fix: govt type (#82)

- updated docs
- classified exception

.github/workflows/publish-to-pypi.yml

@@ -30,4 +30,4 @@ jobs:
       if: startsWith(github.ref, 'refs/tags')
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        password: ${{ secrets.PYPI_API_TOKEN }}
+        password: ${{ secrets.PYPI_API_TOKEN }}

.gitignore

@@ -4,4 +4,4 @@
 **/.pytest_cache/
 *.pyc
 /.ipynb_checkpoints/
-*.csv
+*.csv

.pre-commit-config.yaml

@@ -0,0 +1,21 @@
+---
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.2.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-added-large-files
+      - id: check-yaml
+  - repo: https://github.com/adrienverge/yamllint
+    rev: v1.29.0
+    hooks:
+      - id: yamllint
+        verbose: true # create awareness of linter findings
+        args: ["-d", "{extends: relaxed, rules: {line-length: {max: 120}}}"]
+  - repo: https://github.com/psf/black
+    rev: 24.2.0
+    hooks:
+    - id: black
+      language_version: python
+      args: [--line-length=120, --quiet]

README.md

@@ -1,24 +1,16 @@
 <img src="https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/d1a2bf8b-09f5-4c57-b33a-0ada8a34f12d" width="400">
 
-**HomeHarvest** is a simple, yet comprehensive, real estate scraping library that extracts and formats data in the style of MLS listings.
+**HomeHarvest** is a real estate scraping library that extracts and formats data in the style of MLS listings.
-
-[![Try with Replit](https://replit.com/badge?caption=Try%20with%20Replit)](https://replit.com/@ZacharyHampton/HomeHarvestDemo)
 
 **Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
 
-*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/bunsly/15min)** *to work with us.*
+*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com)** *to work with us.*
-
-Check out another project we wrote: ***[JobSpy](https://github.com/Bunsly/JobSpy)** – a Python package for job scraping*
 
 ## HomeHarvest Features
 
 - **Source**: Fetches properties directly from **Realtor.com**.
 - **Data Format**: Structures data to resemble MLS listings.
 - **Export Flexibility**: Options to save as either CSV or Excel.
-- **Usage Modes**:
-  - **Python**: For those who'd like to integrate scraping into their Python scripts.
-  - **CLI**: For users who prefer command-line operations.
-
 
 [Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
 
@@ -27,9 +19,9 @@ Check out another project we wrote: ***[JobSpy](https://github.com/Bunsly/JobSpy
 ## Installation
 
 ```bash
-pip install homeharvest
+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
 
@@ -47,12 +39,11 @@ properties = scrape_property(
   location="San Diego, CA",
   listing_type="sold",  # or (for_sale, for_rent, pending)
   past_days=30,  # sold in last 30 days - listed in last 30 days if (for_sale, for_rent)
-  
+
-  # date_from="2023-05-01", # alternative to past_days 
+  # date_from="2023-05-01", # alternative to past_days
-  # date_to="2023-05-28", 
+  # date_to="2023-05-28",
-  
+  # foreclosure=True
   # mls_only=True,  # only fetch MLS listings
-  # proxy="http://user:pass@host:port"  # use a proxy to change your IP address
 )
 print(f"Number of properties: {len(properties)}")
 
@@ -61,7 +52,6 @@ properties.to_csv(filename, index=False)
 print(properties.head())
 ```
 
-
 ## Output
 ```plaintext
 >>> properties.head()
@@ -91,43 +81,20 @@ Optional
 ├── past_days (integer): Number of past days to filter properties. Utilizes 'last_sold_date' for 'sold' listing types, and 'list_date' for others (for_rent, for_sale).
 │    Example: 30 (fetches properties listed/sold in the last 30 days)
 │
-├── date_range (string tuple): Start and end dates to filter properties listed or sold, both dates are required.
+├── date_from, date_to (string): Start and end dates to filter properties listed or sold, both dates are required.
-}    (use this to get properties in chunks as there's a 10k result limit)
+|    (use this to get properties in chunks as there's a 10k result limit)
-│    Format for both must be "YYYY-MM-DD". 
+│    Format for both must be "YYYY-MM-DD".
-│    Example: ("2023-05-01", "2023-05-15") (fetches properties listed/sold between these dates)
+│    Example: "2023-05-01", "2023-05-15" (fetches properties listed/sold between these dates)
 │
 ├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
 │
-└── proxy (string): In format 'http://user:pass@host:port'
+├── foreclosure (True/False): If set, fetches only foreclosures
-
+│
-```
+├── proxy (string): In format 'http://user:pass@host:port'
-
+│
-### CLI 
+├── 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'
-usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] [-c] location
-                                                                                                                             
-Home Harvest Property Scraper                                                                                                 
-                                                                                                                             
-positional arguments:                                                                                                         
-  location              Location to scrape (e.g., San Francisco, CA)                                                          
-                                                                                                                             
-options:                                                                                                                      
-  -l {for_sale,for_rent,sold,pending}, --listing_type {for_sale,for_rent,sold,pending}                                                        
-                        Listing type to scrape                                                                                
-  -o {excel,csv}, --output {excel,csv}                                                                                        
-                        Output format                                                                                         
-  -f FILENAME, --filename FILENAME                                                                                            
-                        Name of the output file (without extension)                                                           
-  -p PROXY, --proxy PROXY                                                                                                     
-                        Proxy to use for scraping                                                                             
-  -d DAYS, --days DAYS  Sold/listed in last _ days filter.                                                                           
-  -r RADIUS, --radius RADIUS                                                                                                  
-                        Get comparable properties within _ (e.g., 0.0) miles. Only applicable for individual addresses.        
-  -m, --mls_only        If set, fetches only MLS listings.                                                                    
-```
-```bash
-homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
 ```
 
 ### Property Schema
@@ -160,39 +127,33 @@ Property
 │ ├── days_on_mls
 │ ├── list_price
 │ ├── list_date
+│ ├── pending_date
 │ ├── 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`
-- `NoResultsFound` - no properties found from your search
+- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD.
-  
+- `AuthenticationError` - Realtor.com token request failed.
-  
-## Frequently Asked Questions
----
-
-**Q: Encountering issues with your searches?**  
-**A:** Try to broaden the parameters you're using. If problems persist, [submit an issue](https://github.com/ZacharyHampton/HomeHarvest/issues).
-
----
-
-**Q: Received a Forbidden 403 response code?**  
-**A:** This indicates that you have been blocked by Realtor.com for sending too many requests. We recommend:
-
-- Waiting a few seconds between requests.
-- Trying a VPN or useing a proxy as a parameter to scrape_property() to change your IP address.
-
----
-

homeharvest/__init__.py

@@ -13,18 +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)
@@ -38,15 +44,19 @@ def scrape_property(
         last_x_days=past_days,
         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/cli.py

@@ -5,9 +5,7 @@ from homeharvest import scrape_property
 
 def main():
     parser = argparse.ArgumentParser(description="Home Harvest Property Scraper")
-    parser.add_argument(
+    parser.add_argument("location", type=str, help="Location to scrape (e.g., San Francisco, CA)")
-        "location", type=str, help="Location to scrape (e.g., San Francisco, CA)"
-    )
 
     parser.add_argument(
         "-l",
@@ -35,9 +33,7 @@ def main():
         help="Name of the output file (without extension)",
     )
 
-    parser.add_argument(
+    parser.add_argument("-p", "--proxy", type=str, default=None, help="Proxy to use for scraping")
-        "-p", "--proxy", type=str, default=None, help="Proxy to use for scraping"
-    )
     parser.add_argument(
         "-d",
         "--days",

homeharvest/core/scrapers/__init__.py

@@ -1,6 +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
@@ -8,26 +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 = 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()
-        else:
+            retries = Retry(
-            self.session = session
+                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",
+                }
+            )
 
         if scraper_input.proxy:
             proxy_url = scraper_input.proxy
@@ -40,13 +61,45 @@ class Scraper:
         self.mls_only = scraper_input.mls_only
         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]:
+    def search(self) -> list[Property]: ...
-        ...
 
     @staticmethod
-    def _parse_home(home) -> Property:
+    def _parse_home(home) -> Property: ...
-        ...
 
-    def handle_location(self):
+    def handle_location(self): ...
-        ...
+
+    @staticmethod
+    def get_access_token():
+        device_id = str(uuid.uuid4()).upper()
+
+        response = requests.post(
+            "https://graph.realtor.com/auth/token",
+            headers={
+                'Host': 'graph.realtor.com',
+                'Accept': '*/*',
+                'Content-Type': 'Application/json',
+                'X-Client-ID': 'rdc_mobile_native,iphone',
+                'X-Visitor-ID': device_id,
+                'X-Client-Version': '24.21.23.679885',
+                '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()
+
+        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
@@ -23,8 +24,39 @@ 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"
+    FARM = "FARM"
+    INVESTMENT = "INVESTMENT"
+    LAND = "LAND"
+    MOBILE = "MOBILE"
+    MULTI_FAMILY = "MULTI_FAMILY"
+    RENTAL = "RENTAL"
+    SINGLE_FAMILY = "SINGLE_FAMILY"
+    TOWNHOMES = "TOWNHOMES"
+    OTHER = "OTHER"
+
+
 @dataclass
 class Address:
+    full_line: str | None = None
     street: str | None = None
     unit: str | None = None
     city: str | None = None
@@ -34,7 +66,9 @@ class Address:
 
 @dataclass
 class Description:
-    style: str | None = None
+    primary_photo: str | None = None
+    alt_photos: list[str] | None = None
+    style: PropertyType | None = None
     beds: int | None = None
     baths_full: int | None = None
     baths_half: int | None = None
@@ -44,6 +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
@@ -56,6 +114,7 @@ class Property:
 
     list_price: int | None = None
     list_date: str | None = None
+    pending_date: str | None = None
     last_sold_date: str | None = None
     prc_sqft: int | None = None
     hoa_fee: int | None = None
@@ -65,3 +124,10 @@ class Property:
     latitude: float | None = None
     longitude: float | None = None
     neighborhoods: Optional[str] = None
+    county: Optional[str] = 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

@@ -4,18 +4,22 @@ 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
+from ..models import Property, Address, ListingType, Description, PropertyType, Agent, Broker
 
 
 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"
+    NUM_PROPERTY_WORKERS = 20
 
     def __init__(self, scraper_input):
         super().__init__(scraper_input)
@@ -49,6 +53,8 @@ class RealtorScraper(Scraper):
                             listing_id
                         }
                         address {
+                            line
+                            street_direction
                             street_number
                             street_name
                             street_suffix
@@ -83,6 +89,11 @@ class RealtorScraper(Scraper):
                             garage
                             permalink
                         }
+                        media {
+                            photos {
+                                href
+                            }
+                        }
                     }
                 }"""
 
@@ -104,18 +115,22 @@ class RealtorScraper(Scraper):
         )
 
         able_to_get_lat_long = (
-                property_info
+            property_info
-                and property_info.get("address")
+            and property_info.get("address")
-                and property_info["address"].get("location")
+            and property_info["address"].get("location")
-                and property_info["address"]["location"].get("coordinate")
+            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_str = (
-            "list_date") else None
+            property_info["basic"]["list_date"].split("T")[0] if property_info["basic"].get("list_date") else None
-        last_sold_date_str = property_info["basic"]["sold_date"].split("T")[0] if property_info["basic"].get(
+        )
-            "sold_date") else None
+        last_sold_date_str = (
+            property_info["basic"]["sold_date"].split("T")[0] if property_info["basic"].get("sold_date") else None
+        )
+        pending_date_str = property_info["pending_date"].split("T")[0] if property_info.get("pending_date") else None
 
         list_date = datetime.strptime(list_date_str, "%Y-%m-%d") if list_date_str else None
         last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d") if last_sold_date_str else None
+        pending_date = datetime.strptime(pending_date_str, "%Y-%m-%d") if pending_date_str else None
         today = datetime.now()
 
         days_on_mls = None
@@ -123,35 +138,42 @@ class RealtorScraper(Scraper):
         if list_date:
             if status == "sold" and last_sold_date:
                 days_on_mls = (last_sold_date - list_date).days
-            elif status in ('for_sale', 'for_rent'):
+            elif status in ("for_sale", "for_rent"):
                 days_on_mls = (today - list_date).days
             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=property_info["source"].get("listing_id")
+            mls_id=(
-            if "source" in property_info and isinstance(property_info["source"], dict)
+                property_info["source"].get("listing_id")
-            else None,
+                if "source" in property_info and isinstance(property_info["source"], dict)
-            property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
+                else None
+            ),
+            property_url=f"{self.PROPERTY_URL}{property_id}",
             status=property_info["basic"]["status"].upper(),
             list_price=property_info["basic"]["price"],
             list_date=list_date,
-            prc_sqft=property_info["basic"].get("price")
+            prc_sqft=(
-                     / property_info["basic"].get("sqft")
+                property_info["basic"].get("price") / property_info["basic"].get("sqft")
-            if property_info["basic"].get("price")
+                if property_info["basic"].get("price") and property_info["basic"].get("sqft")
-               and property_info["basic"].get("sqft")
+                else None
-            else None,
+            ),
             last_sold_date=last_sold_date,
-            latitude=property_info["address"]["location"]["coordinate"].get("lat")
+            pending_date=pending_date,
-            if able_to_get_lat_long
+            latitude=property_info["address"]["location"]["coordinate"].get("lat") if able_to_get_lat_long else None,
-            else None,
+            longitude=property_info["address"]["location"]["coordinate"].get("lon") if able_to_get_lat_long else None,
-            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(
-                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"),
@@ -161,8 +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
+            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]
@@ -215,6 +243,8 @@ class RealtorScraper(Scraper):
                             stories
                         }
                         address {
+                            line
+                            street_direction
                             street_number
                             street_name
                             street_suffix
@@ -245,10 +275,17 @@ class RealtorScraper(Scraper):
                             units
                             year_built
                         }
+                        primary_photo {
+                            href
+                        }
+                        photos {
+                            href
+                        }
                     }
                 }"""
 
         variables = {"property_id": property_id}
+        prop_details = self.get_prop_details(property_id)
 
         payload = {
             "query": query,
@@ -264,16 +301,17 @@ class RealtorScraper(Scraper):
             Property(
                 mls_id=property_id,
                 property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
-                address=self._parse_address(
+                address=self._parse_address(property_info, search_type="handle_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"),
             )
         ]
 
-    def general_search(
+    def general_search(self, variables: dict, search_type: str) -> Dict[str, Union[int, list[Property]]]:
-        self, variables: dict, search_type: str
-    ) -> Dict[str, Union[int, list[Property]]]:
         """
         Handles a location area & returns a list of properties
         """
@@ -281,6 +319,7 @@ class RealtorScraper(Scraper):
                             count
                             total
                             results {
+                                pending_date
                                 property_id
                                 list_date
                                 status
@@ -293,6 +332,7 @@ class RealtorScraper(Scraper):
                                     is_pending
                                 }
                                 description {
+                                    type
                                     sqft
                                     beds
                                     baths_full
@@ -305,6 +345,7 @@ class RealtorScraper(Scraper):
                                     type
                                     name
                                     stories
+                                    text
                                 }
                                 source {
                                     id
@@ -315,9 +356,11 @@ class RealtorScraper(Scraper):
                                 }
                                 location {
                                     address {
+                                        street_direction
                                         street_number
                                         street_name
                                         street_suffix
+                                        line
                                         unit
                                         city
                                         state_code
@@ -327,10 +370,23 @@ class RealtorScraper(Scraper):
                                             lat
                                         }
                                     }
+                                    county {
+                                        name
+                                        fips_code
+                                    }
                                     neighborhoods {
                                         name
                                     }
                                 }
+                                tax_record {
+                                    public_record_id
+                                }
+                                primary_photo {
+                                    href
+                                }
+                                photos {
+                                    href
+                                }
                             }
                         }
                     }"""
@@ -354,12 +410,16 @@ class RealtorScraper(Scraper):
         )
 
         pending_or_contingent_param = (
-            "or_filters: { contingent: true, pending: true }"
+            "or_filters: { contingent: true, pending: true }" if self.listing_type == ListingType.PENDING else ""
-            if self.listing_type == ListingType.PENDING
-            else ""
         )
 
         listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
+        is_foreclosure = ""
+
+        if variables.get("foreclosure") is True:
+            is_foreclosure = "foreclosure: true"
+        elif variables.get("foreclosure") is False:
+            is_foreclosure = "foreclosure: false"
 
         if search_type == "comps":  #: comps search, came from an address
             query = """query Property_search(
@@ -368,10 +428,11 @@ class RealtorScraper(Scraper):
                     $offset: Int!,
                     ) {
                         home_search(
-                            query: { 
+                            query: {
+                                %s
                                 nearby: {
                                     coordinates: $coordinates
-                                    radius: $radius 
+                                    radius: $radius
                                 }
                                 status: %s
                                 %s
@@ -381,6 +442,7 @@ class RealtorScraper(Scraper):
                             limit: 200
                             offset: $offset
                     ) %s""" % (
+                is_foreclosure,
                 listing_type.value.lower(),
                 date_param,
                 pending_or_contingent_param,
@@ -397,6 +459,7 @@ class RealtorScraper(Scraper):
                             ) {
                                 home_search(
                                     query: {
+                                        %s
                                         city: $city
                                         county: $county
                                         postal_code: $postal_code
@@ -409,6 +472,7 @@ class RealtorScraper(Scraper):
                                     limit: 200
                                     offset: $offset
                                 ) %s""" % (
+                is_foreclosure,
                 listing_type.value.lower(),
                 date_param,
                 pending_or_contingent_param,
@@ -437,7 +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"
 
@@ -453,15 +516,11 @@ class RealtorScraper(Scraper):
         ):
             return {"total": 0, "properties": []}
 
-        for result in response_json["data"][search_key]["results"]:
+        def process_property(result: dict) -> Property | None:
-            mls = (
+            mls = result["source"].get("id") if "source" in result and isinstance(result["source"], dict) else None
-                result["source"].get("id")
-                if "source" in result and isinstance(result["source"], dict)
-                else None
-            )
 
             if not mls and self.mls_only:
-                continue
+                return
 
             able_to_get_lat_long = (
                 result
@@ -472,36 +531,55 @@ 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):
-                continue
+                return
+
+            property_id = result["property_id"]
+            prop_details = self.get_prop_details(property_id)
 
             realty_property = Property(
                 mls=mls,
-                mls_id=result["source"].get("listing_id")
+                mls_id=(
-                if "source" in result and isinstance(result["source"], dict)
+                    result["source"].get("listing_id")
-                else None,
+                    if "source" in result and isinstance(result["source"], dict)
-                property_url=f"{self.PROPERTY_URL}{result['property_id']}",
+                    else None
+                ),
+                property_url=(
+                    f"{self.PROPERTY_URL}{property_id}"
+                    if self.listing_type != ListingType.FOR_RENT
+                    else f"{self.PROPERTY_URL}M{property_id}?listing_status=rental"
+                ),
                 status="PENDING" if is_pending else result["status"].upper(),
                 list_price=result["list_price"],
-                list_date=result["list_date"].split("T")[0]
+                list_date=result["list_date"].split("T")[0] if result.get("list_date") else None,
-                if result.get("list_date")
-                else None,
                 prc_sqft=result.get("price_per_sqft"),
                 last_sold_date=result.get("last_sold_date"),
-                hoa_fee=result["hoa"]["fee"]
+                hoa_fee=result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) else None,
-                if result.get("hoa") and isinstance(result["hoa"], dict)
+                latitude=result["location"]["address"]["coordinate"].get("lat") if able_to_get_lat_long else None,
-                else None,
+                longitude=result["location"]["address"]["coordinate"].get("lon") if able_to_get_lat_long else None,
-                latitude=result["location"]["address"]["coordinate"].get("lat")
-                if able_to_get_lat_long
-                else None,
-                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),
-                days_on_mls=self.calculate_days_on_mls(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=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"),
             )
-            properties.append(realty_property)
+            return realty_property
+
+        with ThreadPoolExecutor(max_workers=self.NUM_PROPERTY_WORKERS) as executor:
+            futures = [
+                executor.submit(process_property, result) for result in response_json["data"][search_key]["results"]
+            ]
+
+            for future in as_completed(futures):
+                result = future.result()
+                if result:
+                    properties.append(result)
 
         return {
             "total": response_json["data"][search_key]["total"],
@@ -522,18 +600,14 @@ class RealtorScraper(Scraper):
         search_type = (
             "comps"
             if self.radius and location_type == "address"
-            else "address"
+            else "address" if location_type == "address" and not self.radius else "area"
-            if location_type == "address" and not self.radius
-            else "area"
         )
         if location_type == "address":
             if not self.radius:  #: single address search, non comps
                 property_id = location_info["mpr_id"]
                 search_variables |= {"property_id": property_id}
 
-                gql_results = self.general_search(
+                gql_results = self.general_search(search_variables, search_type=search_type)
-                    search_variables, search_type=search_type
-                )
                 if gql_results["total"] == 0:
                     listing_id = self.get_latest_listing_id(property_id)
                     if listing_id is None:
@@ -544,12 +618,20 @@ class RealtorScraper(Scraper):
                     return gql_results["properties"]
 
             else:  #: general search, comps (radius)
+                if not location_info.get("centroid"):
+                    return []
+
                 coordinates = list(location_info["centroid"].values())
                 search_variables |= {
                     "coordinates": coordinates,
                     "radius": "{}mi".format(self.radius),
                 }
 
+        elif location_type == "postal_code":
+            search_variables |= {
+                "postal_code": location_info.get("postal_code"),
+            }
+
         else:  #: general search, location
             search_variables |= {
                 "city": location_info.get("city"),
@@ -558,6 +640,9 @@ class RealtorScraper(Scraper):
                 "postal_code": location_info.get("postal_code"),
             }
 
+        if self.foreclosure:
+            search_variables["foreclosure"] = self.foreclosure
+
         result = self.general_search(search_variables, search_type=search_type)
         total = result["total"]
         homes = result["properties"]
@@ -577,6 +662,88 @@ class RealtorScraper(Scraper):
 
         return homes
 
+    def get_prop_details(self, property_id: str) -> dict:
+        if not self.extra_property_data:
+            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()
+
+        def get_key(keys: list):
+            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]:
         neighborhoods_list = []
@@ -597,18 +764,25 @@ 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']
+            address = result["location"]["address"]
         else:
             address = result["address"]
 
         return Address(
-            street=" ".join([
+            full_line=address.get("line"),
-                self.handle_none_safely(address.get('street_number')),
+            street=" ".join(
-                self.handle_none_safely(address.get('street_name')),
+                part
-                self.handle_none_safely(address.get('street_suffix')),
+                for part in [
-            ]).strip(),
+                    address.get("street_number"),
+                    address.get("street_direction"),
+                    address.get("street_name"),
+                    address.get("street_suffix"),
+                ]
+                if part is not None
+            ).strip(),
             unit=address["unit"],
             city=address["city"],
             state=address["state_code"],
@@ -626,17 +800,31 @@ class RealtorScraper(Scraper):
         if style is not None:
             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")
+
         return Description(
-            style=style,
+            primary_photo=primary_photo,
+            alt_photos=RealtorScraper.process_alt_photos(result.get("photos", [])),
+            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
@@ -648,12 +836,25 @@ class RealtorScraper(Scraper):
         today = datetime.now()
 
         if list_date:
-            if result["status"] == 'sold':
+            if result["status"] == "sold":
                 if last_sold_date:
                     days = (last_sold_date - list_date).days
                     if days >= 0:
                         return days
-            elif result["status"] in ('for_sale', 'for_rent'):
+            elif result["status"] in ("for_sale", "for_rent"):
                 days = (today - list_date).days
                 if days >= 0:
                     return days
+
+    @staticmethod
+    def process_alt_photos(photos_info):
+        try:
+            alt_photos = []
+            if photos_info:
+                for photo_info in photos_info:
+                    href = photo_info.get("href", "")
+                    alt_photo_href = href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
+                    alt_photos.append(alt_photo_href)
+            return alt_photos
+        except Exception:
+            pass

homeharvest/exceptions.py

@@ -1,5 +1,14 @@
 class InvalidListingType(Exception):
     """Raised when a provided listing type is does not exist."""
 
+
 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 """
+    """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",
@@ -24,13 +27,27 @@ 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",
 ]
 
 
@@ -40,25 +57,46 @@ 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
         prop_data["state"] = address_data.state
         prop_data["zip_code"] = address_data.zip
 
+    if "agents" in prop_data:
+        agents: list[Agent] | None = prop_data["agents"]
+        if agents:
+            prop_data["agent"] = agents[0].name
+            prop_data["agent_email"] = agents[0].email
+            prop_data["agent_phones"] = agents[0].phones
+
+    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["style"] = description.style
+    if description:
-    prop_data["beds"] = description.beds
+        prop_data["primary_photo"] = description.primary_photo
-    prop_data["full_baths"] = description.baths_full
+        prop_data["alt_photos"] = ", ".join(description.alt_photos) if description.alt_photos else None
-    prop_data["half_baths"] = description.baths_half
+        prop_data["style"] = description.style if isinstance(description.style, str) else description.style.value if description.style else None
-    prop_data["sqft"] = description.sqft
+        prop_data["beds"] = description.beds
-    prop_data["lot_sqft"] = description.lot_sqft
+        prop_data["full_baths"] = description.baths_full
-    prop_data["sold_price"] = description.sold_price
+        prop_data["half_baths"] = description.baths_half
-    prop_data["year_built"] = description.year_built
+        prop_data["sqft"] = description.sqft
-    prop_data["parking_garage"] = description.garage
+        prop_data["lot_sqft"] = description.lot_sqft
-    prop_data["stories"] = description.stories
+        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)
@@ -68,9 +106,7 @@ def process_result(result: Property) -> pd.DataFrame:
 
 def validate_input(listing_type: str) -> None:
     if listing_type.upper() not in ListingType.__members__:
-        raise InvalidListingType(
+        raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
-            f"Provided listing type, '{listing_type}', does not exist."
-        )
 
 
 def validate_dates(date_from: str | None, date_to: str | None) -> None:
@@ -84,5 +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

@@ -1,4 +1,15 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# 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"
@@ -11,6 +22,17 @@ files = [
     {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
 ]
 
+[[package]]
+name = "cfgv"
+version = "3.4.0"
+description = "Validate configuration and produce human readable error messages."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
+    {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
+]
+
 [[package]]
 name = "charset-normalizer"
 version = "3.3.0"
@@ -122,14 +144,14 @@ files = [
 ]
 
 [[package]]
-name = "et-xmlfile"
+name = "distlib"
-version = "1.1.0"
+version = "0.3.8"
-description = "An implementation of lxml.xmlfile for the standard library"
+description = "Distribution utilities"
 optional = false
-python-versions = ">=3.6"
+python-versions = "*"
 files = [
-    {file = "et_xmlfile-1.1.0-py3-none-any.whl", hash = "sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada"},
+    {file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"},
-    {file = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
+    {file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
 ]
 
 [[package]]
@@ -146,6 +168,36 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "filelock"
+version = "3.13.4"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "filelock-3.13.4-py3-none-any.whl", hash = "sha256:404e5e9253aa60ad457cae1be07c0f0ca90a63931200a47d9b6a6af84fd7b45f"},
+    {file = "filelock-3.13.4.tar.gz", hash = "sha256:d13f466618bfde72bd2c18255e269f72542c6e70e7bac83a0232d6b1cc5c8cf4"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+typing = ["typing-extensions (>=4.8)"]
+
+[[package]]
+name = "identify"
+version = "2.5.35"
+description = "File identification library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "identify-2.5.35-py2.py3-none-any.whl", hash = "sha256:c4de0081837b211594f8e877a6b4fad7ca32bbfc1a9307fdd61c28bfe923f13e"},
+    {file = "identify-2.5.35.tar.gz", hash = "sha256:10a7ca245cfcd756a554a7288159f72ff105ad233c7c4b9c6f0f4d108f5f6791"},
+]
+
+[package.extras]
+license = ["ukkonen"]
+
 [[package]]
 name = "idna"
 version = "3.4"
@@ -168,6 +220,20 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "nodeenv"
+version = "1.8.0"
+description = "Node.js virtual environment builder"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
+files = [
+    {file = "nodeenv-1.8.0-py2.py3-none-any.whl", hash = "sha256:df865724bb3c3adc86b3876fa209771517b0cfe596beff01a92700e0e8be4cec"},
+    {file = "nodeenv-1.8.0.tar.gz", hash = "sha256:d51e0c37e64fbf47d017feac3145cdbb58836d7eee8c6f6d3b6880c5456227d2"},
+]
+
+[package.dependencies]
+setuptools = "*"
+
 [[package]]
 name = "numpy"
 version = "1.26.0"
@@ -209,20 +275,6 @@ files = [
     {file = "numpy-1.26.0.tar.gz", hash = "sha256:f93fc78fe8bf15afe2b8d6b6499f1c73953169fad1e9a8dd086cdff3190e7fdf"},
 ]
 
-[[package]]
-name = "openpyxl"
-version = "3.1.2"
-description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "openpyxl-3.1.2-py2.py3-none-any.whl", hash = "sha256:f91456ead12ab3c6c2e9491cf33ba6d08357d802192379bb482f1033ade496f5"},
-    {file = "openpyxl-3.1.2.tar.gz", hash = "sha256:a6f5977418eff3b2d5500d54d9db50c8277a368436f4e4f8ddb1be3422870184"},
-]
-
-[package.dependencies]
-et-xmlfile = "*"
-
 [[package]]
 name = "packaging"
 version = "23.2"
@@ -302,6 +354,21 @@ sql-other = ["SQLAlchemy (>=1.4.36)"]
 test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.8.0)"]
 
+[[package]]
+name = "platformdirs"
+version = "4.2.0"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "platformdirs-4.2.0-py3-none-any.whl", hash = "sha256:0614df2a2f37e1a662acbd8e2b25b92ccf8632929bc6d43467e17fe89c75e068"},
+    {file = "platformdirs-4.2.0.tar.gz", hash = "sha256:ef0cc731df711022c174543cb70a9b5bd22e5a9337c8624ef2c2ceb8ddad8768"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
+
 [[package]]
 name = "pluggy"
 version = "1.3.0"
@@ -317,6 +384,134 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
+[[package]]
+name = "pre-commit"
+version = "3.7.0"
+description = "A framework for managing and maintaining multi-language pre-commit hooks."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "pre_commit-3.7.0-py2.py3-none-any.whl", hash = "sha256:5eae9e10c2b5ac51577c3452ec0a490455c45a0533f7960f993a0d01e59decab"},
+    {file = "pre_commit-3.7.0.tar.gz", hash = "sha256:e209d61b8acdcf742404408531f0c37d49d2c734fd7cff2d6076083d191cb060"},
+]
+
+[package.dependencies]
+cfgv = ">=2.0.0"
+identify = ">=1.0.0"
+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 = [
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 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
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+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+
 [[package]]
 name = "six"
 version = "1.16.0"
@@ -407,6 +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"
@@ -435,7 +717,27 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "virtualenv"
+version = "20.25.1"
+description = "Virtual Python Environment builder"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
+    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
+]
+
+[package.dependencies]
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<5"
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
+
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.10,<3.13"
+python-versions = ">=3.9,<3.13"
-content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"
+content-hash = "21ef9cfb35c446a375a2b74c37691d7031afb1e4f66a8b63cb7c1669470689d2"

pyproject.toml

@@ -1,8 +1,8 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.3.8"
+version = "0.3.31"
-description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
+description = "Real estate scraping library"
-authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
+authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/Bunsly/HomeHarvest"
 readme = "README.md"
 
@@ -10,14 +10,15 @@ 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"
-openpyxl = "^3.1.2"
+pydantic = "^2.7.4"
 
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.2"
+pre-commit = "^3.7.0"
 
 [build-system]
 requires = ["poetry-core"]

tests/test_realtor.py

@@ -1,22 +1,12 @@
 from homeharvest import scrape_property
-from homeharvest.exceptions import (
-    InvalidListingType,
-)
 
 
 def test_realtor_pending_or_contingent():
-    pending_or_contingent_result = scrape_property(
+    pending_or_contingent_result = scrape_property(location="Surprise, AZ", listing_type="pending")
-        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(
+    assert all([result is not None for result in [pending_or_contingent_result, regular_result]])
-        [
-            result is not None
-            for result in [pending_or_contingent_result, regular_result]
-        ]
-    )
     assert len(pending_or_contingent_result) != len(regular_result)
 
 
@@ -71,17 +61,13 @@ def test_realtor_comps():
 
 
 def test_realtor_last_x_days_sold():
-    days_result_30 = scrape_property(
+    days_result_30 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=30)
-        location="Dallas, TX", listing_type="sold", past_days=30
-    )
 
-    days_result_10 = scrape_property(
+    days_result_10 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=10)
-        location="Dallas, TX", listing_type="sold", past_days=10
-    )
 
-    assert all(
+    assert all([result is not None for result in [days_result_30, days_result_10]]) and len(days_result_30) != len(
-        [result is not None for result in [days_result_30, days_result_10]]
+        days_result_10
-    ) and len(days_result_30) != len(days_result_10)
+    )
 
 
 def test_realtor_date_range_sold():
@@ -93,9 +79,9 @@ def test_realtor_date_range_sold():
         location="Dallas, TX", listing_type="sold", date_from="2023-04-01", date_to="2023-06-10"
     )
 
-    assert all(
+    assert all([result is not None for result in [days_result_30, days_result_60]]) and len(days_result_30) < len(
-        [result is not None for result in [days_result_30, days_result_60]]
+        days_result_60
-    ) and len(days_result_30) < len(days_result_60)
+    )
 
 
 def test_realtor_single_property():
@@ -119,23 +105,83 @@ def test_realtor():
             location="2530 Al Lipscomb Way",
             listing_type="for_sale",
         ),
-        scrape_property(
+        scrape_property(location="Phoenix, AZ", listing_type="for_rent"),  #: does not support "city, state, USA" format
-            location="Phoenix, AZ", listing_type="for_rent"
+        scrape_property(location="Dallas, TX", listing_type="sold"),  #: does not support "city, state, USA" format
-        ),  #: does not support "city, state, USA" format
-        scrape_property(
-            location="Dallas, TX", listing_type="sold"
-        ),  #: does not support "city, state, USA" format
         scrape_property(location="85281"),
     ]
 
     assert all([result is not None for result in results])
 
 
+def test_realtor_city():
+    results = scrape_property(
+        location="Atlanta, GA",
+        listing_type="for_sale",
+    )
+
+    assert results is not None and len(results) > 0
+
+
 def test_realtor_bad_address():
     bad_results = scrape_property(
-            location="abceefg ju098ot498hh9",
+        location="abceefg ju098ot498hh9",
-            listing_type="for_sale",
+        listing_type="for_sale",
-        )
+    )
     if len(bad_results) == 0:
         assert True
 
+
+def test_realtor_foreclosed():
+    foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=True)
+
+    not_foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=False)
+
+    assert len(foreclosed) != len(not_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