Add foreclosure parameter (#55 )

Merge pull request #48 from Bunsly/for_rent_url
fix: rent url
2026-03-05 12:04:31 -08:00 · 2024-03-03 11:45:28 -06:00 · 2024-01-09 13:12:30 -07:00 · 2024-01-08 12:46:31 -06:00 · 2023-12-02 00:40:13 -06:00 · 2023-12-02 00:39:28 -06:00
13 changed files with 531 additions and 321 deletions
--- a/README.md
+++ b/README.md
@@ -1,15 +1,10 @@
 <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/zachary-products/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/cullenwatson/JobSpy)** – a Python package for job scraping*
 ## HomeHarvest Features
@@ -17,10 +12,9 @@ Check out another project we wrote: ***[JobSpy](https://github.com/cullenwatson/
 - **Data Format**: Structures data to resemble MLS listings.
 - **Export Flexibility**: Options to save as either CSV or Excel.
 - **Usage Modes**:
  - **CLI**: For users who prefer command-line operations.
  - **Python**: For those who'd like to integrate scraping into their Python scripts.
-[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)
@@ -33,34 +27,6 @@ pip install homeharvest
 ## Usage
 ### CLI 
 ```
 usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] location
 Home Harvest Property Scraper                                                                                                 
 positional arguments:                                                                                                         
  location              Location to scrape (e.g., San Francisco, CA)                                                          
 options:                                                                                                                      
  -l {for_sale,for_rent,sold}, --listing_type {for_sale,for_rent,sold}                                                        
                        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 _ (eg. 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
 ```
 ### Python
 ```py
@@ -69,13 +35,18 @@ from datetime import datetime
 # Generate filename based on current timestamp
 current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-filename = f"output/{current_timestamp}.csv"
+filename = f"HomeHarvest_{current_timestamp}.csv"
 properties = scrape_property(
  location="San Diego, CA",
-  listing_type="sold",  # or (for_sale, for_rent)
+  listing_type="sold",  # or (for_sale, for_rent, pending)
-  property_younger_than=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)
-  mls_only=True,  # only fetch MLS listings
+  
  # date_from="2023-05-01", # alternative to past_days 
  # date_to="2023-05-28", 
  # foreclosure=True
  # mls_only=True,  # only fetch MLS listings
 )
 print(f"Number of properties: {len(properties)}")
@@ -104,19 +75,27 @@ Required
    - 'for_rent'
    - 'for_sale'
    - 'sold'
    - 'pending'
 Optional
 ├── radius (decimal): Radius in miles to find comparable properties based on individual addresses.
 │    Example: 5.5 (fetches properties within a 5.5-mile radius if location is set to a specific address; otherwise, ignored)
 │
-├── property_younger_than (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).
+├── 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
@@ -144,6 +123,7 @@ Property
 │ └── lot_sqft
 ├── Property Listing Details:
 │ ├── days_on_mls
 │ ├── list_price
 │ ├── list_date
 │ ├── sold_price
@@ -163,22 +143,5 @@ Property
 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
-  
+  
 ## 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.
 ---
--- a/examples/HomeHarvest_Demo.ipynb
+++ b/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))"
   ]
  }
 ],
--- a/examples/HomeHarvest_Demo.py
+++ b/examples/HomeHarvest_Demo.py
@@ -3,16 +3,18 @@ from datetime import datetime
 # Generate filename based on current timestamp
 current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-filename = f"output/{current_timestamp}.csv"
+filename = f"HomeHarvest_{current_timestamp}.csv"
 properties = scrape_property(
    location="San Diego, CA",
-    listing_type="sold", # for_sale, for_rent
+    listing_type="sold",  # or (for_sale, for_rent)
-    property_younger_than=30, # sold/listed in last 30 days
+    past_days=30,  # sold in last 30 days - listed in last x days if (for_sale, for_rent)
-    mls_only=True, # only fetch MLS listings
+    # pending_or_contingent=True # use on for_sale listings to find pending / contingent listings
    # 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)}")
 # Export to csv
 properties.to_csv(filename, index=False)
-print(properties.head())
+print(properties.head())
--- a/homeharvest/init.py
+++ b/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(
@@ -12,9 +11,11 @@ def scrape_property(
    listing_type: str = "for_sale",
    radius: float = None,
    mls_only: bool = False,
-    property_younger_than: int = None,
+    past_days: int = None,
    pending_or_contingent: bool = False,
    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.
@@ -22,11 +23,12 @@ def scrape_property(
    :param listing_type: Listing Type (for_sale, for_rent, sold)
    :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 property_younger_than: Get properties sold/listed in last _ days.
+    :param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
-    :param pending_or_contingent: If set, fetches only pending or contingent listings. Only applicable for for_sale listings from general area searches.
+    :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,
@@ -34,8 +36,10 @@ def scrape_property(
        proxy=proxy,
        radius=radius,
        mls_only=mls_only,
-        last_x_days=property_younger_than,
+        last_x_days=past_days,
-        pending_or_contingent=pending_or_contingent,
+        date_from=date_from,
        date_to=date_to,
        foreclosure=foreclosure,
    )
    site = RealtorScraper(scraper_input)
@@ -43,7 +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)
--- a/homeharvest/cli.py
+++ b/homeharvest/cli.py
@@ -14,7 +14,7 @@ def main():
        "--listing_type",
        type=str,
        default="for_sale",
-        choices=["for_sale", "for_rent", "sold"],
+        choices=["for_sale", "for_rent", "sold", "pending"],
        help="Listing type to scrape",
    )
@@ -68,7 +68,7 @@ def main():
        radius=args.radius,
        proxy=args.proxy,
        mls_only=args.mls_only,
-        property_younger_than=args.days,
+        past_days=args.days,
    )
    if not args.filename:
--- a/homeharvest/core/scrapers/init.py
+++ b/homeharvest/core/scrapers/init.py
@@ -1,6 +1,5 @@
 from dataclasses import dataclass
 import requests
 import tls_client
 from .models import Property, ListingType, SiteName
@@ -12,14 +11,16 @@ class ScraperInput:
    mls_only: bool | None = None
    proxy: str | None = None
    last_x_days: int | None = None
-    pending_or_contingent: bool | None = None
+    date_from: str | None = None
    date_to: str | None = None
    foreclosure: bool | None = None
 class Scraper:
    def __init__(
        self,
        scraper_input: ScraperInput,
-        session: requests.Session | tls_client.Session = None,
+        session: requests.Session = None,
    ):
        self.location = scraper_input.location
        self.listing_type = scraper_input.listing_type
@@ -38,7 +39,9 @@ class Scraper:
        self.radius = scraper_input.radius
        self.last_x_days = scraper_input.last_x_days
        self.mls_only = scraper_input.mls_only
-        self.pending_or_contingent = scraper_input.pending_or_contingent
+        self.date_from = scraper_input.date_from
        self.date_to = scraper_input.date_to
        self.foreclosure = scraper_input.foreclosure
    def search(self) -> list[Property]:
        ...
--- a/homeharvest/core/scrapers/models.py
+++ b/homeharvest/core/scrapers/models.py
@@ -19,6 +19,7 @@ class SiteName(Enum):
 class ListingType(Enum):
    FOR_SALE = "FOR_SALE"
    FOR_RENT = "FOR_RENT"
    PENDING = "PENDING"
    SOLD = "SOLD"
@@ -33,6 +34,8 @@ class Address:
@dataclass
 class Description:
    primary_photo: str | None = None
    alt_photos: list[str] | None = None
    style: str | None = None
    beds: int | None = None
    baths_full: int | None = None
@@ -58,6 +61,7 @@ class Property:
    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
--- a/homeharvest/core/scrapers/realtor/init.py
+++ b/homeharvest/core/scrapers/realtor/init.py
@@ -4,11 +4,11 @@ homeharvest.realtor.__init__
 This module implements the scraper for realtor.com
 """
 from datetime import datetime
 from typing import Dict, Union, Optional
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from .. import Scraper
 from ....exceptions import NoResultsFound
 from ..models import Property, Address, ListingType, Description
@@ -18,7 +18,6 @@ class RealtorScraper(Scraper):
    ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
    def __init__(self, scraper_input):
        self.counter = 1
        super().__init__(scraper_input)
    def handle_location(self):
@@ -38,7 +37,7 @@ class RealtorScraper(Scraper):
        result = response_json["autocomplete"]
        if not result:
-            raise NoResultsFound("No results found for location: " + self.location)
+            return None
        return result[0]
@@ -50,6 +49,7 @@ class RealtorScraper(Scraper):
                            listing_id
                        }
                        address {
                            street_direction
                            street_number
                            street_name
                            street_suffix
@@ -84,6 +84,12 @@ class RealtorScraper(Scraper):
                            garage
                            permalink
                        }
                        primary_photo {
                            href
                        }
                        photos {
                            href
                        }
                    }
                }"""
@@ -110,6 +116,24 @@ 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
        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
        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
        listing = Property(
            mls=mls,
@@ -119,15 +143,13 @@ class RealtorScraper(Scraper):
            property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
            status=property_info["basic"]["status"].upper(),
            list_price=property_info["basic"]["price"],
-            list_date=property_info["basic"]["list_date"].split("T")[0]
+            list_date=list_date,
-            if property_info["basic"].get("list_date")
+            prc_sqft=property_info["basic"].get("price")
-            else None,
+                     / property_info["basic"].get("sqft")
-            prc_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,
            last_sold_date=property_info["basic"]["sold_date"].split("T")[0]
            if property_info["basic"].get("sold_date")
            else None,
            last_sold_date=last_sold_date,
            latitude=property_info["address"]["location"]["coordinate"].get("lat")
            if able_to_get_lat_long
            else None,
@@ -136,6 +158,8 @@ class RealtorScraper(Scraper):
            else None,
            address=self._parse_address(property_info, search_type="handle_listing"),
            description=Description(
                primary_photo=property_info["primary_photo"].get("href", "").replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75"),
                alt_photos=self.process_alt_photos(property_info.get("photos", [])),
                style=property_info["basic"].get("type", "").upper(),
                beds=property_info["basic"].get("beds"),
                baths_full=property_info["basic"].get("baths_full"),
@@ -146,7 +170,8 @@ class RealtorScraper(Scraper):
                year_built=property_info["details"].get("year_built"),
                garage=property_info["details"].get("garage"),
                stories=property_info["details"].get("stories"),
-            )
+            ),
            days_on_mls=days_on_mls
        )
        return [listing]
@@ -175,7 +200,10 @@ class RealtorScraper(Scraper):
        if property_info["listings"] is None:
            return None
-        primary_listing = next((listing for listing in property_info["listings"] if listing["primary"]), None)
+        primary_listing = next(
            (listing for listing in property_info["listings"] if listing["primary"]),
            None,
        )
        if primary_listing:
            return primary_listing["listing_id"]
        else:
@@ -196,6 +224,7 @@ class RealtorScraper(Scraper):
                            stories
                        }
                        address {
                            street_direction
                            street_number
                            street_name
                            street_suffix
@@ -226,6 +255,12 @@ class RealtorScraper(Scraper):
                            units
                            year_built
                        }
                        primary_photo {
                            href
                        }
                        photos {
                            href
                        }
                    }
                }"""
@@ -269,6 +304,10 @@ class RealtorScraper(Scraper):
                                last_sold_date
                                list_price
                                price_per_sqft
                                flags {
                                    is_contingent
                                    is_pending
                                }
                                description {
                                    sqft
                                    beds
@@ -292,6 +331,7 @@ class RealtorScraper(Scraper):
                                }
                                location {
                                    address {
                                        street_direction
                                        street_number
                                        street_name
                                        street_suffix
@@ -308,19 +348,27 @@ class RealtorScraper(Scraper):
                                        name
                                    }
                                }
                                primary_photo {
                                    href
                                }
                                photos {
                                    href
                                }
                            }
                        }
                    }"""
-        date_param = (
+        date_param = ""
-            'sold_date: { min: "$today-%sD" }' % self.last_x_days
+        if self.listing_type == ListingType.SOLD:
-            if self.listing_type == ListingType.SOLD and self.last_x_days
+            if self.date_from and self.date_to:
-            else (
+                date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
-                'list_date: { min: "$today-%sD" }' % self.last_x_days
+            elif self.last_x_days:
-                if self.last_x_days
+                date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
-                else ""
+        else:
-            )
+            if self.date_from and self.date_to:
-        )
+                date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
            elif self.last_x_days:
                date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
        sort_param = (
            "sort: [{ field: sold_date, direction: desc }]"
@@ -328,29 +376,46 @@ class RealtorScraper(Scraper):
            else "sort: [{ field: list_date, direction: desc }]"
        )
-        pending_or_contingent_param = "or_filters: { contingent: true, pending: true }" if self.pending_or_contingent else ""
+        pending_or_contingent_param = (
-
+            "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 'foreclosure' in variables and variables['foreclosure'] == True:
               is_foreclosure = "foreclosure: true"
        if 'foreclosure' in variables and variables['foreclosure'] == False:
             is_foreclosure = "foreclosure: false"
        if search_type == "comps":  #: comps search, came from an address
            query = """query Property_search(
                    $coordinates: [Float]!
                    $radius: String!
                    $offset: Int!,
                    ) {
-                        property_search(
+                        home_search(
                            query: { 
                                %s
                                nearby: {
                                    coordinates: $coordinates
                                    radius: $radius 
                                }
                                status: %s
                                %s
                                %s
                            }
                            %s
                            limit: 200
                            offset: $offset
                    ) %s""" % (
-                self.listing_type.value.lower(),
+                is_foreclosure,        
                listing_type.value.lower(),
                date_param,
                pending_or_contingent_param,
                sort_param,
                results_query,
            )
@@ -364,6 +429,7 @@ class RealtorScraper(Scraper):
                            ) {
                                home_search(
                                    query: {
                                        %s
                                        city: $city
                                        county: $county
                                        postal_code: $postal_code
@@ -376,7 +442,8 @@ class RealtorScraper(Scraper):
                                    limit: 200
                                    offset: $offset
                                ) %s""" % (
-                self.listing_type.value.lower(),
+                is_foreclosure,
                listing_type.value.lower(),
                date_param,
                pending_or_contingent_param,
                sort_param,
@@ -384,7 +451,7 @@ class RealtorScraper(Scraper):
            )
        else:  #: general search, came from an address
            query = (
-                    """query Property_search(
+                """query Property_search(
                        $property_id: [ID]!
                        $offset: Int!,
                    ) {
@@ -394,7 +461,9 @@ class RealtorScraper(Scraper):
                            }
                            limit: 1
                            offset: $offset
-                        ) %s""" % results_query)
+                        ) %s"""
                % results_query
            )
        payload = {
            "query": query,
@@ -404,7 +473,7 @@ 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 search_type == "area" else "property_search"
+        search_key = "home_search" if "home_search" in query else "property_search"
        properties: list[Property] = []
@@ -419,7 +488,6 @@ class RealtorScraper(Scraper):
            return {"total": 0, "properties": []}
        for result in response_json["data"][search_key]["results"]:
            self.counter += 1
            mls = (
                result["source"].get("id")
                if "source" in result and isinstance(result["source"], dict)
@@ -436,13 +504,18 @@ class RealtorScraper(Scraper):
                and result["location"]["address"].get("coordinate")
            )
            is_pending = result["flags"].get("is_pending") or result["flags"].get("is_contingent")
            if is_pending and self.listing_type != ListingType.PENDING:
                continue
            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']}",
+                property_url=f"{self.PROPERTY_URL}{result['property_id']}" if self.listing_type != ListingType.FOR_RENT else f"{self.PROPERTY_URL}M{result['property_id']}?listing_status=rental",
-                status=result["status"].upper(),
+                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")
@@ -459,8 +532,8 @@ class RealtorScraper(Scraper):
                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),
                days_on_mls=self.calculate_days_on_mls(result)
            )
            properties.append(realty_property)
@@ -471,19 +544,30 @@ class RealtorScraper(Scraper):
    def search(self):
        location_info = self.handle_location()
        if not location_info:
            return []
        location_type = location_info["area_type"]
        search_variables = {
            "offset": 0,
        }
-
+     
-        search_type = "comps" if self.radius and location_type == "address" else "address" if location_type == "address" and not self.radius else "area"
+        search_type = (
            "comps"
            if self.radius and location_type == "address"
            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:
@@ -500,6 +584,11 @@ class RealtorScraper(Scraper):
                    "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"),
@@ -508,6 +597,9 @@ 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"]
@@ -541,28 +633,54 @@ 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(
+            address = result['location']['address']
-                street=f"{result['location']['address']['street_number']} {result['location']['address']['street_name']} {result['location']['address']['street_suffix']}",
+        else:
-                unit=result["location"]["address"]["unit"],
+            address = result["address"]
-                city=result["location"]["address"]["city"],
+
                state=result["location"]["address"]["state_code"],
                zip=result["location"]["address"]["postal_code"],
            )
        return Address(
-            street=f"{result['address']['street_number']} {result['address']['street_name']} {result['address']['street_suffix']}",
+            street=" ".join([
-            unit=result["address"]["unit"],
+                self.handle_none_safely(address.get('street_number')),
-            city=result["address"]["city"],
+                self.handle_none_safely(address.get('street_direction')),
-            state=result["address"]["state_code"],
+                self.handle_none_safely(address.get('street_name')),
-            zip=result["address"]["postal_code"],
+                self.handle_none_safely(address.get('street_suffix')),
            ]).strip(),
            unit=address["unit"],
            city=address["city"],
            state=address["state_code"],
            zip=address["postal_code"],
        )
    @staticmethod
    def _parse_description(result: dict) -> Description:
        description_data = result.get("description", {})
        if description_data is None or not isinstance(description_data, dict):
            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=description_data.get("type", "").upper(),
+            primary_photo=primary_photo,
            alt_photos=RealtorScraper.process_alt_photos(result.get("photos")),
            style=style,
            beds=description_data.get("beds"),
            baths_full=description_data.get("baths_full"),
            baths_half=description_data.get("baths_half"),
@@ -573,3 +691,36 @@ class RealtorScraper(Scraper):
            garage=description_data.get("garage"),
            stories=description_data.get("stories"),
        )
    @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
--- a/homeharvest/exceptions.py
+++ b/homeharvest/exceptions.py
@@ -1,6 +1,5 @@
 class InvalidListingType(Exception):
    """Raised when a provided listing type is does not exist."""
-
+class InvalidDate(Exception):
-class NoResultsFound(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 no results are found for the given location"""
--- a/homeharvest/utils.py
+++ b/homeharvest/utils.py
@@ -1,6 +1,7 @@
 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",
@@ -18,6 +19,7 @@ ordered_properties = [
    "half_baths",
    "sqft",
    "year_built",
    "days_on_mls",
    "list_price",
    "list_date",
    "sold_price",
@@ -29,6 +31,8 @@ ordered_properties = [
    "stories",
    "hoa_fee",
    "parking_garage",
    "primary_photo",
    "alt_photos",
 ]
@@ -47,6 +51,8 @@ def process_result(result: Property) -> pd.DataFrame:
    prop_data["price_per_sqft"] = prop_data["prc_sqft"]
    description = result.description
    prop_data["primary_photo"] = description.primary_photo
    prop_data["alt_photos"] = ", ".join(description.alt_photos)
    prop_data["style"] = description.style
    prop_data["beds"] = description.beds
    prop_data["full_baths"] = description.baths_full
@@ -69,3 +75,18 @@ def validate_input(listing_type: str) -> None:
        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")
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,86 +13,101 @@ files = [
 [[package]]
 name = "charset-normalizer"
-version = "3.2.0"
+version = "3.3.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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+    {file = "charset-normalizer-3.3.0.tar.gz", hash = "sha256:63563193aec44bce707e0c5ca64ff69fa72ed7cf34ce6e11d5127555756fd2f6"},
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-    {file = "pandas-2.1.0.tar.gz", hash = "sha256:62c24c7fc59e42b775ce0679cfa7b14a5f9bfb7643cfbe708c960699e05fb918"},
+    {file = "pandas-2.1.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:366da7b0e540d1b908886d4feb3d951f2f1e572e655c1160f5fde28ad4abb750"},
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    {file = "pandas-2.1.1-cp39-cp39-win_amd64.whl", hash = "sha256:4cdb0fab0400c2cb46dafcf1a0fe084c8bb2480a1fa8d81e19d15e12e6d4ded2"},
    {file = "pandas-2.1.1.tar.gz", hash = "sha256:fecb198dc389429be557cde50a2d46da8434a17fe37d7d41ff102e3987fd947b"},
 ]
 [package.dependencies]
 numpy = [
    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
-    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -408,17 +396,6 @@ files = [
    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
 ]
 [[package]]
 name = "tls-client"
 version = "0.2.2"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
    {file = "tls_client-0.2.2-py3-none-any.whl", hash = "sha256:30934871397cdad6862e00b5634f382666314a452ddd3d774e18323a0ad9b765"},
    {file = "tls_client-0.2.2.tar.gz", hash = "sha256:78bc0e291e3aadc6c5e903b62bb26c01374577691f2a9e5e17899900a5927a13"},
 ]
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -443,13 +420,13 @@ files = [
 [[package]]
 name = "urllib3"
-version = "2.0.4"
+version = "2.0.6"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "urllib3-2.0.4-py3-none-any.whl", hash = "sha256:de7df1803967d2c2a98e4b11bb7d6bd9210474c46e8a0401514e3a42a75ebde4"},
+    {file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"},
-    {file = "urllib3-2.0.4.tar.gz", hash = "sha256:8d22f86aae8ef5e410d4f539fde9ce6b2113a001bb4d189e0aed70642d602b11"},
+    {file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"},
 ]
 [package.extras]
@@ -460,5 +437,5 @@ zstd = ["zstandard (>=0.18.0)"]
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.10"
+python-versions = ">=3.10,<3.13"
-content-hash = "9b77e1a09fcf2cf5e7e6be53f304cd21a6a51ea51680d661a178afe5e5343670"
+content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,20 +1,18 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.3.0"
+version = "0.3.12"
-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/ZacharyHampton/HomeHarvest"
+homepage = "https://github.com/Bunsly/HomeHarvest"
 readme = "README.md"
 [tool.poetry.scripts]
 homeharvest = "homeharvest.cli:main"
 [tool.poetry.dependencies]
-python = "^3.10"
+python = ">=3.10,<3.13"
 requests = "^2.31.0"
-pandas = "^2.1.0"
+pandas = "^2.1.1"
 openpyxl = "^3.1.2"
 tls-client = "^0.2.2"
 [tool.poetry.group.dev.dependencies]
--- a/tests/test_realtor.py
+++ b/tests/test_realtor.py
@@ -1,30 +1,69 @@
 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",
+        location="Surprise, AZ", listing_type="pending"
        pending_or_contingent=True,
    )
-    regular_result = scrape_property(
+    regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
        location="Surprise, AZ",
        pending_or_contingent=False,
    )
-    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)
 def test_realtor_pending_comps():
    pending_comps = scrape_property(
        location="2530 Al Lipscomb Way",
        radius=5,
        past_days=180,
        listing_type="pending",
    )
    for_sale_comps = scrape_property(
        location="2530 Al Lipscomb Way",
        radius=5,
        past_days=180,
        listing_type="for_sale",
    )
    sold_comps = scrape_property(
        location="2530 Al Lipscomb Way",
        radius=5,
        past_days=180,
        listing_type="sold",
    )
    results = [pending_comps, for_sale_comps, sold_comps]
    assert all([result is not None for result in results])
    #: assert all lengths are different
    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",
        radius=0.5,
-        property_younger_than=180,
+        past_days=180,
        listing_type="sold",
    )
@@ -33,11 +72,11 @@ def test_realtor_comps():
 def test_realtor_last_x_days_sold():
    days_result_30 = scrape_property(
-        location="Dallas, TX", listing_type="sold", property_younger_than=30
+        location="Dallas, TX", listing_type="sold", past_days=30
    )
    days_result_10 = scrape_property(
-        location="Dallas, TX", listing_type="sold", property_younger_than=10
+        location="Dallas, TX", listing_type="sold", past_days=10
    )
    assert all(
@@ -45,6 +84,20 @@ def test_realtor_last_x_days_sold():
    ) 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", date_from="2023-05-01", date_to="2023-05-28"
    )
    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_60]]
    ) and len(days_result_30) < len(days_result_60)
 def test_realtor_single_property():
    results = [
        scrape_property(
@@ -77,15 +130,24 @@ def test_realtor():
    assert all([result is not None for result in results])
-    bad_results = []
+
-    try:
+def test_realtor_bad_address():
-        bad_results += [
+    bad_results = scrape_property(
-            scrape_property(
+            location="abceefg ju098ot498hh9",
-                location="abceefg ju098ot498hh9",
+            listing_type="for_sale",
-                listing_type="for_sale",
+        )
-            )
+    if len(bad_results) == 0:
        ]
    except (InvalidListingType, NoResultsFound):
        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)
Author	SHA1	Message	Date
robertomr100	ab6a0e3b6e	Add foreclosure parameter (#55 )	2024-03-03 11:45:28 -06:00
Zachary Hampton	03198428de	Merge pull request #48 from Bunsly/for_rent_url fix: rent url	2024-01-09 13:12:30 -07:00
Cullen Watson	70fa071318	fix: rent url	2024-01-08 12:46:31 -06:00
Cullen Watson	f7e74cf535	Merge pull request #44 from Bunsly/fix_postal_search fix postal search to search just by zip	2023-12-02 00:40:13 -06:00
Cullen Watson	e17b976923	fix postal search to search just by zip	2023-12-02 00:39:28 -06:00
Zachary Hampton	ad13b55ea6	Update README.md	2023-11-30 11:48:48 -07:00
Cullen Watson	19f23c95c4	Merge pull request #43 from Bunsly/add_photos Add photos	2023-11-24 21:40:34 -06:00
Cullen	4676ec9839	chore: remove test file	2023-11-24 13:42:52 -06:00
Cullen	6dd0b058d3	chore: version	2023-11-24 13:41:46 -06:00
Cullen	a74c1a9950	enh: add photos	2023-11-24 13:40:57 -06:00
Cullen Watson	fa507dbc72	docs: typo	2023-11-20 01:05:10 -06:00
Cullen Watson	5b6a9943cc	Merge pull request #42 from Bunsly/street_dirction fix: add street direction	2023-11-08 16:53:29 -06:00
Cullen Watson	9816defaf3	chore: version	2023-11-08 16:53:05 -06:00
Cullen Watson	f692b438b2	fix: add street direction	2023-11-08 16:52:06 -06:00
Zachary Hampton	30f48f54c8	Update README.md	2023-11-06 22:13:01 -07:00
Cullen Watson	7f86f69610	docs: readme	2023-11-03 18:53:46 -05:00
Cullen Watson	cc64dacdb0	docs: readme - date_from, date_to	2023-11-03 18:52:22 -05:00
Cullen Watson	d3268d8e5a	Merge pull request #40 from Bunsly/date_range Add date_to and date_from params	2023-11-03 18:42:13 -05:00
Cullen Watson	4edad901c5	[enh] date_to and date_from	2023-11-03 18:40:34 -05:00
Zachary Hampton	c597a78191	- None address bug fix	2023-10-18 16:32:43 -07:00
Zachary Hampton	11a7d854f0	- remove pending listings from for_sale	2023-10-18 14:41:41 -07:00
Zachary Hampton	f726548cc6	Update pyproject.toml	2023-10-18 09:35:48 -07:00
Zachary Hampton	fad7d670eb	Update README.md	2023-10-18 08:37:42 -07:00
Zachary Hampton	89a6f93c9f	Update pyproject.toml	2023-10-18 08:37:26 -07:00
Zachary Hampton	e1090b06e4	Update README.md	2023-10-17 20:22:25 -07:00
Cullen Watson	5036e74b60	Merge branch 'master' of https://github.com/ZacharyHampton/HomeHarvest	2023-10-09 11:30:17 -05:00
Cullen Watson	2cb544bc8d	[chore] display clickable URLs in jupyter	2023-10-09 11:28:56 -05:00
Zachary Hampton	68cb365e03	Merge pull request #34 from ZacharyHampton/days_on_mls [enh] days_on_mls attr	2023-10-09 09:04:59 -07:00
Cullen Watson	23876d5725	[chore] function types	2023-10-09 11:02:51 -05:00
Cullen Watson	b59d55f6b5	[enh] days_on_mls attr	2023-10-09 11:00:36 -05:00
Cullen Watson	3c3adb5f29	[docs] update video	2023-10-05 20:24:23 -05:00
Zachary Hampton	6ede8622cc	- pending listing support - removal of pending_or_contingent param	2023-10-05 11:43:00 -07:00
Cullen Watson	9f50d33bdb	[chore] remove unused dependency	2023-10-05 10:11:45 -05:00
Cullen Watson	735ec021f7	[docs] README	2023-10-05 10:03:21 -05:00
Zachary Hampton	00537329cf	- version bump	2023-10-04 21:35:21 -07:00
Zachary Hampton	a9225b532f	- rename days variable	2023-10-04 21:35:14 -07:00
Zachary Hampton	ba7ad069c9	Merge pull request #32 from ZacharyHampton/key_error [fix] keyerror on style	2023-10-04 20:35:05 -07:00
Cullen Watson	22bda972b0	[chore] version number	2023-10-04 22:34:52 -05:00
Cullen Watson	6f5bbf79a4	[fix] keyerror on style	2023-10-04 22:33:21 -05:00
Cullen Watson	608cceba34	[docs] reorder	2023-10-04 22:12:16 -05:00
Cullen Watson	3609586995	[docs]: add contingent to example	2023-10-04 22:11:38 -05:00
Cullen Watson	68c7e411e4	[docs] pending / contingent searches	2023-10-04 22:07:51 -05:00
Cullen Watson	5e825601a7	[docs] update example	2023-10-04 21:50:54 -05:00
Cullen Watson	ce3f94d0af	[docs] update example	2023-10-04 21:50:16 -05:00