- primary photo bug fix

- limit parameter

README.md

@@ -90,9 +90,13 @@ Optional
 │
 ├── foreclosure (True/False): If set, fetches only foreclosures
 │
-└── proxy (string): In format 'http://user:pass@host:port'
+├── proxy (string): In format 'http://user:pass@host:port'
 │
-└── extra_property_data (bool): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
+├── 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'
+│
+└── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
 ```
 
 ### Property Schema
@@ -142,6 +146,11 @@ Property
 │ ├── agent
 │ ├── agent_email
 │ └── agent_phone
+
+├── Broker Info:
+│ ├── broker
+│ ├── broker_email
+│ └── broker_website
 ```
 
 ### Exceptions

homeharvest/__init__.py

@@ -1,7 +1,7 @@
 import warnings
 import pandas as pd
 from .core.scrapers import ScraperInput
-from .utils import process_result, ordered_properties, validate_input, validate_dates
+from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit
 from .core.scrapers.realtor import RealtorScraper
 from .core.scrapers.models import ListingType
 
@@ -17,11 +17,13 @@ def scrape_property(
     date_to: str = None,
     foreclosure: bool = None,
     extra_property_data: bool = True,
+    exclude_pending: bool = False,
+    limit: int = 10000,
 ) -> pd.DataFrame:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
     :param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
-    :param listing_type: Listing Type (for_sale, for_rent, sold)
+    :param listing_type: Listing Type (for_sale, for_rent, sold, pending)
     :param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
     :param mls_only: If set, fetches only listings with MLS IDs.
     :param proxy: Proxy to use for scraping
@@ -29,9 +31,12 @@ def scrape_property(
     :param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
     :param foreclosure: If set, fetches only foreclosure listings.
     :param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
+    :param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
+    :param limit: Limit the number of results returned. Maximum is 10,000.
     """
     validate_input(listing_type)
     validate_dates(date_from, date_to)
+    validate_limit(limit)
 
     scraper_input = ScraperInput(
         location=location,
@@ -44,6 +49,8 @@ def scrape_property(
         date_to=date_to,
         foreclosure=foreclosure,
         extra_property_data=extra_property_data,
+        exclude_pending=exclude_pending,
+        limit=limit,
     )
 
     site = RealtorScraper(scraper_input)

homeharvest/core/scrapers/__init__.py

@@ -21,6 +21,8 @@ class ScraperInput:
     date_to: str | None = None
     foreclosure: bool | None = False
     extra_property_data: bool | None = True
+    exclude_pending: bool | None = False
+    limit: int = 10000
 
 
 class Scraper:
@@ -62,6 +64,8 @@ class Scraper:
         self.date_to = scraper_input.date_to
         self.foreclosure = scraper_input.foreclosure
         self.extra_property_data = scraper_input.extra_property_data
+        self.exclude_pending = scraper_input.exclude_pending
+        self.limit = scraper_input.limit
 
     def search(self) -> list[Property]: ...
 

homeharvest/core/scrapers/models.py

@@ -34,6 +34,8 @@ class PropertyType(Enum):
     APARTMENT = "APARTMENT"
     BUILDING = "BUILDING"
     COMMERCIAL = "COMMERCIAL"
+    GOVERNMENT = "GOVERNMENT"
+    INDUSTRIAL = "INDUSTRIAL"
     CONDO_TOWNHOME = "CONDO_TOWNHOME"
     CONDO_TOWNHOME_ROWHOME_COOP = "CONDO_TOWNHOME_ROWHOME_COOP"
     CONDO = "CONDO"

homeharvest/core/scrapers/realtor/__init__.py

@@ -4,6 +4,7 @@ homeharvest.realtor.__init__
 
 This module implements the scraper for realtor.com
 """
+
 from __future__ import annotations
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from datetime import datetime
@@ -114,10 +115,10 @@ class RealtorScraper(Scraper):
         )
 
         able_to_get_lat_long = (
-            property_info
-            and property_info.get("address")
-            and property_info["address"].get("location")
-            and property_info["address"]["location"].get("coordinate")
+                property_info
+                and property_info.get("address")
+                and property_info["address"].get("location")
+                and property_info["address"]["location"].get("coordinate")
         )
         list_date_str = (
             property_info["basic"]["list_date"].split("T")[0] if property_info["basic"].get("list_date") else None
@@ -144,6 +145,7 @@ class RealtorScraper(Scraper):
 
         property_id = property_info["details"]["permalink"]
         prop_details = self.get_prop_details(property_id)
+        style = property_info["basic"].get("type", "").upper()
         listing = Property(
             mls=mls,
             mls_id=(
@@ -166,8 +168,12 @@ class RealtorScraper(Scraper):
             longitude=property_info["address"]["location"]["coordinate"].get("lon") if able_to_get_lat_long else None,
             address=self._parse_address(property_info, search_type="handle_listing"),
             description=Description(
-                alt_photos=self.process_alt_photos(property_info["media"].get("photos", [])) if property_info.get("media") else None,
-                style=property_info["basic"].get("type", "").upper(),
+                alt_photos=(
+                    self.process_alt_photos(property_info["media"].get("photos", []))
+                    if property_info.get("media")
+                    else None
+                ),
+                style=PropertyType.__getitem__(style) if style and style in PropertyType.__members__ else None,
                 beds=property_info["basic"].get("beds"),
                 baths_full=property_info["basic"].get("baths_full"),
                 baths_half=property_info["basic"].get("baths_half"),
@@ -475,7 +481,7 @@ class RealtorScraper(Scraper):
             )
         else:  #: general search, came from an address
             query = (
-                """query Property_search(
+                    """query Property_search(
                         $property_id: [ID]!
                         $offset: Int!,
                     ) {
@@ -486,7 +492,7 @@ class RealtorScraper(Scraper):
                             limit: 1
                             offset: $offset
                         ) %s"""
-                % results_query
+                    % results_query
             )
 
         payload = {
@@ -501,12 +507,12 @@ class RealtorScraper(Scraper):
         properties: list[Property] = []
 
         if (
-            response_json is None
-            or "data" not in response_json
-            or response_json["data"] is None
-            or search_key not in response_json["data"]
-            or response_json["data"][search_key] is None
-            or "results" not in response_json["data"][search_key]
+                response_json is None
+                or "data" not in response_json
+                or response_json["data"] is None
+                or search_key not in response_json["data"]
+                or response_json["data"][search_key] is None
+                or "results" not in response_json["data"][search_key]
         ):
             return {"total": 0, "properties": []}
 
@@ -517,19 +523,19 @@ class RealtorScraper(Scraper):
                 return
 
             able_to_get_lat_long = (
-                result
-                and result.get("location")
-                and result["location"].get("address")
-                and result["location"]["address"].get("coordinate")
+                    result
+                    and result.get("location")
+                    and result["location"].get("address")
+                    and result["location"]["address"].get("coordinate")
             )
 
             is_pending = result["flags"].get("is_pending") or result["flags"].get("is_contingent")
 
-            if is_pending and self.listing_type != ListingType.PENDING:
+            if is_pending and (self.exclude_pending and self.listing_type != ListingType.PENDING):
                 return
 
             property_id = result["property_id"]
-            prop_details = self.get_prop_details(property_id)
+            prop_details = self.get_prop_details(property_id) if self.extra_property_data else {}
 
             realty_property = Property(
                 mls=mls,
@@ -641,14 +647,14 @@ class RealtorScraper(Scraper):
         total = result["total"]
         homes = result["properties"]
 
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        with ThreadPoolExecutor() as executor:
             futures = [
                 executor.submit(
                     self.general_search,
                     variables=search_variables | {"offset": i},
                     search_type=search_type,
                 )
-                for i in range(200, min(total, 10000), 200)
+                for i in range(200, min(total, self.limit), 200)
             ]
 
             for future in as_completed(futures):
@@ -665,7 +671,7 @@ class RealtorScraper(Scraper):
         query = """query GetHome($property_id: ID!) {
                     home(property_id: $property_id) {
                         __typename
-                
+
                         advertisers {
                             __typename
                             type
@@ -673,29 +679,29 @@ class RealtorScraper(Scraper):
                             email
                             phones { number type ext primary }
                         }
-                        
+
                         consumer_advertisers {
                             name
                             phone
                             href
                             type
                         }
-                
-                        nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) { 
-                            __typename schools { district { __typename id name } } 
-                        }  
+
+                        nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {
+                            __typename schools { district { __typename id name } }
+                        }
                         taxHistory: tax_history { __typename tax year assessment { __typename building land total } }
-                        estimates { 
-                            __typename 
-                            currentValues: current_values { 
+                        estimates {
+                            __typename
+                            currentValues: current_values {
                                 __typename
-                                source { __typename type name } 
-                                estimate 
+                                source { __typename type name }
+                                estimate
                                 estimateHigh: estimate_high
-                                estimateLow: estimate_low 
-                                date 
-                                isBestHomeValue: isbest_homevalue 
-                            } 
+                                estimateLow: estimate_low
+                                date
+                                isBestHomeValue: isbest_homevalue
+                            }
                         }
                     }
                 }"""
@@ -721,19 +727,15 @@ class RealtorScraper(Scraper):
         assessed_value = get_key(["data", "home", "taxHistory", 0, "assessment", "total"])
         estimated_value = get_key(["data", "home", "estimates", "currentValues", 0, "estimate"])
 
-        agents = [Agent(
-            name=ad["name"],
-            email=ad["email"],
-            phones=ad["phones"]
-        ) for ad in agents]
+        agents = [Agent(name=ad["name"], email=ad["email"], phones=ad["phones"]) for ad in agents]
 
-        brokers = [Broker(
-            name=ad["name"],
-            phone=ad["phone"],
-            website=ad["href"]
-        ) for ad in advertisers if ad.get("type") != "Agent"]
+        brokers = [
+            Broker(name=ad["name"], phone=ad["phone"], website=ad["href"])
+            for ad in advertisers
+            if ad.get("type") != "Agent"
+        ]
 
-        schools = [school["district"]["name"] for school in schools if school['district'].get('name')]
+        schools = [school["district"]["name"] for school in schools if school["district"].get("name")]
         return {
             "agents": agents if agents else None,
             "brokers": brokers if brokers else None,
@@ -772,12 +774,14 @@ class RealtorScraper(Scraper):
         return Address(
             full_line=address.get("line"),
             street=" ".join(
-                part for part in [
+                part
+                for part in [
                     address.get("street_number"),
                     address.get("street_direction"),
                     address.get("street_name"),
                     address.get("street_suffix"),
-                ] if part is not None
+                ]
+                if part is not None
             ).strip(),
             unit=address["unit"],
             city=address["city"],
@@ -786,7 +790,10 @@ class RealtorScraper(Scraper):
         )
 
     @staticmethod
-    def _parse_description(result: dict) -> Description:
+    def _parse_description(result: dict) -> Description | None:
+        if not result:
+            return None
+
         description_data = result.get("description", {})
 
         if description_data is None or not isinstance(description_data, dict):
@@ -797,11 +804,8 @@ class RealtorScraper(Scraper):
             style = style.upper()
 
         primary_photo = ""
-        if result and "primary_photo" in result:
-            primary_photo_info = result["primary_photo"]
-            if primary_photo_info and "href" in primary_photo_info:
-                primary_photo_href = primary_photo_info["href"]
-                primary_photo = primary_photo_href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
+        if (primary_photo_info := result.get('primary_photo')) and (primary_photo_href := primary_photo_info.get("href")):
+            primary_photo = primary_photo_href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
 
         return Description(
             primary_photo=primary_photo,
@@ -812,7 +816,11 @@ class RealtorScraper(Scraper):
             baths_half=description_data.get("baths_half"),
             sqft=description_data.get("sqft"),
             lot_sqft=description_data.get("lot_sqft"),
-            sold_price=description_data.get("sold_price") if result.get('last_sold_date') or result["list_price"] != description_data.get("sold_price") else None,  #: has a sold date or list and sold price are different
+            sold_price=(
+                description_data.get("sold_price")
+                if result.get("last_sold_date") or result["list_price"] != description_data.get("sold_price")
+                else None
+            ),  #: has a sold date or list and sold price are different
             year_built=description_data.get("year_built"),
             garage=description_data.get("garage"),
             stories=description_data.get("stories"),

homeharvest/utils.py

@@ -83,19 +83,21 @@ def process_result(result: Property) -> pd.DataFrame:
     prop_data["nearby_schools"] = ", ".join(set(prop_data["nearby_schools"])) if prop_data["nearby_schools"] else None
 
     description = result.description
-    prop_data["primary_photo"] = description.primary_photo
-    prop_data["alt_photos"] = ", ".join(description.alt_photos) if description.alt_photos else None
-    prop_data["style"] = description.style if type(description.style) == str else description.style.value
-    prop_data["beds"] = description.beds
-    prop_data["full_baths"] = description.baths_full
-    prop_data["half_baths"] = description.baths_half
-    prop_data["sqft"] = description.sqft
-    prop_data["lot_sqft"] = description.lot_sqft
-    prop_data["sold_price"] = description.sold_price
-    prop_data["year_built"] = description.year_built
-    prop_data["parking_garage"] = description.garage
-    prop_data["stories"] = description.stories
-    prop_data["text"] = description.text
+    if description:
+        prop_data["primary_photo"] = description.primary_photo
+        prop_data["alt_photos"] = ", ".join(description.alt_photos) if description.alt_photos else None
+        prop_data["style"] = description.style if isinstance(description.style,
+                                                             str) else description.style.value if description.style else None
+        prop_data["beds"] = description.beds
+        prop_data["full_baths"] = description.baths_full
+        prop_data["half_baths"] = description.baths_half
+        prop_data["sqft"] = description.sqft
+        prop_data["lot_sqft"] = description.lot_sqft
+        prop_data["sold_price"] = description.sold_price
+        prop_data["year_built"] = description.year_built
+        prop_data["parking_garage"] = description.garage
+        prop_data["stories"] = description.stories
+        prop_data["text"] = description.text
 
     properties_df = pd.DataFrame([prop_data])
     properties_df = properties_df.reindex(columns=ordered_properties)
@@ -109,7 +111,7 @@ def validate_input(listing_type: str) -> None:
 
 
 def validate_dates(date_from: str | None, date_to: str | None) -> None:
-    if (date_from is not None and date_to is None) or (date_from is None and date_to is not None):
+    if isinstance(date_from, str) != isinstance(date_to, str):
         raise InvalidDate("Both date_from and date_to must be provided.")
 
     if date_from and date_to:
@@ -121,3 +123,10 @@ def validate_dates(date_from: str | None, date_to: str | None) -> None:
                 raise InvalidDate("date_to must be after date_from.")
         except ValueError:
             raise InvalidDate(f"Invalid date format or range")
+
+
+def validate_limit(limit: int) -> None:
+    #: 1 -> 10000 limit
+
+    if limit is not None and (limit < 1 or limit > 10000):
+        raise ValueError("Property limit must be between 1 and 10,000.")

poetry.lock

@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
 [[package]]
 name = "certifi"
 version = "2023.7.22"
@@ -391,6 +402,116 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
+[[package]]
+name = "pydantic"
+version = "2.7.4"
+description = "Data validation using Python type hints"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pydantic-2.7.4-py3-none-any.whl", hash = "sha256:ee8538d41ccb9c0a9ad3e0e5f07bf15ed8015b481ced539a1759d8cc89ae90d0"},
+    {file = "pydantic-2.7.4.tar.gz", hash = "sha256:0c84efd9548d545f63ac0060c1e4d39bb9b14db8b3c0652338aecc07b5adec52"},
+]
+
+[package.dependencies]
+annotated-types = ">=0.4.0"
+pydantic-core = "2.18.4"
+typing-extensions = ">=4.6.1"
+
+[package.extras]
+email = ["email-validator (>=2.0.0)"]
+
+[[package]]
+name = "pydantic-core"
+version = "2.18.4"
+description = "Core functionality for Pydantic validation and serialization"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pydantic_core-2.18.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:f76d0ad001edd426b92233d45c746fd08f467d56100fd8f30e9ace4b005266e4"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:59ff3e89f4eaf14050c8022011862df275b552caef8082e37b542b066ce1ff26"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a55b5b16c839df1070bc113c1f7f94a0af4433fcfa1b41799ce7606e5c79ce0a"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4d0dcc59664fcb8974b356fe0a18a672d6d7cf9f54746c05f43275fc48636851"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8951eee36c57cd128f779e641e21eb40bc5073eb28b2d23f33eb0ef14ffb3f5d"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4701b19f7e3a06ea655513f7938de6f108123bf7c86bbebb1196eb9bd35cf724"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e00a3f196329e08e43d99b79b286d60ce46bed10f2280d25a1718399457e06be"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:97736815b9cc893b2b7f663628e63f436018b75f44854c8027040e05230eeddb"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:6891a2ae0e8692679c07728819b6e2b822fb30ca7445f67bbf6509b25a96332c"},
+    {file = "pydantic_core-2.18.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bc4ff9805858bd54d1a20efff925ccd89c9d2e7cf4986144b30802bf78091c3e"},
+    {file = "pydantic_core-2.18.4-cp310-none-win32.whl", hash = "sha256:1b4de2e51bbcb61fdebd0ab86ef28062704f62c82bbf4addc4e37fa4b00b7cbc"},
+    {file = "pydantic_core-2.18.4-cp310-none-win_amd64.whl", hash = "sha256:6a750aec7bf431517a9fd78cb93c97b9b0c496090fee84a47a0d23668976b4b0"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:942ba11e7dfb66dc70f9ae66b33452f51ac7bb90676da39a7345e99ffb55402d"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:b2ebef0e0b4454320274f5e83a41844c63438fdc874ea40a8b5b4ecb7693f1c4"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a642295cd0c8df1b86fc3dced1d067874c353a188dc8e0f744626d49e9aa51c4"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5f09baa656c904807e832cf9cce799c6460c450c4ad80803517032da0cd062e2"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:98906207f29bc2c459ff64fa007afd10a8c8ac080f7e4d5beff4c97086a3dabd"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:19894b95aacfa98e7cb093cd7881a0c76f55731efad31073db4521e2b6ff5b7d"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0fbbdc827fe5e42e4d196c746b890b3d72876bdbf160b0eafe9f0334525119c8"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f85d05aa0918283cf29a30b547b4df2fbb56b45b135f9e35b6807cb28bc47951"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e85637bc8fe81ddb73fda9e56bab24560bdddfa98aa64f87aaa4e4b6730c23d2"},
+    {file = "pydantic_core-2.18.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2f5966897e5461f818e136b8451d0551a2e77259eb0f73a837027b47dc95dab9"},
+    {file = "pydantic_core-2.18.4-cp311-none-win32.whl", hash = "sha256:44c7486a4228413c317952e9d89598bcdfb06399735e49e0f8df643e1ccd0558"},
+    {file = "pydantic_core-2.18.4-cp311-none-win_amd64.whl", hash = "sha256:8a7164fe2005d03c64fd3b85649891cd4953a8de53107940bf272500ba8a788b"},
+    {file = "pydantic_core-2.18.4-cp311-none-win_arm64.whl", hash = "sha256:4e99bc050fe65c450344421017f98298a97cefc18c53bb2f7b3531eb39bc7805"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:6f5c4d41b2771c730ea1c34e458e781b18cc668d194958e0112455fff4e402b2"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2fdf2156aa3d017fddf8aea5adfba9f777db1d6022d392b682d2a8329e087cef"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4748321b5078216070b151d5271ef3e7cc905ab170bbfd27d5c83ee3ec436695"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:847a35c4d58721c5dc3dba599878ebbdfd96784f3fb8bb2c356e123bdcd73f34"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3c40d4eaad41f78e3bbda31b89edc46a3f3dc6e171bf0ecf097ff7a0ffff7cb1"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:21a5e440dbe315ab9825fcd459b8814bb92b27c974cbc23c3e8baa2b76890077"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:01dd777215e2aa86dfd664daed5957704b769e726626393438f9c87690ce78c3"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4b06beb3b3f1479d32befd1f3079cc47b34fa2da62457cdf6c963393340b56e9"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:564d7922e4b13a16b98772441879fcdcbe82ff50daa622d681dd682175ea918c"},
+    {file = "pydantic_core-2.18.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:0eb2a4f660fcd8e2b1c90ad566db2b98d7f3f4717c64fe0a83e0adb39766d5b8"},
+    {file = "pydantic_core-2.18.4-cp312-none-win32.whl", hash = "sha256:8b8bab4c97248095ae0c4455b5a1cd1cdd96e4e4769306ab19dda135ea4cdb07"},
+    {file = "pydantic_core-2.18.4-cp312-none-win_amd64.whl", hash = "sha256:14601cdb733d741b8958224030e2bfe21a4a881fb3dd6fbb21f071cabd48fa0a"},
+    {file = "pydantic_core-2.18.4-cp312-none-win_arm64.whl", hash = "sha256:c1322d7dd74713dcc157a2b7898a564ab091ca6c58302d5c7b4c07296e3fd00f"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:823be1deb01793da05ecb0484d6c9e20baebb39bd42b5d72636ae9cf8350dbd2"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:ebef0dd9bf9b812bf75bda96743f2a6c5734a02092ae7f721c048d156d5fabae"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ae1d6df168efb88d7d522664693607b80b4080be6750c913eefb77e34c12c71a"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f9899c94762343f2cc2fc64c13e7cae4c3cc65cdfc87dd810a31654c9b7358cc"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:99457f184ad90235cfe8461c4d70ab7dd2680e28821c29eca00252ba90308c78"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18f469a3d2a2fdafe99296a87e8a4c37748b5080a26b806a707f25a902c040a8"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b7cdf28938ac6b8b49ae5e92f2735056a7ba99c9b110a474473fd71185c1af5d"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:938cb21650855054dc54dfd9120a851c974f95450f00683399006aa6e8abb057"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:44cd83ab6a51da80fb5adbd9560e26018e2ac7826f9626bc06ca3dc074cd198b"},
+    {file = "pydantic_core-2.18.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:972658f4a72d02b8abfa2581d92d59f59897d2e9f7e708fdabe922f9087773af"},
+    {file = "pydantic_core-2.18.4-cp38-none-win32.whl", hash = "sha256:1d886dc848e60cb7666f771e406acae54ab279b9f1e4143babc9c2258213daa2"},
+    {file = "pydantic_core-2.18.4-cp38-none-win_amd64.whl", hash = "sha256:bb4462bd43c2460774914b8525f79b00f8f407c945d50881568f294c1d9b4443"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:44a688331d4a4e2129140a8118479443bd6f1905231138971372fcde37e43528"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a2fdd81edd64342c85ac7cf2753ccae0b79bf2dfa063785503cb85a7d3593223"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:86110d7e1907ab36691f80b33eb2da87d780f4739ae773e5fc83fb272f88825f"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:46387e38bd641b3ee5ce247563b60c5ca098da9c56c75c157a05eaa0933ed154"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:123c3cec203e3f5ac7b000bd82235f1a3eced8665b63d18be751f115588fea30"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dc1803ac5c32ec324c5261c7209e8f8ce88e83254c4e1aebdc8b0a39f9ddb443"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:53db086f9f6ab2b4061958d9c276d1dbe3690e8dd727d6abf2321d6cce37fa94"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:abc267fa9837245cc28ea6929f19fa335f3dc330a35d2e45509b6566dc18be23"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:a0d829524aaefdebccb869eed855e2d04c21d2d7479b6cada7ace5448416597b"},
+    {file = "pydantic_core-2.18.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:509daade3b8649f80d4e5ff21aa5673e4ebe58590b25fe42fac5f0f52c6f034a"},
+    {file = "pydantic_core-2.18.4-cp39-none-win32.whl", hash = "sha256:ca26a1e73c48cfc54c4a76ff78df3727b9d9f4ccc8dbee4ae3f73306a591676d"},
+    {file = "pydantic_core-2.18.4-cp39-none-win_amd64.whl", hash = "sha256:c67598100338d5d985db1b3d21f3619ef392e185e71b8d52bceacc4a7771ea7e"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:574d92eac874f7f4db0ca653514d823a0d22e2354359d0759e3f6a406db5d55d"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1f4d26ceb5eb9eed4af91bebeae4b06c3fb28966ca3a8fb765208cf6b51102ab"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:77450e6d20016ec41f43ca4a6c63e9fdde03f0ae3fe90e7c27bdbeaece8b1ed4"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d323a01da91851a4f17bf592faf46149c9169d68430b3146dcba2bb5e5719abc"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:43d447dd2ae072a0065389092a231283f62d960030ecd27565672bd40746c507"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:578e24f761f3b425834f297b9935e1ce2e30f51400964ce4801002435a1b41ef"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:81b5efb2f126454586d0f40c4d834010979cb80785173d1586df845a632e4e6d"},
+    {file = "pydantic_core-2.18.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:ab86ce7c8f9bea87b9d12c7f0af71102acbf5ecbc66c17796cff45dae54ef9a5"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:90afc12421df2b1b4dcc975f814e21bc1754640d502a2fbcc6d41e77af5ec312"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:51991a89639a912c17bef4b45c87bd83593aee0437d8102556af4885811d59f5"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:293afe532740370aba8c060882f7d26cfd00c94cae32fd2e212a3a6e3b7bc15e"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b48ece5bde2e768197a2d0f6e925f9d7e3e826f0ad2271120f8144a9db18d5c8"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:eae237477a873ab46e8dd748e515c72c0c804fb380fbe6c85533c7de51f23a8f"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:834b5230b5dfc0c1ec37b2fda433b271cbbc0e507560b5d1588e2cc1148cf1ce"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:e858ac0a25074ba4bce653f9b5d0a85b7456eaddadc0ce82d3878c22489fa4ee"},
+    {file = "pydantic_core-2.18.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:2fd41f6eff4c20778d717af1cc50eca52f5afe7805ee530a4fbd0bae284f16e9"},
+    {file = "pydantic_core-2.18.4.tar.gz", hash = "sha256:ec3beeada09ff865c344ff3bc2f427f5e6c26401cc6113d77e372c3fdac73864"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
+
 [[package]]
 name = "pytest"
 version = "7.4.2"
@@ -557,6 +678,17 @@ files = [
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
+[[package]]
+name = "typing-extensions"
+version = "4.12.2"
+description = "Backported and Experimental Type Hints for Python 3.8+"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
+    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
+]
+
 [[package]]
 name = "tzdata"
 version = "2023.3"
@@ -607,5 +739,5 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.10,<3.13"
-content-hash = "371781da268d5f61d6e798c023777f337b620e9b07a48c316825d7b998b63f02"
+python-versions = ">=3.9,<3.13"
+content-hash = "21ef9cfb35c446a375a2b74c37691d7031afb1e4f66a8b63cb7c1669470689d2"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.3.28"
+version = "0.3.33"
 description = "Real estate scraping library"
 authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/Bunsly/HomeHarvest"
@@ -13,6 +13,7 @@ homeharvest = "homeharvest.cli:main"
 python = ">=3.9,<3.13"
 requests = "^2.31.0"
 pandas = "^2.1.1"
+pydantic = "^2.7.4"
 
 
 [tool.poetry.group.dev.dependencies]

tests/test_realtor.py

@@ -4,7 +4,7 @@ from homeharvest import scrape_property
 def test_realtor_pending_or_contingent():
     pending_or_contingent_result = scrape_property(location="Surprise, AZ", listing_type="pending")
 
-    regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
+    regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale", exclude_pending=True)
 
     assert all([result is not None for result in [pending_or_contingent_result, regular_result]])
     assert len(pending_or_contingent_result) != len(regular_result)
@@ -165,3 +165,23 @@ def test_pr_zip_code():
     )
 
     assert results is not None and len(results) > 0
+
+
+def test_exclude_pending():
+    results = scrape_property(
+        location="33567",
+        listing_type="pending",
+        exclude_pending=True,
+    )
+
+    assert results is not None and len(results) > 0
+
+
+def test_style_value_error():
+    results = scrape_property(
+        location="Alaska, AK",
+        listing_type="sold",
+        extra_property_data=False,
+    )
+
+    assert results is not None and len(results) > 0