 @@ class RealtorScraper(Scraper):
         else:
             sort_param = ""  #: prioritize normal fractal sort from realtor
 
-        # Handle PENDING with or_filters (applies if PENDING is in the list or is the single type)
+        # Handle PENDING with or_filters
+        # Only use or_filters when PENDING is the only type or mixed only with FOR_SALE
+        # Using or_filters with other types (SOLD, FOR_RENT, etc.) will exclude those types
         has_pending = ListingType.PENDING in listing_types
+        other_types = [lt for lt in listing_types if lt not in [ListingType.PENDING, ListingType.FOR_SALE]]
+        use_or_filters = has_pending and len(other_types) == 0
         pending_or_contingent_param = (
-            "or_filters: { contingent: true, pending: true }" if has_pending else ""
+            "or_filters: { contingent: true, pending: true }" if use_or_filters else ""
         )
 
         # Build bucket parameter (only use fractal sort if no custom sort is specified)
@@ -351,19 +408,13 @@ class RealtorScraper(Scraper):
             )
         elif search_type == "area":  #: general search, came from a general location
             query = """query Home_search(
-                                $city: String,
-                                $county: [String],
-                                $state_code: String,
-                                $postal_code: String
+                                $search_location: SearchLocation,
                                 $offset: Int,
                             ) {
                                 home_search(
                                     query: {
                                         %s
-                                        city: $city
-                                        county: $county
-                                        postal_code: $postal_code
-                                        state_code: $state_code
+                                        search_location: $search_location
                                         %s
                                         %s
                                         %s
@@ -499,24 +550,16 @@ class RealtorScraper(Scraper):
                 if not location_info.get("centroid"):
                     return []
 
-                coordinates = list(location_info["centroid"].values())
+                centroid = location_info["centroid"]
+                coordinates = [centroid["lon"], centroid["lat"]]  # GeoJSON order: [lon, lat]
                 search_variables |= {
                     "coordinates": coordinates,
                     "radius": "{}mi".format(self.radius),
                 }
 
-        elif location_type == "postal_code":
+        else:  #: general search (city, county, postal_code, etc.)
             search_variables |= {
-                "postal_code": location_info.get("postal_code"),
-            }
-
-        else:  #: general search, location
-            search_variables |= {
-                "city": location_info.get("city"),
-                "county": location_info.get("county"),
-                "state_code": location_info.get("state_code"),
-                "postal_code": location_info.get("postal_code"),
-
+                "search_location": {"location": location_info.get("text")},
             }
 
         if self.foreclosure:
@@ -526,39 +569,49 @@ class RealtorScraper(Scraper):
         total = result["total"]
         homes = result["properties"]
 
-        # Pre-check: Should we continue pagination?
-        # This optimization prevents unnecessary API calls when using time-based filters
-        # with date sorting. If page 1's last property is outside the time window,
-        # all future pages will also be outside (due to sort order).
-        should_continue_pagination = self._should_fetch_more_pages(homes)
+        # Fetch remaining pages based on parallel parameter
+        if self.offset + self.DEFAULT_PAGE_SIZE < min(total, self.offset + self.limit):
+            if self.parallel:
+                # Parallel mode: Fetch all remaining pages in parallel
+                with ThreadPoolExecutor() as executor:
+                    futures_with_offsets = [
+                        (i, executor.submit(
+                            self.general_search,
+                            variables=search_variables | {"offset": i},
+                            search_type=search_type,
+                        ))
+                        for i in range(
+                            self.offset + self.DEFAULT_PAGE_SIZE,
+                            min(total, self.offset + self.limit),
+                            self.DEFAULT_PAGE_SIZE,
+                        )
+                    ]
 
-        # Only launch parallel pagination if needed
-        if should_continue_pagination and self.offset + self.DEFAULT_PAGE_SIZE < min(total, self.offset + self.limit):
-            with ThreadPoolExecutor() as executor:
-                # Store futures with their offsets to maintain proper sort order
-                # Start from offset + page_size and go up to offset + limit
-                futures_with_offsets = [
-                    (i, executor.submit(
-                        self.general_search,
-                        variables=search_variables | {"offset": i},
+                    # Collect results and sort by offset to preserve API sort order
+                    results = []
+                    for offset, future in futures_with_offsets:
+                        results.append((offset, future.result()["properties"]))
+
+                    results.sort(key=lambda x: x[0])
+                    for offset, properties in results:
+                        homes.extend(properties)
+            else:
+                # Sequential mode: Fetch pages one by one with early termination checks
+                for current_offset in range(
+                    self.offset + self.DEFAULT_PAGE_SIZE,
+                    min(total, self.offset + self.limit),
+                    self.DEFAULT_PAGE_SIZE,
+                ):
+                    # Check if we should continue based on time-based filters
+                    if not self._should_fetch_more_pages(homes):
+                        break
+
+                    result = self.general_search(
+                        variables=search_variables | {"offset": current_offset},
                         search_type=search_type,
-                    ))
-                    for i in range(
-                        self.offset + self.DEFAULT_PAGE_SIZE,
-                        min(total, self.offset + self.limit),
-                        self.DEFAULT_PAGE_SIZE,
                     )
-                ]
-
-                # Collect results and sort by offset to preserve API sort order across pages
-                results = []
-                for offset, future in futures_with_offsets:
-                    results.append((offset, future.result()["properties"]))
-
-                # Sort by offset and concatenate in correct order
-                results.sort(key=lambda x: x[0])
-                for offset, properties in results:
-                    homes.extend(properties)
+                    page_properties = result["properties"]
+                    homes.extend(page_properties)
 
         # Apply client-side hour-based filtering if needed
         # (API only supports day-level filtering, so we post-filter for hour precision)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.8.3"
+version = "0.8.6b"
 description = "Real estate scraping library"
 authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/ZacharyHampton/HomeHarvest"

tests/test_realtor.py

@@ -87,6 +87,25 @@ def test_realtor_date_range_sold():
     )
 
 
+def test_listing_type_none_includes_sold():
+    """Test that listing_type=None includes sold listings (issue #142)"""
+    # Get properties with listing_type=None (should include all common types)
+    result_none = scrape_property(
+        location="Warren, MI",
+        listing_type=None
+    )
+
+    # Verify we got results
+    assert result_none is not None and len(result_none) > 0
+
+    # Verify sold listings are included
+    status_types = set(result_none['status'].unique())
+    assert 'SOLD' in status_types, "SOLD listings should be included when listing_type=None"
+
+    # Verify we get multiple listing types (not just one)
+    assert len(status_types) > 1, "Should return multiple listing types when listing_type=None"
+
+
 def test_realtor_single_property():
     results = [
         scrape_property(