enh: assessed/estimated value (#77)

- alt photos bug fix (#57)

.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

@@ -1,35 +1,27 @@
 <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.
-
-[![Try with Replit](https://replit.com/badge?caption=Try%20with%20Replit)](https://replit.com/@ZacharyHampton/HomeHarvestDemo)
+**HomeHarvest** is a real estate scraping library that extracts and formats data in the style of MLS listings.
 
 **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/zachary-products/15min)** *to work with us.*
-
-Check out another project we wrote: ***[JobSpy](https://github.com/cullenwatson/JobSpy)** – a Python package for job scraping*
+*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com)** *to work with us.*
 
 ## 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/JnV7eR2Ve2o) - _updated for release v0.2.7_
+[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
 
 ![homeharvest](https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/b3d5d727-e67b-4a9f-85d8-1e65fd18620a)
 
 ## Installation
 
 ```bash
-pip install homeharvest
+pip install -U homeharvest
 ```
-  _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_ 
+  _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
 
 ## Usage
 
@@ -46,9 +38,13 @@ filename = f"HomeHarvest_{current_timestamp}.csv"
 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 x days if (for_sale, for_rent)
+  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_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)}")
 
@@ -57,35 +53,6 @@ properties.to_csv(filename, index=False)
 print(properties.head())
 ```
 
-### CLI 
-
-```
-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
-```
-
-
 ## Output
 ```plaintext
 >>> properties.head()
@@ -115,11 +82,18 @@ 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_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)
+│    Format for both must be "YYYY-MM-DD".
+│    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)
 │
+├── foreclosure (True/False): If set, fetches only foreclosures
+│
 └── proxy (string): In format 'http://user:pass@host:port'
-
 ```
+
 ### Property Schema
 ```plaintext
 Property
@@ -147,41 +121,35 @@ Property
 │ └── lot_sqft
 
 ├── Property Listing Details:
+│ ├── 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
+│ ├── broker
+│ └── broker_phone
+
+├── Agent Info:
+│ ├── agent
+│ ├── broker
+│ └── broker_phone
 ```
 
 ### 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
-  
-  
-## 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.
-
----
-
+- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD

examples/HomeHarvest_Demo.ipynb

@@ -4,7 +4,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "cb48903e-5021-49fe-9688-45cd0bc05d0f",
-   "metadata": {},
+   "metadata": {
+    "is_executing": true
+   },
    "outputs": [],
    "source": [
     "from homeharvest import scrape_property\n",
@@ -84,10 +86,34 @@
    "outputs": [],
    "source": [
     "# check sold properties\n",
-    "scrape_property(\n",
+    "properties = scrape_property(\n",
     "    location=\"90210\",\n",
-    "    listing_type=\"sold\"\n",
-    ")"
+    "    listing_type=\"sold\",\n",
+    "    past_days=10\n",
+    ")\n",
+    "display(properties)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "628c1ce2",
+   "metadata": {
+    "collapsed": false,
+    "is_executing": true,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# display clickable URLs\n",
+    "from IPython.display import display, HTML\n",
+    "properties['property_url'] = '<a href=\"' + properties['property_url'] + '\" target=\"_blank\">' + properties['property_url'] + '</a>'\n",
+    "\n",
+    "html = properties.to_html(escape=False)\n",
+    "truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
+    "display(HTML(truncate_width))"
    ]
   }
  ],

homeharvest/__init__.py

@@ -1,10 +1,9 @@
 import warnings
 import pandas as pd
 from .core.scrapers import ScraperInput
-from .utils import process_result, ordered_properties, validate_input
+from .utils import process_result, ordered_properties, validate_input, validate_dates
 from .core.scrapers.realtor import RealtorScraper
 from .core.scrapers.models import ListingType
-from .exceptions import InvalidListingType, NoResultsFound
 
 
 def scrape_property(
@@ -14,6 +13,9 @@ def scrape_property(
     mls_only: bool = False,
     past_days: int = None,
     proxy: str = None,
+    date_from: str = None,
+    date_to: str = None,
+    foreclosure: bool = None,
 ) -> pd.DataFrame:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
@@ -22,9 +24,11 @@ def scrape_property(
     :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 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
     """
     validate_input(listing_type)
+    validate_dates(date_from, date_to)
 
     scraper_input = ScraperInput(
         location=location,
@@ -33,6 +37,9 @@ def scrape_property(
         radius=radius,
         mls_only=mls_only,
         last_x_days=past_days,
+        date_from=date_from,
+        date_to=date_to,
+        foreclosure=foreclosure,
     )
 
     site = RealtorScraper(scraper_input)
@@ -40,7 +47,7 @@ def scrape_property(
 
     properties_dfs = [process_result(result) for result in results]
     if not properties_dfs:
-        raise NoResultsFound("no results found for the query")
+        return pd.DataFrame()
 
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", category=FutureWarning)

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(
-        "location", type=str, help="Location to scrape (e.g., San Francisco, CA)"
-    )
+    parser.add_argument("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(
-        "-p", "--proxy", type=str, default=None, help="Proxy to use for scraping"
-    )
+    parser.add_argument("-p", "--proxy", type=str, default=None, help="Proxy to use for scraping")
     parser.add_argument(
         "-d",
         "--days",

homeharvest/core/scrapers/__init__.py

@@ -1,5 +1,8 @@
 from dataclasses import dataclass
 import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util.retry import Retry
+import uuid
 from .models import Property, ListingType, SiteName
 
 
@@ -11,21 +14,36 @@ class ScraperInput:
     mls_only: bool | None = None
     proxy: str | None = None
     last_x_days: int | None = None
+    date_from: str | None = None
+    date_to: str | None = None
+    foreclosure: bool | None = None
 
 
 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:
-            self.session = requests.Session()
-        else:
-            self.session = session
+        if not self.session:
+            Scraper.session = requests.Session()
+            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",
+                }
+            )
 
         if scraper_input.proxy:
             proxy_url = scraper_input.proxy
@@ -36,13 +54,34 @@ class Scraper:
         self.radius = scraper_input.radius
         self.last_x_days = scraper_input.last_x_days
         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
 
-    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): ...
+
+    def get_access_token(self):
+        url = "https://graph.realtor.com/auth/token"
+
+        payload = f'{{"client_app_id":"rdc_mobile_native,24.20.4.149916,iphone","device_id":"{str(uuid.uuid4()).upper()}","grant_type":"device_mobile"}}'
+        headers = {
+            "Host": "graph.realtor.com",
+            "x-client-version": "24.20.4.149916",
+            "accept": "*/*",
+            "content-type": "Application/json",
+            "user-agent": "Realtor.com/24.20.4.149916 CFNetwork/1410.0.3 Darwin/22.6.0",
+            "accept-language": "en-US,en;q=0.9",
+        }
+        response = requests.post(url, headers=headers, data=payload)
+
+        data = response.json()
+        try:
+            access_token = data["access_token"]
+        except Exception:
+            raise Exception("Could not get access token, use a proxy/vpn or wait")
+        return access_token

homeharvest/core/scrapers/models.py

@@ -23,6 +23,33 @@ 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"
+    CONDO_TOWNHOME = "CONDO_TOWNHOME"
+    CONDO_TOWNHOME_ROWHOME_COOP = "CONDO_TOWNHOME_ROWHOME_COOP"
+    CONDO = "CONDO"
+    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:
     street: str | None = None
@@ -34,7 +61,9 @@ 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 +73,13 @@ class Description:
     year_built: int | None = None
     garage: float | None = None
     stories: int | None = None
+    text: str | None = None
+
+
+@dataclass
+class Agent:
+    name: str | None = None
+    phone: str | None = None
 
 
 @dataclass
@@ -56,11 +92,19 @@ 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
+    days_on_mls: int | None = None
     description: Description | None = None
 
     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
+    nearby_schools: list[str] = None
+    assessed_value: int | None = None
+    estimated_value: int | None = None

homeharvest/core/scrapers/realtor/__init__.py

@@ -4,18 +4,21 @@ homeharvest.realtor.__init__
 
 This module implements the scraper for realtor.com
 """
-from typing import Dict, Union, Optional
+
 from concurrent.futures import ThreadPoolExecutor, as_completed
+from datetime import datetime
+from typing import Dict, Union, Optional
 
 from .. import Scraper
-from ....exceptions import NoResultsFound
-from ..models import Property, Address, ListingType, Description
+from ..models import Property, Address, ListingType, Description, PropertyType, Agent
 
 
 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)
@@ -37,7 +40,7 @@ class RealtorScraper(Scraper):
         result = response_json["autocomplete"]
 
         if not result:
-            raise NoResultsFound("No results found for location: " + self.location)
+            return None
 
         return result[0]
 
@@ -49,6 +52,7 @@ class RealtorScraper(Scraper):
                             listing_id
                         }
                         address {
+                            street_direction
                             street_number
                             street_name
                             street_suffix
@@ -83,6 +87,11 @@ class RealtorScraper(Scraper):
                             garage
                             permalink
                         }
+                        media {
+                            photos {
+                                href
+                            }
+                        }
                     }
                 }"""
 
@@ -109,34 +118,54 @@ class RealtorScraper(Scraper):
             and property_info["address"].get("location")
             and property_info["address"]["location"].get("coordinate")
         )
+        list_date_str = (
+            property_info["basic"]["list_date"].split("T")[0] if property_info["basic"].get("list_date") else None
+        )
+        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
+        status = property_info["basic"]["status"].lower()
+        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"):
+                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)
         listing = Property(
             mls=mls,
-            mls_id=property_info["source"].get("listing_id")
-            if "source" in property_info and isinstance(property_info["source"], dict)
-            else None,
-            property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
+            mls_id=(
+                property_info["source"].get("listing_id")
+                if "source" in property_info and isinstance(property_info["source"], dict)
+                else None
+            ),
+            property_url=f"{self.PROPERTY_URL}{property_id}",
             status=property_info["basic"]["status"].upper(),
             list_price=property_info["basic"]["price"],
-            list_date=property_info["basic"]["list_date"].split("T")[0]
-            if property_info["basic"].get("list_date")
-            else None,
-            prc_sqft=property_info["basic"].get("price")
-            / property_info["basic"].get("sqft")
-            if property_info["basic"].get("price")
-            and property_info["basic"].get("sqft")
-            else None,
-            last_sold_date=property_info["basic"]["sold_date"].split("T")[0]
-            if property_info["basic"].get("sold_date")
-            else None,
-            latitude=property_info["address"]["location"]["coordinate"].get("lat")
-            if able_to_get_lat_long
-            else None,
-            longitude=property_info["address"]["location"]["coordinate"].get("lon")
-            if able_to_get_lat_long
-            else None,
+            list_date=list_date,
+            prc_sqft=(
+                property_info["basic"].get("price") / property_info["basic"].get("sqft")
+                if property_info["basic"].get("price") and property_info["basic"].get("sqft")
+                else None
+            ),
+            last_sold_date=last_sold_date,
+            pending_date=pending_date,
+            latitude=property_info["address"]["location"]["coordinate"].get("lat") 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(
+                alt_photos=self.process_alt_photos(property_info.get("media", {}).get("photos", [])),
                 style=property_info["basic"].get("type", "").upper(),
                 beds=property_info["basic"].get("beds"),
                 baths_full=property_info["basic"].get("baths_full"),
@@ -147,7 +176,13 @@ 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"),
+            nearby_schools=prop_details.get("schools"),
+            assessed_value=prop_details.get("assessed_value"),
+            estimated_value=prop_details.get("estimated_value"),
         )
 
         return [listing]
@@ -200,6 +235,7 @@ class RealtorScraper(Scraper):
                             stories
                         }
                         address {
+                            street_direction
                             street_number
                             street_name
                             street_suffix
@@ -230,10 +266,17 @@ 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,
@@ -249,16 +292,16 @@ class RealtorScraper(Scraper):
             Property(
                 mls_id=property_id,
                 property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
-                address=self._parse_address(
-                    property_info, search_type="handle_address"
-                ),
+                address=self._parse_address(property_info, search_type="handle_address"),
                 description=self._parse_description(property_info),
+                agents=prop_details.get("agents"),
+                nearby_schools=prop_details.get("schools"),
+                assessed_value=prop_details.get("assessed_value"),
+                estimated_value=prop_details.get("estimated_value"),
             )
         ]
 
-    def general_search(
-        self, variables: dict, search_type: str
-    ) -> Dict[str, Union[int, list[Property]]]:
+    def general_search(self, variables: dict, search_type: str) -> Dict[str, Union[int, list[Property]]]:
         """
         Handles a location area & returns a list of properties
         """
@@ -266,6 +309,7 @@ class RealtorScraper(Scraper):
                             count
                             total
                             results {
+                                pending_date
                                 property_id
                                 list_date
                                 status
@@ -278,6 +322,7 @@ class RealtorScraper(Scraper):
                                     is_pending
                                 }
                                 description {
+                                    type
                                     sqft
                                     beds
                                     baths_full
@@ -290,6 +335,7 @@ class RealtorScraper(Scraper):
                                     type
                                     name
                                     stories
+                                    text
                                 }
                                 source {
                                     id
@@ -300,6 +346,7 @@ class RealtorScraper(Scraper):
                                 }
                                 location {
                                     address {
+                                        street_direction
                                         street_number
                                         street_name
                                         street_suffix
@@ -312,23 +359,38 @@ class RealtorScraper(Scraper):
                                             lat
                                         }
                                     }
+                                    county {
+                                        name
+                                        fips_code
+                                    }
                                     neighborhoods {
                                         name
                                     }
                                 }
+                                tax_record {
+                                    public_record_id
+                                }
+                                primary_photo {
+                                    href
+                                }
+                                photos {
+                                    href
+                                }
                             }
                         }
                     }"""
 
-        date_param = (
-            'sold_date: { min: "$today-%sD" }' % self.last_x_days
-            if self.listing_type == ListingType.SOLD and self.last_x_days
-            else (
-                'list_date: { min: "$today-%sD" }' % self.last_x_days
-                if self.last_x_days
-                else ""
-            )
-        )
+        date_param = ""
+        if self.listing_type == ListingType.SOLD:
+            if self.date_from and self.date_to:
+                date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
+            elif self.last_x_days:
+                date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
+        else:
+            if self.date_from and self.date_to:
+                date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
+            elif self.last_x_days:
+                date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
 
         sort_param = (
             "sort: [{ field: sold_date, direction: desc }]"
@@ -337,12 +399,16 @@ class RealtorScraper(Scraper):
         )
 
         pending_or_contingent_param = (
-            "or_filters: { contingent: true, pending: true }"
-            if self.listing_type == ListingType.PENDING
-            else ""
+            "or_filters: { contingent: true, pending: true }" 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(
@@ -351,10 +417,11 @@ class RealtorScraper(Scraper):
                     $offset: Int!,
                     ) {
                         home_search(
-                            query: { 
+                            query: {
+                                %s
                                 nearby: {
                                     coordinates: $coordinates
-                                    radius: $radius 
+                                    radius: $radius
                                 }
                                 status: %s
                                 %s
@@ -364,6 +431,7 @@ class RealtorScraper(Scraper):
                             limit: 200
                             offset: $offset
                     ) %s""" % (
+                is_foreclosure,
                 listing_type.value.lower(),
                 date_param,
                 pending_or_contingent_param,
@@ -380,6 +448,7 @@ class RealtorScraper(Scraper):
                             ) {
                                 home_search(
                                     query: {
+                                        %s
                                         city: $city
                                         county: $county
                                         postal_code: $postal_code
@@ -392,6 +461,7 @@ class RealtorScraper(Scraper):
                                     limit: 200
                                     offset: $offset
                                 ) %s""" % (
+                is_foreclosure,
                 listing_type.value.lower(),
                 date_param,
                 pending_or_contingent_param,
@@ -420,7 +490,6 @@ 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"
 
@@ -436,15 +505,11 @@ class RealtorScraper(Scraper):
         ):
             return {"total": 0, "properties": []}
 
-        for result in response_json["data"][search_key]["results"]:
-            mls = (
-                result["source"].get("id")
-                if "source" in result and isinstance(result["source"], dict)
-                else None
-            )
+        def process_property(result: dict) -> Property | None:
+            mls = 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
@@ -455,33 +520,54 @@ 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:
+                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")
-                if "source" in result and isinstance(result["source"], dict)
-                else None,
-                property_url=f"{self.PROPERTY_URL}{result['property_id']}",
+                mls_id=(
+                    result["source"].get("listing_id")
+                    if "source" in result and isinstance(result["source"], dict)
+                    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]
-                if result.get("list_date")
-                else None,
+                list_date=result["list_date"].split("T")[0] 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"]
-                if result.get("hoa") and isinstance(result["hoa"], dict)
-                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,
+                hoa_fee=result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) 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"),
-                #: neighborhoods=self._parse_neighborhoods(result),
                 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=prop_details.get("agents"),
+                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"],
@@ -490,6 +576,9 @@ class RealtorScraper(Scraper):
 
     def search(self):
         location_info = self.handle_location()
+        if not location_info:
+            return []
+
         location_type = location_info["area_type"]
 
         search_variables = {
@@ -499,18 +588,14 @@ class RealtorScraper(Scraper):
         search_type = (
             "comps"
             if self.radius and location_type == "address"
-            else "address"
-            if location_type == "address" and not self.radius
-            else "area"
+            else "address" 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(
-                    search_variables, search_type=search_type
-                )
+                gql_results = self.general_search(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:
@@ -521,12 +606,20 @@ 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"),
@@ -535,6 +628,9 @@ 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"]
@@ -554,6 +650,34 @@ class RealtorScraper(Scraper):
 
         return homes
 
+    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  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 }} }}    }}\\n}}\\n","variables":{{"property_id":"{property_id}"}}}}'
+        response = self.session.post(self.PROPERTY_GQL, data=payload)
+
+        def get_key(keys: list):
+            try:
+                data = response.json()
+                for key in keys:
+                    data = data[key]
+                return data
+            except (KeyError, TypeError):
+                return {}
+
+        ads = get_key(["data", "home", "consumerAdvertisers"])
+        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"], phone=ad["phone"]) for ad in ads]
+
+        schools = [school["district"]["name"] for school in schools]
+        return {
+            "agents": agents if agents 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 = []
@@ -568,21 +692,31 @@ class RealtorScraper(Scraper):
         return ", ".join(neighborhoods_list) if neighborhoods_list else None
 
     @staticmethod
-    def _parse_address(result: dict, search_type):
+    def handle_none_safely(address_part):
+        if address_part is None:
+            return ""
+
+        return address_part
+
+    def _parse_address(self, result: dict, search_type):
         if search_type == "general_search":
-            return Address(
-                street=f"{result['location']['address']['street_number']} {result['location']['address']['street_name']} {result['location']['address']['street_suffix']}",
-                unit=result["location"]["address"]["unit"],
-                city=result["location"]["address"]["city"],
-                state=result["location"]["address"]["state_code"],
-                zip=result["location"]["address"]["postal_code"],
-            )
+            address = result["location"]["address"]
+        else:
+            address = result["address"]
+
         return Address(
-            street=f"{result['address']['street_number']} {result['address']['street_name']} {result['address']['street_suffix']}",
-            unit=result["address"]["unit"],
-            city=result["address"]["city"],
-            state=result["address"]["state_code"],
-            zip=result["address"]["postal_code"],
+            street=" ".join(
+                [
+                    self.handle_none_safely(address.get("street_number")),
+                    self.handle_none_safely(address.get("street_direction")),
+                    self.handle_none_safely(address.get("street_name")),
+                    self.handle_none_safely(address.get("street_suffix")),
+                ]
+            ).strip(),
+            unit=address["unit"],
+            city=address["city"],
+            state=address["state_code"],
+            zip=address["postal_code"],
         )
 
     @staticmethod
@@ -590,15 +724,23 @@ class RealtorScraper(Scraper):
         description_data = result.get("description", {})
 
         if description_data is None or not isinstance(description_data, dict):
-            print("Warning: description_data is invalid!")
             description_data = {}
 
         style = description_data.get("type", "")
         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(style) if style else None,
             beds=description_data.get("beds"),
             baths_full=description_data.get("baths_full"),
             baths_half=description_data.get("baths_half"),
@@ -608,4 +750,37 @@ class RealtorScraper(Scraper):
             year_built=description_data.get("year_built"),
             garage=description_data.get("garage"),
             stories=description_data.get("stories"),
+            text=description_data.get("text"),
         )
+
+    @staticmethod
+    def calculate_days_on_mls(result: dict) -> Optional[int]:
+        list_date_str = result.get("list_date")
+        list_date = datetime.strptime(list_date_str.split("T")[0], "%Y-%m-%d") if list_date_str else None
+        last_sold_date_str = result.get("last_sold_date")
+        last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d") if last_sold_date_str else None
+        today = datetime.now()
+
+        if list_date:
+            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"):
+                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

@@ -2,5 +2,5 @@ class InvalidListingType(Exception):
     """Raised when a provided listing type is does not exist."""
 
 
-class NoResultsFound(Exception):
-    """Raised when no results are found for the given location"""
+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"""

homeharvest/utils.py

@@ -1,12 +1,14 @@
-from .core.scrapers.models import Property, ListingType
 import pandas as pd
-from .exceptions import InvalidListingType
+from datetime import datetime
+from .core.scrapers.models import Property, ListingType
+from .exceptions import InvalidListingType, InvalidDate
 
 ordered_properties = [
     "property_url",
     "mls",
     "mls_id",
     "status",
+    "text",
     "style",
     "street",
     "unit",
@@ -18,17 +20,29 @@ ordered_properties = [
     "half_baths",
     "sqft",
     "year_built",
+    "days_on_mls",
     "list_price",
     "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",
+    "broker",
+    "broker_phone",
+    "nearby_schools",
+    "primary_photo",
+    "alt_photos",
 ]
 
 
@@ -44,10 +58,22 @@ def process_result(result: Property) -> pd.DataFrame:
         prop_data["state"] = address_data.state
         prop_data["zip_code"] = address_data.zip
 
+    if "agents" in prop_data:
+        agents = prop_data["agents"]
+        if agents:
+            prop_data["agent"] = agents[0].name
+            if len(agents) > 1:
+                prop_data["broker"] = agents[1].name
+                prop_data["broker_phone"] = agents[1].phone
+
     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
+    prop_data["primary_photo"] = description.primary_photo
+    prop_data["alt_photos"] = ", ".join(description.alt_photos)
+    prop_data["style"] = description.style if type(description.style) == str else description.style.value
     prop_data["beds"] = description.beds
     prop_data["full_baths"] = description.baths_full
     prop_data["half_baths"] = description.baths_half
@@ -57,6 +83,7 @@ def process_result(result: Property) -> pd.DataFrame:
     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)
@@ -66,6 +93,19 @@ def process_result(result: Property) -> pd.DataFrame:
 
 def validate_input(listing_type: str) -> None:
     if listing_type.upper() not in ListingType.__members__:
-        raise InvalidListingType(
-            f"Provided listing type, '{listing_type}', does not exist."
-        )
+        raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
+
+
+def validate_dates(date_from: str | None, date_to: str | None) -> None:
+    if (date_from is not None and date_to is None) or (date_from is None and date_to is not None):
+        raise InvalidDate("Both date_from and date_to must be provided.")
+
+    if date_from and date_to:
+        try:
+            date_from_obj = datetime.strptime(date_from, "%Y-%m-%d")
+            date_to_obj = datetime.strptime(date_to, "%Y-%m-%d")
+
+            if date_to_obj < date_from_obj:
+                raise InvalidDate("date_to must be after date_from.")
+        except ValueError as e:
+            raise InvalidDate(f"Invalid date format or range")

poetry.lock

@@ -1,4 +1,4 @@
-# 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 = "certifi"
@@ -11,6 +11,17 @@ 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 +133,14 @@ files = [
 ]
 
 [[package]]
-name = "et-xmlfile"
-version = "1.1.0"
-description = "An implementation of lxml.xmlfile for the standard library"
+name = "distlib"
+version = "0.3.8"
+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 = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
+    {file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"},
+    {file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
 ]
 
 [[package]]
@@ -146,6 +157,36 @@ 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 +209,20 @@ 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 +264,6 @@ 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 +343,21 @@ 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 +373,24 @@ 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 = "pytest"
 version = "7.4.2"
@@ -364,6 +438,66 @@ files = [
     {file = "pytz-2023.3.post1.tar.gz", hash = "sha256:7b4fddbeb94a1eba4b557da24f19fdf9db575192544270a9101d8509f9f43d7b"},
 ]
 
+[[package]]
+name = "pyyaml"
+version = "6.0.1"
+description = "YAML parser and emitter for Python"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "PyYAML-6.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d858aa552c999bc8a8d57426ed01e40bef403cd8ccdd0fc5f6f04a00414cac2a"},
+    {file = "PyYAML-6.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fd66fc5d0da6d9815ba2cebeb4205f95818ff4b79c3ebe268e75d961704af52f"},
+    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938"},
+    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d"},
+    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba336e390cd8e4d1739f42dfe9bb83a3cc2e80f567d8805e11b46f4a943f5515"},
+    {file = "PyYAML-6.0.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:326c013efe8048858a6d312ddd31d56e468118ad4cdeda36c719bf5bb6192290"},
+    {file = "PyYAML-6.0.1-cp310-cp310-win32.whl", hash = "sha256:bd4af7373a854424dabd882decdc5579653d7868b8fb26dc7d0e99f823aa5924"},
+    {file = "PyYAML-6.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d"},
+    {file = "PyYAML-6.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6965a7bc3cf88e5a1c3bd2e0b5c22f8d677dc88a455344035f03399034eb3007"},
+    {file = "PyYAML-6.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f003ed9ad21d6a4713f0a9b5a7a0a79e08dd0f221aff4525a2be4c346ee60aab"},
+    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42f8152b8dbc4fe7d96729ec2b99c7097d656dc1213a3229ca5383f973a5ed6d"},
+    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:062582fca9fabdd2c8b54a3ef1c978d786e0f6b3a1510e0ac93ef59e0ddae2bc"},
+    {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2b04aac4d386b172d5b9692e2d2da8de7bfb6c387fa4f801fbf6fb2e6ba4673"},
+    {file = "PyYAML-6.0.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b"},
+    {file = "PyYAML-6.0.1-cp311-cp311-win32.whl", hash = "sha256:1635fd110e8d85d55237ab316b5b011de701ea0f29d07611174a1b42f1444741"},
+    {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
+    {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
+    {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
+    {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08c6f0fe150303c1c6b71ebcd7213c2858041a7e01975da3a99aed1e7a378ef"},
+    {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
+    {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
+    {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
+    {file = "PyYAML-6.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:0d3304d8c0adc42be59c5f8a4d9e3d7379e6955ad754aa9d6ab7a398b59dd1df"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50550eb667afee136e9a77d6dc71ae76a44df8b3e51e41b77f6de2932bfe0f47"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:afd7e57eddb1a54f0f1a974bc4391af8bcce0b444685d936840f125cf046d5bd"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-win32.whl", hash = "sha256:fca0e3a251908a499833aa292323f32437106001d436eca0e6e7833256674585"},
+    {file = "PyYAML-6.0.1-cp36-cp36m-win_amd64.whl", hash = "sha256:f22ac1c3cac4dbc50079e965eba2c1058622631e526bd9afd45fedd49ba781fa"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:b1275ad35a5d18c62a7220633c913e1b42d44b46ee12554e5fd39c70a243d6a3"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:18aeb1bf9a78867dc38b259769503436b7c72f7a1f1f4c93ff9a17de54319b27"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:596106435fa6ad000c2991a98fa58eeb8656ef2325d7e158344fb33864ed87e3"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baa90d3f661d43131ca170712d903e6295d1f7a0f595074f151c0aed377c9b9c"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-win32.whl", hash = "sha256:9046c58c4395dff28dd494285c82ba00b546adfc7ef001486fbf0324bc174fba"},
+    {file = "PyYAML-6.0.1-cp37-cp37m-win_amd64.whl", hash = "sha256:4fb147e7a67ef577a588a0e2c17b6db51dda102c71de36f8549b6816a96e1867"},
+    {file = "PyYAML-6.0.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1d4c7e777c441b20e32f52bd377e0c409713e8bb1386e1099c2415f26e479595"},
+    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0cd17c15d3bb3fa06978b4e8958dcdc6e0174ccea823003a106c7d4d7899ac5"},
+    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696"},
+    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"},
+    {file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"},
+    {file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
+    {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
+    {file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
+    {file = "PyYAML-6.0.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c8098ddcc2a85b61647b2590f825f3db38891662cfc2fc776415143f599bb859"},
+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
+    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
+]
+
 [[package]]
 name = "requests"
 version = "2.31.0"
@@ -385,6 +519,22 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "setuptools"
+version = "69.5.1"
+description = "Easily download, build, install, upgrade, and uninstall Python packages"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
+    {file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
+]
+
+[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"
@@ -435,7 +585,27 @@ 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"
-content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"
+content-hash = "371781da268d5f61d6e798c023777f337b620e9b07a48c316825d7b998b63f02"

pyproject.toml

@@ -1,9 +1,9 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.3.4"
-description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
-authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
-homepage = "https://github.com/ZacharyHampton/HomeHarvest"
+version = "0.3.20"
+description = "Real estate scraping library"
+authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
+homepage = "https://github.com/Bunsly/HomeHarvest"
 readme = "README.md"
 
 [tool.poetry.scripts]
@@ -13,11 +13,11 @@ homeharvest = "homeharvest.cli:main"
 python = ">=3.10,<3.13"
 requests = "^2.31.0"
 pandas = "^2.1.1"
-openpyxl = "^3.1.2"
 
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.2"
+pre-commit = "^3.7.0"
 
 [build-system]
 requires = ["poetry-core"]

tests/test_realtor.py

@@ -1,27 +1,12 @@
 from homeharvest import scrape_property
-from homeharvest.exceptions import (
-    InvalidListingType,
-    NoResultsFound,
-)
 
 
 def test_realtor_pending_or_contingent():
-    pending_or_contingent_result = scrape_property(
-        location="Surprise, AZ",
-        listing_type="pending"
-    )
+    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")
 
-    assert all(
-        [
-            result is not None
-            for result in [pending_or_contingent_result, regular_result]
-        ]
-    )
+    assert all([result is not None for result in [pending_or_contingent_result, regular_result]])
     assert len(pending_or_contingent_result) != len(regular_result)
 
 
@@ -54,6 +39,16 @@ def test_realtor_pending_comps():
     assert len(set([len(result) for result in results])) == len(results)
 
 
+def test_realtor_sold_past():
+    result = scrape_property(
+        location="San Diego, CA",
+        past_days=30,
+        listing_type="sold",
+    )
+
+    assert result is not None and len(result) > 0
+
+
 def test_realtor_comps():
     result = scrape_property(
         location="2530 Al Lipscomb Way",
@@ -66,17 +61,27 @@ def test_realtor_comps():
 
 
 def test_realtor_last_x_days_sold():
+    days_result_30 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=30)
+
+    days_result_10 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=10)
+
+    assert all([result is not None for result in [days_result_30, days_result_10]]) and len(days_result_30) != len(
+        days_result_10
+    )
+
+
+def test_realtor_date_range_sold():
     days_result_30 = scrape_property(
-        location="Dallas, TX", listing_type="sold", past_days=30
+        location="Dallas, TX", listing_type="sold", date_from="2023-05-01", date_to="2023-05-28"
     )
 
-    days_result_10 = scrape_property(
-        location="Dallas, TX", listing_type="sold", past_days=10
+    days_result_60 = scrape_property(
+        location="Dallas, TX", listing_type="sold", date_from="2023-04-01", date_to="2023-06-10"
     )
 
-    assert all(
-        [result is not None for result in [days_result_30, days_result_10]]
-    ) and len(days_result_30) != len(days_result_10)
+    assert all([result is not None for result in [days_result_30, days_result_60]]) and len(days_result_30) < len(
+        days_result_60
+    )
 
 
 def test_realtor_single_property():
@@ -100,26 +105,40 @@ def test_realtor():
             location="2530 Al Lipscomb Way",
             listing_type="for_sale",
         ),
-        scrape_property(
-            location="Phoenix, AZ", listing_type="for_rent"
-        ),  #: 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="Phoenix, AZ", listing_type="for_rent"),  #: 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])
 
-    bad_results = []
-    try:
-        bad_results += [
-            scrape_property(
-                location="abceefg ju098ot498hh9",
-                listing_type="for_sale",
-            )
-        ]
-    except (InvalidListingType, NoResultsFound):
+
+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",
+        listing_type="for_sale",
+    )
+    if len(bad_results) == 0:
         assert True
 
-    assert all([result is None for result in bad_results])
+
+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