fix: govt type (#82)

- updated docs
- classified exception

README.md

@@ -21,7 +21,7 @@
 ```bash
 pip install -U homeharvest
 ```
-  _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
+  _Python version >= [3.9](https://www.python.org/downloads/release/python-3100/) required_
 
 ## Usage
 
@@ -43,7 +43,6 @@ properties = scrape_property(
   # date_from="2023-05-01", # alternative to past_days
   # date_to="2023-05-28",
   # foreclosure=True
-
   # mls_only=True,  # only fetch MLS listings
 )
 print(f"Number of properties: {len(properties)}")
@@ -91,7 +90,11 @@ 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 (True/False): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
+│
+└── exclude_pending (True/False): If set, excludes pending properties from the results unless listing_type is 'pending'
 ```
 
 ### Property Schema
@@ -128,18 +131,29 @@ Property
 │ ├── sold_price
 │ ├── last_sold_date
 │ ├── price_per_sqft
+│ ├── parking_garage
 │ └── hoa_fee
 
 ├── Location Details:
 │ ├── latitude
 │ ├── longitude
+│ ├── nearby_schools
 
-└── Parking Details:
+
-    └── parking_garage
+├── Agent Info:
+│ ├── agent
+│ ├── agent_email
+│ └── agent_phone
+
+├── Broker Info:
+│ ├── broker
+│ ├── broker_email
+│ └── broker_website
 ```
 
 ### Exceptions
 The following exceptions may be raised when using HomeHarvest:
 
 - `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
-- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
+- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD.
+- `AuthenticationError` - Realtor.com token request failed.

homeharvest/__init__.py

@@ -13,19 +13,24 @@ def scrape_property(
     mls_only: bool = False,
     past_days: int = None,
     proxy: str = None,
-    date_from: str = None,
+    date_from: str = None,  #: TODO: Switch to one parameter, Date, with date_from and date_to, pydantic validation
     date_to: str = None,
     foreclosure: bool = None,
+    extra_property_data: bool = True,
+    exclude_pending: bool = False,
 ) -> 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
     :param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
     :param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
-    :param proxy: Proxy to use for scraping
+    :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.
     """
     validate_input(listing_type)
     validate_dates(date_from, date_to)
@@ -40,15 +45,18 @@ def scrape_property(
         date_from=date_from,
         date_to=date_to,
         foreclosure=foreclosure,
+        extra_property_data=extra_property_data,
+        exclude_pending=exclude_pending,
     )
 
     site = RealtorScraper(scraper_input)
     results = site.search()
 
-    properties_dfs = [process_result(result) for result in results]
+    properties_dfs = [df for result in results if not (df := process_result(result)).empty]
     if not properties_dfs:
         return pd.DataFrame()
 
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", category=FutureWarning)
-        return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties]
+
+        return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace({"None": pd.NA, None: pd.NA, "": pd.NA})

homeharvest/core/scrapers/__init__.py

@@ -1,7 +1,12 @@
+from __future__ import annotations
 from dataclasses import dataclass
 import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
 import uuid
+from ...exceptions import AuthenticationError
 from .models import Property, ListingType, SiteName
+import json
 
 
 @dataclass
@@ -9,33 +14,41 @@ class ScraperInput:
     location: str
     listing_type: ListingType
     radius: float | None = None
-    mls_only: bool | None = None
+    mls_only: bool | None = False
     proxy: str | None = None
     last_x_days: int | None = None
     date_from: str | None = None
     date_to: str | None = None
-    foreclosure: bool | None = None
+    foreclosure: bool | None = False
+    extra_property_data: bool | None = True
+    exclude_pending: bool | None = False
 
 
 class Scraper:
+    session = None
+
     def __init__(
         self,
         scraper_input: ScraperInput,
-        session: requests.Session = None,
     ):
         self.location = scraper_input.location
         self.listing_type = scraper_input.listing_type
 
-        if not session:
+        if not self.session:
-            self.session = requests.Session()
+            Scraper.session = requests.Session()
-            self.session.headers.update(
+            retries = Retry(
+                total=3, backoff_factor=3, status_forcelist=[429, 403], allowed_methods=frozenset(["GET", "POST"])
+            )
+
+            adapter = HTTPAdapter(max_retries=retries)
+            Scraper.session.mount("http://", adapter)
+            Scraper.session.mount("https://", adapter)
+            Scraper.session.headers.update(
                 {
                     "auth": f"Bearer {self.get_access_token()}",
                     "apollographql-client-name": "com.move.Realtor-apollo-ios",
                 }
             )
-        else:
-            self.session = session
 
         if scraper_input.proxy:
             proxy_url = scraper_input.proxy
@@ -49,6 +62,8 @@ class Scraper:
         self.date_from = scraper_input.date_from
         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
 
     def search(self) -> list[Property]: ...
 
@@ -57,19 +72,34 @@ class Scraper:
 
     def handle_location(self): ...
 
-    def get_access_token(self):
+    @staticmethod
-        url = "https://graph.realtor.com/auth/token"
+    def get_access_token():
+        device_id = str(uuid.uuid4()).upper()
 
-        payload = f'{{"client_app_id":"rdc_mobile_native,24.20.4.149916,iphone","device_id":"{str(uuid.uuid4()).upper()}","grant_type":"device_mobile"}}'
+        response = requests.post(
-        headers = {
+            "https://graph.realtor.com/auth/token",
-            "Host": "graph.realtor.com",
+            headers={
-            "x-client-version": "24.20.4.149916",
+                'Host': 'graph.realtor.com',
-            "accept": "*/*",
+                'Accept': '*/*',
-            "content-type": "Application/json",
+                'Content-Type': 'Application/json',
-            "user-agent": "Realtor.com/24.20.4.149916 CFNetwork/1410.0.3 Darwin/22.6.0",
+                'X-Client-ID': 'rdc_mobile_native,iphone',
-            "accept-language": "en-US,en;q=0.9",
+                'X-Visitor-ID': device_id,
-        }
+                'X-Client-Version': '24.21.23.679885',
-        response = requests.post(url, headers=headers, data=payload)
+                'Accept-Language': 'en-US,en;q=0.9',
+                'User-Agent': 'Realtor.com/24.21.23.679885 CFNetwork/1494.0.7 Darwin/23.4.0',
+            },
+            data=json.dumps({
+                "grant_type": "device_mobile",
+                "device_id": device_id,
+                "client_app_id": "rdc_mobile_native,24.21.23.679885,iphone"
+            }))
 
         data = response.json()
-        return data["access_token"]
+
+        if not (access_token := data.get("access_token")):
+            raise AuthenticationError(
+                "Failed to get access token, use a proxy/vpn or wait a moment and try again.",
+                response=response
+            )
+
+        return access_token

homeharvest/core/scrapers/models.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 from dataclasses import dataclass
 from enum import Enum
 from typing import Optional
@@ -23,13 +24,22 @@ class ListingType(Enum):
     SOLD = "SOLD"
 
 
+@dataclass
+class Agent:
+    name: str | None = None
+    phone: str | None = None
+
+
 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"
+    CONDOP = "CONDOP"
     CONDOS = "CONDOS"
     COOP = "COOP"
     DUPLEX_TRIPLEX = "DUPLEX_TRIPLEX"
@@ -46,6 +56,7 @@ class PropertyType(Enum):
 
 @dataclass
 class Address:
+    full_line: str | None = None
     street: str | None = None
     unit: str | None = None
     city: str | None = None
@@ -67,12 +78,30 @@ class Description:
     year_built: int | None = None
     garage: float | None = None
     stories: int | None = None
+    text: str | None = None
+
+
+@dataclass
+class AgentPhone:  #: For documentation purposes only (at the moment)
+    number: str | None = None
+    type: str | None = None
+    primary: bool | None = None
+    ext: str | None = None
 
 
 @dataclass
 class Agent:
+    name: str | None = None
+    phones: list[dict] | AgentPhone | None = None
+    email: str | None = None
+    href: str | None = None
+
+
+@dataclass
+class Broker:
     name: str | None = None
     phone: str | None = None
+    website: str | None = None
 
 
 @dataclass
@@ -95,5 +124,10 @@ class Property:
     latitude: float | None = None
     longitude: float | None = None
     neighborhoods: Optional[str] = None
-
+    county: Optional[str] = None
-    agents: list[Agent] = None
+    fips_code: Optional[str] = None
+    agents: list[Agent] | None = None
+    brokers: list[Broker] | None = None
+    nearby_schools: list[str] = None
+    assessed_value: int | None = None
+    estimated_value: int | None = None

homeharvest/core/scrapers/realtor/__init__.py

@@ -5,12 +5,13 @@ 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
 from typing import Dict, Union, Optional
-from concurrent.futures import ThreadPoolExecutor, as_completed
 
 from .. import Scraper
-from ..models import Property, Address, ListingType, Description, PropertyType, Agent
+from ..models import Property, Address, ListingType, Description, PropertyType, Agent, Broker
 
 
 class RealtorScraper(Scraper):
@@ -52,6 +53,7 @@ class RealtorScraper(Scraper):
                             listing_id
                         }
                         address {
+                            line
                             street_direction
                             street_number
                             street_name
@@ -141,6 +143,9 @@ class RealtorScraper(Scraper):
             if days_on_mls and days_on_mls < 0:
                 days_on_mls = None
 
+        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=(
@@ -148,7 +153,7 @@ class RealtorScraper(Scraper):
                 if "source" in property_info and isinstance(property_info["source"], dict)
                 else None
             ),
-            property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
+            property_url=f"{self.PROPERTY_URL}{property_id}",
             status=property_info["basic"]["status"].upper(),
             list_price=property_info["basic"]["price"],
             list_date=list_date,
@@ -163,8 +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.get("media", {}).get("photos", [])),
+                alt_photos=(
-                style=property_info["basic"].get("type", "").upper(),
+                    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"),
@@ -174,8 +183,14 @@ class RealtorScraper(Scraper):
                 year_built=property_info["details"].get("year_built"),
                 garage=property_info["details"].get("garage"),
                 stories=property_info["details"].get("stories"),
+                text=property_info.get("description", {}).get("text"),
             ),
             days_on_mls=days_on_mls,
+            agents=prop_details.get("agents"),
+            brokers=prop_details.get("brokers"),
+            nearby_schools=prop_details.get("schools"),
+            assessed_value=prop_details.get("assessed_value"),
+            estimated_value=prop_details.get("estimated_value"),
         )
 
         return [listing]
@@ -228,6 +243,7 @@ class RealtorScraper(Scraper):
                             stories
                         }
                         address {
+                            line
                             street_direction
                             street_number
                             street_name
@@ -269,6 +285,7 @@ class RealtorScraper(Scraper):
                 }"""
 
         variables = {"property_id": property_id}
+        prop_details = self.get_prop_details(property_id)
 
         payload = {
             "query": query,
@@ -286,6 +303,11 @@ class RealtorScraper(Scraper):
                 property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
                 address=self._parse_address(property_info, search_type="handle_address"),
                 description=self._parse_description(property_info),
+                agents=prop_details.get("agents"),
+                brokers=prop_details.get("brokers"),
+                nearby_schools=prop_details.get("schools"),
+                assessed_value=prop_details.get("assessed_value"),
+                estimated_value=prop_details.get("estimated_value"),
             )
         ]
 
@@ -323,6 +345,7 @@ class RealtorScraper(Scraper):
                                     type
                                     name
                                     stories
+                                    text
                                 }
                                 source {
                                     id
@@ -337,6 +360,7 @@ class RealtorScraper(Scraper):
                                         street_number
                                         street_name
                                         street_suffix
+                                        line
                                         unit
                                         city
                                         state_code
@@ -346,10 +370,17 @@ class RealtorScraper(Scraper):
                                             lat
                                         }
                                     }
+                                    county {
+                                        name
+                                        fips_code
+                                    }
                                     neighborhoods {
                                         name
                                     }
                                 }
+                                tax_record {
+                                    public_record_id
+                                }
                                 primary_photo {
                                     href
                                 }
@@ -470,7 +501,6 @@ class RealtorScraper(Scraper):
         }
 
         response = self.session.post(self.SEARCH_GQL_URL, json=payload)
-        response.raise_for_status()
         response_json = response.json()
         search_key = "home_search" if "home_search" in query else "property_search"
 
@@ -501,11 +531,11 @@ class RealtorScraper(Scraper):
 
             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"]
-            agents = self.get_agents(property_id)
+            prop_details = self.get_prop_details(property_id)
 
             realty_property = Property(
                 mls=mls,
@@ -529,8 +559,15 @@ class RealtorScraper(Scraper):
                 longitude=result["location"]["address"]["coordinate"].get("lon") if able_to_get_lat_long else None,
                 address=self._parse_address(result, search_type="general_search"),
                 description=self._parse_description(result),
+                neighborhoods=self._parse_neighborhoods(result),
+                county=result["location"]["county"].get("name") if result["location"]["county"] else None,
+                fips_code=result["location"]["county"].get("fips_code") if result["location"]["county"] else None,
                 days_on_mls=self.calculate_days_on_mls(result),
-                agents=agents,
+                agents=prop_details.get("agents"),
+                brokers=prop_details.get("brokers"),
+                nearby_schools=prop_details.get("schools"),
+                assessed_value=prop_details.get("assessed_value"),
+                estimated_value=prop_details.get("estimated_value"),
             )
             return realty_property
 
@@ -625,18 +662,87 @@ class RealtorScraper(Scraper):
 
         return homes
 
-    def get_agents(self, property_id: str) -> list[Agent]:
+    def get_prop_details(self, property_id: str) -> dict:
-        payload = f'{{"query":"query GetHome($property_id: ID!) {{\\n  home(property_id: $property_id) {{\\n    __typename\\n\\n    consumerAdvertisers: consumer_advertisers {{\\n      __typename\\n      type\\n      advertiserId: advertiser_id\\n      name\\n      phone\\n      type\\n      href\\n      slogan\\n      photo {{\\n        __typename\\n        href\\n      }}\\n      showRealtorLogo: show_realtor_logo\\n      hours\\n    }}\\n\\n\\n  }}\\n}}\\n","variables":{{"property_id":"{property_id}"}}}}'
+        if not self.extra_property_data:
-        response = self.session.post(self.PROPERTY_GQL, data=payload)
+            return {}
 
+        #: TODO: migrate "advertisers" and "estimates" to general query
+
+        query = """query GetHome($property_id: ID!) {
+                    home(property_id: $property_id) {
+                        __typename
+
+                        advertisers {
+                            __typename
+                            type
+                            name
+                            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 } }
+                        }
+                        taxHistory: tax_history { __typename tax year assessment { __typename building land total } }
+                        estimates {
+                            __typename
+                            currentValues: current_values {
+                                __typename
+                                source { __typename type name }
+                                estimate
+                                estimateHigh: estimate_high
+                                estimateLow: estimate_low
+                                date
+                                isBestHomeValue: isbest_homevalue
+                            }
+                        }
+                    }
+                }"""
+
+        variables = {"property_id": property_id}
+        response = self.session.post(self.PROPERTY_GQL, json={"query": query, "variables": variables})
         data = response.json()
-        try:
-            ads = data["data"]["home"]["consumerAdvertisers"]
-        except (KeyError, TypeError):
-            return []
 
-        agents = [Agent(name=ad["name"], phone=ad["phone"]) for ad in ads]
+        def get_key(keys: list):
-        return agents
+            try:
+                value = data
+                for key in keys:
+                    value = value[key]
+
+                return value or {}
+            except (KeyError, TypeError, IndexError):
+                return {}
+
+        agents = get_key(["data", "home", "advertisers"])
+        advertisers = get_key(["data", "home", "consumer_advertisers"])
+
+        schools = get_key(["data", "home", "nearbySchools", "schools"])
+        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]
+
+        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")]
+        return {
+            "agents": agents if agents else None,
+            "brokers": brokers if brokers else None,
+            "schools": schools if schools else None,
+            "assessed_value": assessed_value if assessed_value else None,
+            "estimated_value": estimated_value if estimated_value else None,
+        }
 
     @staticmethod
     def _parse_neighborhoods(result: dict) -> Optional[str]:
@@ -658,20 +764,24 @@ class RealtorScraper(Scraper):
 
         return address_part
 
-    def _parse_address(self, result: dict, search_type):
+    @staticmethod
+    def _parse_address(result: dict, search_type):
         if search_type == "general_search":
             address = result["location"]["address"]
         else:
             address = result["address"]
 
         return Address(
+            full_line=address.get("line"),
             street=" ".join(
-                [
+                part
-                    self.handle_none_safely(address.get("street_number")),
+                for part in [
-                    self.handle_none_safely(address.get("street_direction")),
+                    address.get("street_number"),
-                    self.handle_none_safely(address.get("street_name")),
+                    address.get("street_direction"),
-                    self.handle_none_safely(address.get("street_suffix")),
+                    address.get("street_name"),
+                    address.get("street_suffix"),
                 ]
+                if part is not None
             ).strip(),
             unit=address["unit"],
             city=address["city"],
@@ -699,17 +809,22 @@ class RealtorScraper(Scraper):
 
         return Description(
             primary_photo=primary_photo,
-            alt_photos=RealtorScraper.process_alt_photos(result.get("photos")),
+            alt_photos=RealtorScraper.process_alt_photos(result.get("photos", [])),
-            style=PropertyType(style) if style else None,
+            style=PropertyType.__getitem__(style) if style and style in PropertyType.__members__ else None,
             beds=description_data.get("beds"),
             baths_full=description_data.get("baths_full"),
             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"),
+            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"),
+            text=description_data.get("text"),
         )
 
     @staticmethod

homeharvest/exceptions.py

@@ -4,3 +4,11 @@ class InvalidListingType(Exception):
 
 class InvalidDate(Exception):
     """Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23"""
+
+
+class AuthenticationError(Exception):
+    """Raised when there is an issue with the authentication process."""
+    def __init__(self, *args, response):
+        super().__init__(*args)
+
+        self.response = response

homeharvest/utils.py

@@ -1,6 +1,7 @@
+from __future__ import annotations
 import pandas as pd
 from datetime import datetime
-from .core.scrapers.models import Property, ListingType
+from .core.scrapers.models import Property, ListingType, Agent
 from .exceptions import InvalidListingType, InvalidDate
 
 ordered_properties = [
@@ -8,7 +9,9 @@ ordered_properties = [
     "mls",
     "mls_id",
     "status",
+    "text",
     "style",
+    "full_street_line",
     "street",
     "unit",
     "city",
@@ -24,16 +27,25 @@ ordered_properties = [
     "list_date",
     "sold_price",
     "last_sold_date",
+    "assessed_value",
+    "estimated_value",
     "lot_sqft",
     "price_per_sqft",
     "latitude",
     "longitude",
+    "neighborhoods",
+    "county",
+    "fips_code",
     "stories",
     "hoa_fee",
     "parking_garage",
     "agent",
+    "agent_email",
+    "agent_phones",
     "broker",
     "broker_phone",
+    "broker_website",
+    "nearby_schools",
     "primary_photo",
     "alt_photos",
 ]
@@ -45,6 +57,7 @@ def process_result(result: Property) -> pd.DataFrame:
 
     if "address" in prop_data:
         address_data = prop_data["address"]
+        prop_data["full_street_line"] = address_data.full_line
         prop_data["street"] = address_data.street
         prop_data["unit"] = address_data.unit
         prop_data["city"] = address_data.city
@@ -52,28 +65,38 @@ def process_result(result: Property) -> pd.DataFrame:
         prop_data["zip_code"] = address_data.zip
 
     if "agents" in prop_data:
-        agents = prop_data["agents"]
+        agents: list[Agent] | None = prop_data["agents"]
         if agents:
             prop_data["agent"] = agents[0].name
-            if len(agents) > 1:
+            prop_data["agent_email"] = agents[0].email
-                prop_data["broker"] = agents[1].name
+            prop_data["agent_phones"] = agents[0].phones
-                prop_data["broker_phone"] = agents[1].phone
+
+    if "brokers" in prop_data:
+        brokers = prop_data["brokers"]
+        if brokers:
+            prop_data["broker"] = brokers[0].name
+            prop_data["broker_phone"] = brokers[0].phone
+            prop_data["broker_website"] = brokers[0].website
 
     prop_data["price_per_sqft"] = prop_data["prc_sqft"]
+    prop_data["nearby_schools"] = filter(None, prop_data["nearby_schools"]) if prop_data["nearby_schools"] else None
+    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
+    if description:
-    prop_data["alt_photos"] = ", ".join(description.alt_photos)
+        prop_data["primary_photo"] = description.primary_photo
-    prop_data["style"] = description.style.value
+        prop_data["alt_photos"] = ", ".join(description.alt_photos) if description.alt_photos else None
-    prop_data["beds"] = description.beds
+        prop_data["style"] = description.style if isinstance(description.style, str) else description.style.value if description.style else None
-    prop_data["full_baths"] = description.baths_full
+        prop_data["beds"] = description.beds
-    prop_data["half_baths"] = description.baths_half
+        prop_data["full_baths"] = description.baths_full
-    prop_data["sqft"] = description.sqft
+        prop_data["half_baths"] = description.baths_half
-    prop_data["lot_sqft"] = description.lot_sqft
+        prop_data["sqft"] = description.sqft
-    prop_data["sold_price"] = description.sold_price
+        prop_data["lot_sqft"] = description.lot_sqft
-    prop_data["year_built"] = description.year_built
+        prop_data["sold_price"] = description.sold_price
-    prop_data["parking_garage"] = description.garage
+        prop_data["year_built"] = description.year_built
-    prop_data["stories"] = description.stories
+        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)
@@ -97,5 +120,5 @@ def validate_dates(date_from: str | None, date_to: str | None) -> None:
 
             if date_to_obj < date_from_obj:
                 raise InvalidDate("date_to must be after date_from.")
-        except ValueError as e:
+        except ValueError:
             raise InvalidDate(f"Invalid date format or range")

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"
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+    {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"
+python-versions = ">=3.9,<3.13"
-content-hash = "371781da268d5f61d6e798c023777f337b620e9b07a48c316825d7b998b63f02"
+content-hash = "21ef9cfb35c446a375a2b74c37691d7031afb1e4f66a8b63cb7c1669470689d2"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.3.16"
+version = "0.3.31"
 description = "Real estate scraping library"
 authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/Bunsly/HomeHarvest"
@@ -10,9 +10,10 @@ readme = "README.md"
 homeharvest = "homeharvest.cli:main"
 
 [tool.poetry.dependencies]
-python = ">=3.10,<3.13"
+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)
@@ -142,3 +142,46 @@ def test_realtor_foreclosed():
 def test_realtor_agent():
     scraped = scrape_property(location="Detroit, MI", listing_type="for_sale")
     assert scraped["agent"].nunique() > 1
+
+
+def test_realtor_without_extra_details():
+    results = [
+        scrape_property(
+            location="15509 N 172nd Dr, Surprise, AZ 85388",
+            extra_property_data=False,
+        ),
+        scrape_property(
+            location="15509 N 172nd Dr, Surprise, AZ 85388",
+        ),
+    ]
+
+    assert not results[0].equals(results[1])
+
+
+def test_pr_zip_code():
+    results = scrape_property(
+        location="00741",
+        listing_type="for_sale",
+    )
+
+    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