Update pyproject.toml

[enh] days_on_mls attr

README.md

@@ -1,16 +1,26 @@
 <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.
+**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)
 
-*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to work with us.*
-## Features
+**Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
 
-- Scrapes properties from **Zillow**, **Realtor.com** & **Redfin** simultaneously
-- Aggregates the properties in a Pandas DataFrame
+*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/bunsly/15min)** *to work with us.*
 
-[Video Guide for HomeHarvest](https://youtu.be/JnV7eR2Ve2o) - _updated for release v0.2.7_
+Check out another project we wrote: ***[JobSpy](https://github.com/Bunsly/JobSpy)** – a Python package for job scraping*
+
+## HomeHarvest Features
+
+- **Source**: Fetches properties directly from **Realtor.com**.
+- **Data Format**: Structures data to resemble MLS listings.
+- **Export Flexibility**: Options to save as either CSV or Excel.
+- **Usage Modes**:
+  - **Python**: For those who'd like to integrate scraping into their Python scripts.
+  - **CLI**: For users who prefer command-line operations.
+
+
+[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
 
 ![homeharvest](https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/b3d5d727-e67b-4a9f-85d8-1e65fd18620a)
 
@@ -23,138 +33,156 @@ pip install homeharvest
 
 ## Usage
 
-### CLI 
-
-```bash
-homeharvest "San Francisco, CA" -s zillow realtor.com redfin -l for_rent -o excel -f HomeHarvest
-```
-
-This will scrape properties from the specified sites for the given location and listing type, and save the results to an Excel file named `HomeHarvest.xlsx`.
-
-By default:
-- If `-s` or `--site_name` is not provided, it will scrape from all available sites.
-- If `-l` or `--listing_type` is left blank, the default is `for_sale`. Other options are `for_rent` or `sold`.
-- The `-o` or `--output` default format is `excel`. Options are `csv` or `excel`.
-- If `-f` or `--filename` is left blank, the default is `HomeHarvest_<current_timestamp>`.
-- If `-p` or `--proxy` is not provided, the scraper uses the local IP.
-- Use `-k` or `--keep_duplicates` to keep duplicate properties based on address. If not provided, duplicates will be removed.
 ### Python
 
 ```py
 from homeharvest import scrape_property
-import pandas as pd
+from datetime import datetime
 
-properties: pd.DataFrame = scrape_property(
-    site_name=["zillow", "realtor.com", "redfin"],
-    location="85281",
-    listing_type="for_rent" # for_sale / sold
+# Generate filename based on current timestamp
+current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+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)
+  # 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)}")
 
-#: Note, to export to CSV or Excel, use properties.to_csv() or properties.to_excel().
-print(properties)
+# Export to csv
+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
-```py
->>> properties.head()
-                                        property_url site_name listing_type  apt_min_price  apt_max_price   ...  
-0  https://www.redfin.com/AZ/Tempe/1003-W-Washing...    redfin     for_rent         1666.0         2750.0   ... 
-1  https://www.redfin.com/AZ/Tempe/VELA-at-Town-L...    redfin     for_rent         1665.0         3763.0   ...  
-2  https://www.redfin.com/AZ/Tempe/Camden-Tempe/a...    redfin     for_rent         1939.0         3109.0   ...  
-3  https://www.redfin.com/AZ/Tempe/Emerson-Park/a...    redfin     for_rent         1185.0         1817.0   ... 
-4  https://www.redfin.com/AZ/Tempe/Rio-Paradiso-A...    redfin     for_rent         1470.0         2235.0   ...   
-[5 rows x 41 columns]
-```
-
-### Parameters for `scrape_properties()`
 ```plaintext
-Required
-├── location (str): address in various formats e.g. just zip, full address, city/state, etc.
-└── listing_type (enum): for_rent, for_sale, sold
-Optional
-├── site_name (list[enum], default=all three sites): zillow, realtor.com, redfin
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
-└── keep_duplicates (bool, default=False): whether to keep or remove duplicate properties based on address
+>>> properties.head()
+    MLS       MLS # Status          Style  ...     COEDate LotSFApx PrcSqft Stories
+0  SDCA   230018348   SOLD         CONDOS  ...  2023-10-03   290110     803       2
+1  SDCA   230016614   SOLD      TOWNHOMES  ...  2023-10-03     None     838       3
+2  SDCA   230016367   SOLD         CONDOS  ...  2023-10-03    30056     649       1
+3  MRCA  NDP2306335   SOLD  SINGLE_FAMILY  ...  2023-10-03     7519     661       2
+4  SDCA   230014532   SOLD         CONDOS  ...  2023-10-03     None     752       1
+[5 rows x 22 columns]
 ```
 
+### Parameters for `scrape_property()`
+```
+Required
+├── location (str): The address in various formats - this could be just a zip code, a full address, or city/state, etc.
+└── listing_type (option): Choose the type of listing.
+    - '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)
+│
+├── 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)
+│
+├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
+│
+└── proxy (string): In format 'http://user:pass@host:port'
+
+```
 ### Property Schema
 ```plaintext
 Property
 ├── Basic Information:
-│   ├── property_url (str)
-│   ├── site_name (enum): zillow, redfin, realtor.com
-│   ├── listing_type (enum): for_sale, for_rent, sold
-│   └── property_type (enum): house, apartment, condo, townhouse, single_family, multi_family, building
+│ ├── property_url
+│ ├── mls
+│ ├── mls_id
+│ └── status
 
 ├── Address Details:
-│   ├── street_address (str)
-│   ├── city (str)
-│   ├── state (str)
-│   ├── zip_code (str)
-│   ├── unit (str)
-│   └── country (str)
+│ ├── street
+│ ├── unit
+│ ├── city
+│ ├── state
+│ └── zip_code
 
-├── House for Sale Features:
-│   ├── tax_assessed_value (int)
-│   ├── lot_area_value (float)
-│   ├── lot_area_unit (str)
-│   ├── stories (int)
-│   ├── year_built (int)
-│   └── price_per_sqft (int)
+├── Property Description:
+│ ├── style
+│ ├── beds
+│ ├── full_baths
+│ ├── half_baths
+│ ├── sqft
+│ ├── year_built
+│ ├── stories
+│ └── lot_sqft
 
-├── Building for Sale and Apartment Details:
-│   ├── bldg_name (str)
-│   ├── beds_min (int)
-│   ├── beds_max (int)
-│   ├── baths_min (float)
-│   ├── baths_max (float)
-│   ├── sqft_min (int)
-│   ├── sqft_max (int)
-│   ├── price_min (int)
-│   ├── price_max (int)
-│   ├── area_min (int)
-│   └── unit_count (int)
+├── Property Listing Details:
+│ ├── days_on_mls
+│ ├── list_price
+│ ├── list_date
+│ ├── sold_price
+│ ├── last_sold_date
+│ ├── price_per_sqft
+│ └── hoa_fee
 
-├── Miscellaneous Details:
-│   ├── mls_id (str)
-│   ├── agent_name (str)
-│   ├── img_src (str)
-│   ├── description (str)
-│   ├── status_text (str)
-│   └── posted_time (str)
+├── Location Details:
+│ ├── latitude
+│ ├── longitude
 
-└── Location Details:
-    ├── latitude (float)
-    └── longitude (float)
+└── Parking Details:
+    └── parking_garage
 ```
-## Supported Countries for Property Scraping
-
-* **Zillow**: contains listings in the **US** & **Canada** 
-* **Realtor.com**: mainly from the **US** but also has international listings
-* **Redfin**: listings mainly in the **US**, **Canada**, & has expanded to some areas in **Mexico**
 
 ### Exceptions
 The following exceptions may be raised when using HomeHarvest:
 
-- `InvalidSite` - valid options: `zillow`, `redfin`, `realtor.com`
 - `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
-- `NoResultsFound` - no properties found from your input
-- `GeoCoordsNotFound` - if Zillow scraper is not able to derive geo-coordinates from the location you input
+- `NoResultsFound` - no properties found from your search
+  
   
 ## Frequently Asked Questions
-
 ---
 
-**Q: Encountering issues with your queries?**  
-**A:** Try a single site and/or broaden the location. If problems persist, [submit an issue](https://github.com/ZacharyHampton/HomeHarvest/issues).
+**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 the real estate site for sending too many requests. Currently, **Zillow** is particularly aggressive with blocking. We recommend:
+**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 to change your IP address.
+- Trying a VPN or useing a proxy as a parameter to scrape_property() to change your IP address.
 
 ---
 

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",
@@ -31,7 +33,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# scrapes all 3 sites by default\n",
+    "# check for sale properties\n",
     "scrape_property(\n",
     "    location=\"dallas\",\n",
     "    listing_type=\"for_sale\"\n",
@@ -53,7 +55,6 @@
     "# search a specific address\n",
     "scrape_property(\n",
     "    location=\"2530 Al Lipscomb Way\",\n",
-    "    site_name=\"zillow\",\n",
     "    listing_type=\"for_sale\"\n",
     ")"
    ]
@@ -68,7 +69,6 @@
     "# check rentals\n",
     "scrape_property(\n",
     "    location=\"chicago, illinois\",\n",
-    "    site_name=[\"redfin\", \"zillow\"],\n",
     "    listing_type=\"for_rent\"\n",
     ")"
    ]
@@ -86,11 +86,34 @@
    "outputs": [],
    "source": [
     "# check sold properties\n",
-    "scrape_property(\n",
+    "properties = scrape_property(\n",
     "    location=\"90210\",\n",
-    "    site_name=[\"redfin\"],\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))"
    ]
   }
  ],

examples/HomeHarvest_Demo.py

@@ -0,0 +1,20 @@
+from homeharvest import scrape_property
+from datetime import datetime
+
+# Generate filename based on current timestamp
+current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+filename = f"HomeHarvest_{current_timestamp}.csv"
+
+properties = scrape_property(
+    location="San Diego, CA",
+    listing_type="sold",  # or (for_sale, for_rent)
+    past_days=30,  # sold in last 30 days - listed in last x days if (for_sale, for_rent)
+    # 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())

homeharvest/__init__.py

@@ -1,171 +1,47 @@
+import warnings
 import pandas as pd
-from typing import Union
-import concurrent.futures
-from concurrent.futures import ThreadPoolExecutor
-
 from .core.scrapers import ScraperInput
-from .core.scrapers.redfin import RedfinScraper
+from .utils import process_result, ordered_properties, validate_input
 from .core.scrapers.realtor import RealtorScraper
-from .core.scrapers.zillow import ZillowScraper
-from .core.scrapers.models import ListingType, Property, SiteName
-from .exceptions import InvalidSite, InvalidListingType
-
-
-_scrapers = {
-    "redfin": RedfinScraper,
-    "realtor.com": RealtorScraper,
-    "zillow": ZillowScraper,
-}
-
-
-def _validate_input(site_name: str, listing_type: str) -> None:
-    if site_name.lower() not in _scrapers:
-        raise InvalidSite(f"Provided site, '{site_name}', does not exist.")
-
-    if listing_type.upper() not in ListingType.__members__:
-        raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
-
-
-def _get_ordered_properties(result: Property) -> list[str]:
-    return [
-        "property_url",
-        "site_name",
-        "listing_type",
-        "property_type",
-        "status_text",
-        "baths_min",
-        "baths_max",
-        "beds_min",
-        "beds_max",
-        "sqft_min",
-        "sqft_max",
-        "price_min",
-        "price_max",
-        "unit_count",
-        "tax_assessed_value",
-        "price_per_sqft",
-        "lot_area_value",
-        "lot_area_unit",
-        "address_one",
-        "address_two",
-        "city",
-        "state",
-        "zip_code",
-        "posted_time",
-        "area_min",
-        "bldg_name",
-        "stories",
-        "year_built",
-        "agent_name",
-        "mls_id",
-        "img_src",
-        "latitude",
-        "longitude",
-        "description",
-    ]
-
-
-def _process_result(result: Property) -> pd.DataFrame:
-    prop_data = result.__dict__
-
-    prop_data["site_name"] = prop_data["site_name"].value
-    prop_data["listing_type"] = prop_data["listing_type"].value.lower()
-    if "property_type" in prop_data and prop_data["property_type"] is not None:
-        prop_data["property_type"] = prop_data["property_type"].value.lower()
-    else:
-        prop_data["property_type"] = None
-    if "address" in prop_data:
-        address_data = prop_data["address"]
-        prop_data["address_one"] = address_data.address_one
-        prop_data["address_two"] = address_data.address_two
-        prop_data["city"] = address_data.city
-        prop_data["state"] = address_data.state
-        prop_data["zip_code"] = address_data.zip_code
-
-        del prop_data["address"]
-
-    properties_df = pd.DataFrame([prop_data])
-    properties_df = properties_df[_get_ordered_properties(result)]
-
-    return properties_df
-
-
-def _scrape_single_site(location: str, site_name: str, listing_type: str, proxy: str = None) -> pd.DataFrame:
-    """
-    Helper function to scrape a single site.
-    """
-    _validate_input(site_name, listing_type)
-
-    scraper_input = ScraperInput(
-        location=location,
-        listing_type=ListingType[listing_type.upper()],
-        site_name=SiteName.get_by_value(site_name.lower()),
-        proxy=proxy,
-    )
-
-    site = _scrapers[site_name.lower()](scraper_input)
-    results = site.search()
-
-    properties_dfs = [_process_result(result) for result in results]
-    properties_dfs = [df.dropna(axis=1, how="all") for df in properties_dfs if not df.empty]
-    if not properties_dfs:
-        return pd.DataFrame()
-
-    return pd.concat(properties_dfs, ignore_index=True)
+from .core.scrapers.models import ListingType
+from .exceptions import InvalidListingType, NoResultsFound
 
 
 def scrape_property(
     location: str,
-    site_name: Union[str, list[str]] = None,
     listing_type: str = "for_sale",
+    radius: float = None,
+    mls_only: bool = False,
+    past_days: int = None,
     proxy: str = None,
-    keep_duplicates: bool = False
 ) -> pd.DataFrame:
     """
-    Scrape property from various sites from a given location and listing type.
-
-    :returns: pd.DataFrame
-    :param location: US Location (e.g. 'San Francisco, CA', 'Cook County, IL', '85281', '2530 Al Lipscomb Way')
-    :param site_name: Site name or list of site names (e.g. ['realtor.com', 'zillow'], 'redfin')
-    :param listing_type: Listing type (e.g. 'for_sale', 'for_rent', 'sold')
-    :return: pd.DataFrame containing properties
+    Scrape properties from Realtor.com based on a given location and listing type.
+    :param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
+    :param listing_type: Listing Type (for_sale, for_rent, sold)
+    :param 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 proxy: Proxy to use for scraping
     """
-    if site_name is None:
-        site_name = list(_scrapers.keys())
+    validate_input(listing_type)
 
-    if not isinstance(site_name, list):
-        site_name = [site_name]
+    scraper_input = ScraperInput(
+        location=location,
+        listing_type=ListingType[listing_type.upper()],
+        proxy=proxy,
+        radius=radius,
+        mls_only=mls_only,
+        last_x_days=past_days,
+    )
 
-    results = []
+    site = RealtorScraper(scraper_input)
+    results = site.search()
 
-    if len(site_name) == 1:
-        final_df = _scrape_single_site(location, site_name[0], listing_type, proxy)
-        results.append(final_df)
-    else:
-        with ThreadPoolExecutor() as executor:
-            futures = {
-                executor.submit(_scrape_single_site, location, s_name, listing_type, proxy): s_name
-                for s_name in site_name
-            }
+    properties_dfs = [process_result(result) for result in results]
+    if not properties_dfs:
+        raise NoResultsFound("no results found for the query")
 
-            for future in concurrent.futures.as_completed(futures):
-                result = future.result()
-                results.append(result)
-
-    results = [df for df in results if not df.empty and not df.isna().all().all()]
-
-    if not results:
-        return pd.DataFrame()
-
-    final_df = pd.concat(results, ignore_index=True)
-
-    columns_to_track = ["address_one", "address_two", "city"]
-
-    #: validate they exist, otherwise create them
-    for col in columns_to_track:
-        if col not in final_df.columns:
-            final_df[col] = None
-
-    if not keep_duplicates:
-        final_df = final_df.drop_duplicates(subset=columns_to_track, keep="first")
-    return final_df
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", category=FutureWarning)
+        return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties]

homeharvest/cli.py

@@ -5,15 +5,8 @@ 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(
-        "-s",
-        "--site_name",
-        type=str,
-        nargs="*",
-        default=None,
-        help="Site name(s) to scrape from (e.g., realtor, zillow)",
+        "location", type=str, help="Location to scrape (e.g., San Francisco, CA)"
     )
 
     parser.add_argument(
@@ -21,7 +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",
     )
 
@@ -43,17 +36,40 @@ def main():
     )
 
     parser.add_argument(
-        "-k",
-        "--keep_duplicates",
-        action="store_true",
-        help="Keep duplicate properties based on address"
+        "-p", "--proxy", type=str, default=None, help="Proxy to use for scraping"
+    )
+    parser.add_argument(
+        "-d",
+        "--days",
+        type=int,
+        default=None,
+        help="Sold/listed in last _ days filter.",
     )
 
-    parser.add_argument("-p", "--proxy", type=str, default=None, help="Proxy to use for scraping")
+    parser.add_argument(
+        "-r",
+        "--radius",
+        type=float,
+        default=None,
+        help="Get comparable properties within _ (eg. 0.0) miles. Only applicable for individual addresses.",
+    )
+    parser.add_argument(
+        "-m",
+        "--mls_only",
+        action="store_true",
+        help="If set, fetches only MLS listings.",
+    )
 
     args = parser.parse_args()
 
-    result = scrape_property(args.location, args.site_name, args.listing_type, proxy=args.proxy, keep_duplicates=args.keep_duplicates)
+    result = scrape_property(
+        args.location,
+        args.listing_type,
+        radius=args.radius,
+        proxy=args.proxy,
+        mls_only=args.mls_only,
+        past_days=args.days,
+    )
 
     if not args.filename:
         timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")

homeharvest/core/scrapers/__init__.py

@@ -7,22 +7,35 @@ from .models import Property, ListingType, SiteName
 class ScraperInput:
     location: str
     listing_type: ListingType
-    site_name: SiteName
+    radius: float | None = None
+    mls_only: bool | None = None
     proxy: str | None = None
+    last_x_days: int | None = None
 
 
 class Scraper:
-    def __init__(self, scraper_input: ScraperInput):
+    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 scraper_input.proxy:
             proxy_url = scraper_input.proxy
             proxies = {"http": proxy_url, "https": proxy_url}
             self.session.proxies.update(proxies)
+
         self.listing_type = scraper_input.listing_type
-        self.site_name = scraper_input.site_name
+        self.radius = scraper_input.radius
+        self.last_x_days = scraper_input.last_x_days
+        self.mls_only = scraper_input.mls_only
 
     def search(self) -> list[Property]:
         ...

homeharvest/core/scrapers/models.py

@@ -1,6 +1,6 @@
 from dataclasses import dataclass
 from enum import Enum
-from typing import Tuple
+from typing import Optional
 
 
 class SiteName(Enum):
@@ -19,91 +19,49 @@ class SiteName(Enum):
 class ListingType(Enum):
     FOR_SALE = "FOR_SALE"
     FOR_RENT = "FOR_RENT"
+    PENDING = "PENDING"
     SOLD = "SOLD"
 
 
-class PropertyType(Enum):
-    HOUSE = "HOUSE"
-    BUILDING = "BUILDING"
-    CONDO = "CONDO"
-    TOWNHOUSE = "TOWNHOUSE"
-    SINGLE_FAMILY = "SINGLE_FAMILY"
-    MULTI_FAMILY = "MULTI_FAMILY"
-    MANUFACTURED = "MANUFACTURED"
-    NEW_CONSTRUCTION = "NEW_CONSTRUCTION"
-    APARTMENT = "APARTMENT"
-    APARTMENTS = "APARTMENTS"
-    LAND = "LAND"
-    LOT = "LOT"
-    OTHER = "OTHER"
-
-    BLANK = "BLANK"
-
-    @classmethod
-    def from_int_code(cls, code):
-        mapping = {
-            1: cls.HOUSE,
-            2: cls.CONDO,
-            3: cls.TOWNHOUSE,
-            4: cls.MULTI_FAMILY,
-            5: cls.LAND,
-            6: cls.OTHER,
-            8: cls.SINGLE_FAMILY,
-            13: cls.SINGLE_FAMILY,
-        }
-
-        return mapping.get(code, cls.BLANK)
-
-
 @dataclass
 class Address:
-    address_one: str | None = None
-    address_two: str | None = "#"
+    street: str | None = None
+    unit: str | None = None
     city: str | None = None
     state: str | None = None
-    zip_code: str | None = None
+    zip: str | None = None
+
+
+@dataclass
+class Description:
+    style: str | None = None
+    beds: int | None = None
+    baths_full: int | None = None
+    baths_half: int | None = None
+    sqft: int | None = None
+    lot_sqft: int | None = None
+    sold_price: int | None = None
+    year_built: int | None = None
+    garage: float | None = None
+    stories: int | None = None
 
 
 @dataclass
 class Property:
     property_url: str
-    site_name: SiteName
-    listing_type: ListingType
-    address: Address
-    property_type: PropertyType | None = None
-
-    # house for sale
-    tax_assessed_value: int | None = None
-    lot_area_value: float | None = None
-    lot_area_unit: str | None = None
-    stories: int | None = None
-    year_built: int | None = None
-    price_per_sqft: int | None = None
+    mls: str | None = None
     mls_id: str | None = None
+    status: str | None = None
+    address: Address | None = None
 
-    agent_name: str | None = None
-    img_src: str | None = None
-    description: str | None = None
-    status_text: str | None = None
-    posted_time: str | None = None
-
-    # building for sale
-    bldg_name: str | None = None
-    area_min: int | None = None
-
-    beds_min: int | None = None
-    beds_max: int | None = None
-
-    baths_min: float | None = None
-    baths_max: float | None = None
-
-    sqft_min: int | None = None
-    sqft_max: int | None = None
-
-    price_min: int | None = None
-    price_max: int | None = None
-
-    unit_count: int | None = None
+    list_price: int | None = None
+    list_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

homeharvest/core/scrapers/realtor/__init__.py

@@ -2,39 +2,26 @@
 homeharvest.realtor.__init__
 ~~~~~~~~~~~~
 
-This module implements the scraper for relator.com
+This module implements the scraper for realtor.com
 """
-from ..models import Property, Address
+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 ....utils import parse_address_one, parse_address_two
-from concurrent.futures import ThreadPoolExecutor, as_completed
+from ..models import Property, Address, ListingType, Description
 
 
 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/"
+    ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
+
     def __init__(self, scraper_input):
-        self.counter = 1
         super().__init__(scraper_input)
-        self.search_url = (
-            "https://www.realtor.com/api/v1/rdc_search_srp?client_id=rdc-search-new-communities&schema=vesta"
-        )
 
     def handle_location(self):
-        headers = {
-            "authority": "parser-external.geo.moveaws.com",
-            "accept": "*/*",
-            "accept-language": "en-US,en;q=0.9",
-            "origin": "https://www.realtor.com",
-            "referer": "https://www.realtor.com/",
-            "sec-ch-ua": '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
-            "sec-ch-ua-mobile": "?0",
-            "sec-ch-ua-platform": '"Windows"',
-            "sec-fetch-dest": "empty",
-            "sec-fetch-mode": "cors",
-            "sec-fetch-site": "cross-site",
-            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36",
-        }
-
         params = {
             "input": self.location,
             "client_id": self.listing_type.value.lower().replace("_", "-"),
@@ -43,9 +30,8 @@ class RealtorScraper(Scraper):
         }
 
         response = self.session.get(
-            "https://parser-external.geo.moveaws.com/suggest",
+            self.ADDRESS_AUTOCOMPLETE_URL,
             params=params,
-            headers=headers,
         )
         response_json = response.json()
 
@@ -56,6 +42,165 @@ class RealtorScraper(Scraper):
 
         return result[0]
 
+    def handle_listing(self, listing_id: str) -> list[Property]:
+        query = """query Listing($listing_id: ID!) {
+                    listing(id: $listing_id) {
+                        source {
+                            id
+                            listing_id
+                        }
+                        address {
+                            street_number
+                            street_name
+                            street_suffix
+                            unit
+                            city
+                            state_code
+                            postal_code
+                            location {
+                                coordinate {
+                                    lat
+                                    lon
+                                }
+                            }
+                        }
+                        basic {
+                            sqft
+                            beds
+                            baths_full
+                            baths_half
+                            lot_sqft
+                            sold_price
+                            sold_price
+                            type
+                            price
+                            status
+                            sold_date
+                            list_date
+                        }
+                        details {
+                            year_built
+                            stories
+                            garage
+                            permalink
+                        }
+                    }
+                }"""
+
+        variables = {"listing_id": listing_id}
+        payload = {
+            "query": query,
+            "variables": variables,
+        }
+
+        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
+        response_json = response.json()
+
+        property_info = response_json["data"]["listing"]
+
+        mls = (
+            property_info["source"].get("id")
+            if "source" in property_info and isinstance(property_info["source"], dict)
+            else None
+        )
+
+        able_to_get_lat_long = (
+                property_info
+                and property_info.get("address")
+                and property_info["address"].get("location")
+                and property_info["address"]["location"].get("coordinate")
+        )
+        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,
+            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']}",
+            status=property_info["basic"]["status"].upper(),
+            list_price=property_info["basic"]["price"],
+            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,
+            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(
+                style=property_info["basic"].get("type", "").upper(),
+                beds=property_info["basic"].get("beds"),
+                baths_full=property_info["basic"].get("baths_full"),
+                baths_half=property_info["basic"].get("baths_half"),
+                sqft=property_info["basic"].get("sqft"),
+                lot_sqft=property_info["basic"].get("lot_sqft"),
+                sold_price=property_info["basic"].get("sold_price"),
+                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]
+
+    def get_latest_listing_id(self, property_id: str) -> str | None:
+        query = """query Property($property_id: ID!) {
+                    property(id: $property_id) {
+                        listings {
+                            listing_id
+                            primary
+                        }
+                    }
+                }
+                """
+
+        variables = {"property_id": property_id}
+        payload = {
+            "query": query,
+            "variables": variables,
+        }
+
+        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
+        response_json = response.json()
+
+        property_info = response_json["data"]["property"]
+        if property_info["listings"] is None:
+            return None
+
+        primary_listing = next(
+            (listing for listing in property_info["listings"] if listing["primary"]),
+            None,
+        )
+        if primary_listing:
+            return primary_listing["listing_id"]
+        else:
+            return property_info["listings"][0]["listing_id"]
+
     def handle_address(self, property_id: str) -> list[Property]:
         """
         Handles a specific address & returns one property
@@ -71,22 +216,19 @@ class RealtorScraper(Scraper):
                             stories
                         }
                         address {
-                            address_validation_code
-                            city
-                            country
-                            county
-                            line
-                            postal_code
-                            state_code
-                            street_direction
-                            street_name
                             street_number
+                            street_name
                             street_suffix
-                            street_post_direction
-                            unit_value
                             unit
-                            unit_descriptor
-                            zip
+                            city
+                            state_code
+                            postal_code
+                            location {
+                                coordinate {
+                                    lat
+                                    lon
+                                }
+                            }
                         }
                         basic {
                             baths
@@ -114,51 +256,138 @@ class RealtorScraper(Scraper):
             "variables": variables,
         }
 
-        response = self.session.post(self.search_url, json=payload)
+        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
         response_json = response.json()
 
         property_info = response_json["data"]["property"]
-        address_one, address_two = parse_address_one(property_info["address"]["line"])
 
         return [
             Property(
-                site_name=self.site_name,
-                address=Address(
-                    address_one=address_one,
-                    address_two=address_two,
-                    city=property_info["address"]["city"],
-                    state=property_info["address"]["state_code"],
-                    zip_code=property_info["address"]["postal_code"],
-                ),
-                property_url="https://www.realtor.com/realestateandhomes-detail/"
-                + property_info["details"]["permalink"],
-                stories=property_info["details"]["stories"],
-                year_built=property_info["details"]["year_built"],
-                price_per_sqft=property_info["basic"]["price"] // property_info["basic"]["sqft"]
-                if property_info["basic"]["sqft"] is not None and property_info["basic"]["price"] is not None
-                else None,
                 mls_id=property_id,
-                listing_type=self.listing_type,
-                lot_area_value=property_info["public_record"]["lot_size"]
-                if property_info["public_record"] is not None
-                else None,
-                beds_min=property_info["basic"]["beds"],
-                beds_max=property_info["basic"]["beds"],
-                baths_min=property_info["basic"]["baths"],
-                baths_max=property_info["basic"]["baths"],
-                sqft_min=property_info["basic"]["sqft"],
-                sqft_max=property_info["basic"]["sqft"],
-                price_min=property_info["basic"]["price"],
-                price_max=property_info["basic"]["price"],
+                property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
+                address=self._parse_address(
+                    property_info, search_type="handle_address"
+                ),
+                description=self._parse_description(property_info),
             )
         ]
 
-    def handle_area(self, variables: dict, return_total: bool = False) -> list[Property] | int:
+    def general_search(
+        self, variables: dict, search_type: str
+    ) -> Dict[str, Union[int, list[Property]]]:
         """
         Handles a location area & returns a list of properties
         """
-        query = (
-            """query Home_search(
+        results_query = """{
+                            count
+                            total
+                            results {
+                                property_id
+                                list_date
+                                status
+                                last_sold_price
+                                last_sold_date
+                                list_price
+                                price_per_sqft
+                                flags {
+                                    is_contingent
+                                    is_pending
+                                }
+                                description {
+                                    sqft
+                                    beds
+                                    baths_full
+                                    baths_half
+                                    lot_sqft
+                                    sold_price
+                                    year_built
+                                    garage
+                                    sold_price
+                                    type
+                                    name
+                                    stories
+                                }
+                                source {
+                                    id
+                                    listing_id
+                                }
+                                hoa {
+                                    fee
+                                }
+                                location {
+                                    address {
+                                        street_number
+                                        street_name
+                                        street_suffix
+                                        unit
+                                        city
+                                        state_code
+                                        postal_code
+                                        coordinate {
+                                            lon
+                                            lat
+                                        }
+                                    }
+                                    neighborhoods {
+                                        name
+                                    }
+                                }
+                            }
+                        }
+                    }"""
+
+        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 ""
+            )
+        )
+
+        sort_param = (
+            "sort: [{ field: sold_date, direction: desc }]"
+            if self.listing_type == ListingType.SOLD
+            else "sort: [{ field: list_date, direction: desc }]"
+        )
+
+        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
+
+        if search_type == "comps":  #: comps search, came from an address
+            query = """query Property_search(
+                    $coordinates: [Float]!
+                    $radius: String!
+                    $offset: Int!,
+                    ) {
+                        home_search(
+                            query: { 
+                                nearby: {
+                                    coordinates: $coordinates
+                                    radius: $radius 
+                                }
+                                status: %s
+                                %s
+                                %s
+                            }
+                            %s
+                            limit: 200
+                            offset: $offset
+                    ) %s""" % (
+                listing_type.value.lower(),
+                date_param,
+                pending_or_contingent_param,
+                sort_param,
+                results_query,
+            )
+        elif search_type == "area":  #: general search, came from a general location
+            query = """query Home_search(
                                 $city: String,
                                 $county: [String],
                                 $state_code: String,
@@ -172,56 +401,33 @@ class RealtorScraper(Scraper):
                                         postal_code: $postal_code
                                         state_code: $state_code
                                         status: %s
+                                        %s
+                                        %s
                                     }
+                                    %s
                                     limit: 200
                                     offset: $offset
+                                ) %s""" % (
+                listing_type.value.lower(),
+                date_param,
+                pending_or_contingent_param,
+                sort_param,
+                results_query,
+            )
+        else:  #: general search, came from an address
+            query = (
+                """query Property_search(
+                        $property_id: [ID]!
+                        $offset: Int!,
                     ) {
-                                count
-                                total
-                                results {
-                                    property_id
-                                    description {
-                                        baths
-                                        beds
-                                        lot_sqft
-                                        sqft
-                                        text
-                                        sold_price
-                                        stories
-                                        year_built
-                                        garage
-                                        unit_number
-                                        floor_number
+                        property_search(
+                            query: {
+                                property_id: $property_id
                             }
-                                    location {
-                                        address {
-                                            city
-                                            country
-                                            line
-                                            postal_code
-                                            state_code
-                                            state
-                                            street_direction
-                                            street_name
-                                            street_number
-                                            street_post_direction
-                                            street_suffix
-                                            unit
-                                            coordinate {
-                                                lon
-                                                lat
-                                            }
-                                        }
-                                    }
-                                    list_price
-                                    price_per_sqft
-                                    source {
-                                        id
-                                    }
-                                }
-                            }
-                        }"""
-            % self.listing_type.value.lower()
+                            limit: 1
+                            offset: $offset
+                        ) %s"""
+                % results_query
             )
 
         payload = {
@@ -229,12 +435,10 @@ class RealtorScraper(Scraper):
             "variables": variables,
         }
 
-        response = self.session.post(self.search_url, json=payload)
+        response = self.session.post(self.SEARCH_GQL_URL, json=payload)
         response.raise_for_status()
         response_json = response.json()
-
-        if return_total:
-            return response_json["data"]["home_search"]["total"]
+        search_key = "home_search" if "home_search" in query else "property_search"
 
         properties: list[Property] = []
 
@@ -242,89 +446,200 @@ class RealtorScraper(Scraper):
             response_json is None
             or "data" not in response_json
             or response_json["data"] is None
-            or "home_search" not in response_json["data"]
-            or response_json["data"]["home_search"] is None
-            or "results" not in response_json["data"]["home_search"]
+            or search_key not in response_json["data"]
+            or response_json["data"][search_key] is None
+            or "results" not in response_json["data"][search_key]
         ):
-            return []
+            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
+            )
+
+            if not mls and self.mls_only:
+                continue
+
+            able_to_get_lat_long = (
+                result
+                and result.get("location")
+                and result["location"].get("address")
+                and result["location"]["address"].get("coordinate")
+            )
+
+            is_pending = result["flags"].get("is_pending") or result["flags"].get("is_contingent")
 
-        for result in response_json["data"]["home_search"]["results"]:
-            self.counter += 1
-            address_one, _ = parse_address_one(result["location"]["address"]["line"])
             realty_property = Property(
-                address=Address(
-                    address_one=address_one,
-                    city=result["location"]["address"]["city"],
-                    state=result["location"]["address"]["state_code"],
-                    zip_code=result["location"]["address"]["postal_code"],
-                    address_two=parse_address_two(result["location"]["address"]["unit"]),
-                ),
-                latitude=result["location"]["address"]["coordinate"]["lat"]
-                if result
-                and result.get("location")
-                and result["location"].get("address")
-                and result["location"]["address"].get("coordinate")
-                and "lat" in result["location"]["address"]["coordinate"]
+                mls=mls,
+                mls_id=result["source"].get("listing_id")
+                if "source" in result and isinstance(result["source"], dict)
                 else None,
-                longitude=result["location"]["address"]["coordinate"]["lon"]
-                if result
-                and result.get("location")
-                and result["location"].get("address")
-                and result["location"]["address"].get("coordinate")
-                and "lon" in result["location"]["address"]["coordinate"]
+                property_url=f"{self.PROPERTY_URL}{result['property_id']}",
+                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,
-                site_name=self.site_name,
-                property_url="https://www.realtor.com/realestateandhomes-detail/" + result["property_id"],
-                stories=result["description"]["stories"],
-                year_built=result["description"]["year_built"],
-                price_per_sqft=result["price_per_sqft"],
-                mls_id=result["property_id"],
-                listing_type=self.listing_type,
-                lot_area_value=result["description"]["lot_sqft"],
-                beds_min=result["description"]["beds"],
-                beds_max=result["description"]["beds"],
-                baths_min=result["description"]["baths"],
-                baths_max=result["description"]["baths"],
-                sqft_min=result["description"]["sqft"],
-                sqft_max=result["description"]["sqft"],
-                price_min=result["list_price"],
-                price_max=result["list_price"],
+                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,
+                address=self._parse_address(result, search_type="general_search"),
+                description=self._parse_description(result),
+                days_on_mls=self.calculate_days_on_mls(result)
             )
             properties.append(realty_property)
 
-        return properties
+        return {
+            "total": response_json["data"][search_key]["total"],
+            "properties": properties,
+        }
 
     def search(self):
         location_info = self.handle_location()
         location_type = location_info["area_type"]
 
-        if location_type == "address":
-            property_id = location_info["mpr_id"]
-            return self.handle_address(property_id)
-
-        offset = 0
         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"
+        )
+        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
+                )
+                if gql_results["total"] == 0:
+                    listing_id = self.get_latest_listing_id(property_id)
+                    if listing_id is None:
+                        return self.handle_address(property_id)
+                    else:
+                        return self.handle_listing(listing_id)
+                else:
+                    return gql_results["properties"]
+
+            else:  #: general search, comps (radius)
+                coordinates = list(location_info["centroid"].values())
+                search_variables |= {
+                    "coordinates": coordinates,
+                    "radius": "{}mi".format(self.radius),
+                }
+
+        else:  #: general search, location
+            search_variables |= {
                 "city": location_info.get("city"),
                 "county": location_info.get("county"),
                 "state_code": location_info.get("state_code"),
                 "postal_code": location_info.get("postal_code"),
-            "offset": offset,
             }
 
-        total = self.handle_area(search_variables, return_total=True)
+        result = self.general_search(search_variables, search_type=search_type)
+        total = result["total"]
+        homes = result["properties"]
 
-        homes = []
         with ThreadPoolExecutor(max_workers=10) as executor:
             futures = [
                 executor.submit(
-                    self.handle_area,
+                    self.general_search,
                     variables=search_variables | {"offset": i},
-                    return_total=False,
+                    search_type=search_type,
                 )
-                for i in range(0, total, 200)
+                for i in range(200, min(total, 10000), 200)
             ]
 
             for future in as_completed(futures):
-                homes.extend(future.result())
+                homes.extend(future.result()["properties"])
 
         return homes
+
+    @staticmethod
+    def _parse_neighborhoods(result: dict) -> Optional[str]:
+        neighborhoods_list = []
+        neighborhoods = result["location"].get("neighborhoods", [])
+
+        if neighborhoods:
+            for neighborhood in neighborhoods:
+                name = neighborhood.get("name")
+                if name:
+                    neighborhoods_list.append(name)
+
+        return ", ".join(neighborhoods_list) if neighborhoods_list else None
+
+    @staticmethod
+    def _parse_address(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"],
+            )
+        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"],
+        )
+
+    @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()
+
+        return Description(
+            style=style,
+            beds=description_data.get("beds"),
+            baths_full=description_data.get("baths_full"),
+            baths_half=description_data.get("baths_half"),
+            sqft=description_data.get("sqft"),
+            lot_sqft=description_data.get("lot_sqft"),
+            sold_price=description_data.get("sold_price"),
+            year_built=description_data.get("year_built"),
+            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

homeharvest/core/scrapers/redfin/__init__.py

@@ -1,226 +0,0 @@
-"""
-homeharvest.redfin.__init__
-~~~~~~~~~~~~
-
-This module implements the scraper for redfin.com
-"""
-import json
-from typing import Any
-from .. import Scraper
-from ....utils import parse_address_two, parse_address_one
-from ..models import Property, Address, PropertyType, ListingType, SiteName
-from ....exceptions import NoResultsFound
-
-
-class RedfinScraper(Scraper):
-    def __init__(self, scraper_input):
-        super().__init__(scraper_input)
-        self.listing_type = scraper_input.listing_type
-
-    def _handle_location(self):
-        url = "https://www.redfin.com/stingray/do/location-autocomplete?v=2&al=1&location={}".format(self.location)
-
-        response = self.session.get(url)
-        response_json = json.loads(response.text.replace("{}&&", ""))
-
-        def get_region_type(match_type: str):
-            if match_type == "4":
-                return "2"  #: zip
-            elif match_type == "2":
-                return "6"  #: city
-            elif match_type == "1":
-                return "address"  #: address, needs to be handled differently
-
-        if "exactMatch" not in response_json["payload"]:
-            raise NoResultsFound("No results found for location: {}".format(self.location))
-
-        if response_json["payload"]["exactMatch"] is not None:
-            target = response_json["payload"]["exactMatch"]
-        else:
-            target = response_json["payload"]["sections"][0]["rows"][0]
-
-        return target["id"].split("_")[1], get_region_type(target["type"])
-
-    def _parse_home(self, home: dict, single_search: bool = False) -> Property:
-        def get_value(key: str) -> Any | None:
-            if key in home and "value" in home[key]:
-                return home[key]["value"]
-
-        if not single_search:
-            address = Address(
-                address_one=parse_address_one(get_value("streetLine"))[0],
-                address_two=parse_address_one(get_value("streetLine"))[1],
-                city=home.get("city"),
-                state=home.get("state"),
-                zip_code=home.get("zip"),
-            )
-        else:
-            address_info = home.get("streetAddress")
-            address_one, address_two = parse_address_one(address_info.get("assembledAddress"))
-
-            address = Address(
-                address_one=address_one,
-                address_two=address_two,
-                city=home.get("city"),
-                state=home.get("state"),
-                zip_code=home.get("zip"),
-            )
-
-        url = "https://www.redfin.com{}".format(home["url"])
-        lot_size_data = home.get("lotSize")
-
-        if not isinstance(lot_size_data, int):
-            lot_size = lot_size_data.get("value", None) if isinstance(lot_size_data, dict) else None
-        else:
-            lot_size = lot_size_data
-
-        return Property(
-            site_name=self.site_name,
-            listing_type=self.listing_type,
-            address=address,
-            property_url=url,
-            beds_min=home["beds"] if "beds" in home else None,
-            beds_max=home["beds"] if "beds" in home else None,
-            baths_min=home["baths"] if "baths" in home else None,
-            baths_max=home["baths"] if "baths" in home else None,
-            price_min=get_value("price"),
-            price_max=get_value("price"),
-            sqft_min=get_value("sqFt"),
-            sqft_max=get_value("sqFt"),
-            stories=home["stories"] if "stories" in home else None,
-            agent_name=get_value("listingAgent"),
-            description=home["listingRemarks"] if "listingRemarks" in home else None,
-            year_built=get_value("yearBuilt") if not single_search else home["yearBuilt"],
-            lot_area_value=lot_size,
-            property_type=PropertyType.from_int_code(home.get("propertyType")),
-            price_per_sqft=get_value("pricePerSqFt"),
-            mls_id=get_value("mlsId"),
-            latitude=home["latLong"]["latitude"] if "latLong" in home and "latitude" in home["latLong"] else None,
-            longitude=home["latLong"]["longitude"] if "latLong" in home and "longitude" in home["latLong"] else None,
-        )
-
-    def _handle_rentals(self, region_id, region_type):
-        url = f"https://www.redfin.com/stingray/api/v1/search/rentals?al=1&isRentals=true&region_id={region_id}&region_type={region_type}&num_homes=100000"
-
-        response = self.session.get(url)
-        response.raise_for_status()
-        homes = response.json()
-
-        properties_list = []
-
-        for home in homes["homes"]:
-            home_data = home["homeData"]
-            rental_data = home["rentalExtension"]
-
-            property_url = f"https://www.redfin.com{home_data.get('url', '')}"
-            address_info = home_data.get("addressInfo", {})
-            centroid = address_info.get("centroid", {}).get("centroid", {})
-            address = Address(
-                address_one=parse_address_one(address_info.get("formattedStreetLine"))[0],
-                city=address_info.get("city"),
-                state=address_info.get("state"),
-                zip_code=address_info.get("zip"),
-            )
-
-            price_range = rental_data.get("rentPriceRange", {"min": None, "max": None})
-            bed_range = rental_data.get("bedRange", {"min": None, "max": None})
-            bath_range = rental_data.get("bathRange", {"min": None, "max": None})
-            sqft_range = rental_data.get("sqftRange", {"min": None, "max": None})
-
-            property_ = Property(
-                property_url=property_url,
-                site_name=SiteName.REDFIN,
-                listing_type=ListingType.FOR_RENT,
-                address=address,
-                description=rental_data.get("description"),
-                latitude=centroid.get("latitude"),
-                longitude=centroid.get("longitude"),
-                baths_min=bath_range.get("min"),
-                baths_max=bath_range.get("max"),
-                beds_min=bed_range.get("min"),
-                beds_max=bed_range.get("max"),
-                price_min=price_range.get("min"),
-                price_max=price_range.get("max"),
-                sqft_min=sqft_range.get("min"),
-                sqft_max=sqft_range.get("max"),
-                img_src=home_data.get("staticMapUrl"),
-                posted_time=rental_data.get("lastUpdated"),
-                bldg_name=rental_data.get("propertyName"),
-            )
-
-            properties_list.append(property_)
-
-        if not properties_list:
-            raise NoResultsFound("No rentals found for the given location.")
-
-        return properties_list
-
-    def _parse_building(self, building: dict) -> Property:
-        street_address = " ".join(
-            [
-                building["address"]["streetNumber"],
-                building["address"]["directionalPrefix"],
-                building["address"]["streetName"],
-                building["address"]["streetType"],
-            ]
-        )
-        return Property(
-            site_name=self.site_name,
-            property_type=PropertyType("BUILDING"),
-            address=Address(
-                address_one=parse_address_one(street_address)[0],
-                city=building["address"]["city"],
-                state=building["address"]["stateOrProvinceCode"],
-                zip_code=building["address"]["postalCode"],
-                address_two=parse_address_two(
-                    " ".join(
-                        [
-                            building["address"]["unitType"],
-                            building["address"]["unitValue"],
-                        ]
-                    )
-                ),
-            ),
-            property_url="https://www.redfin.com{}".format(building["url"]),
-            listing_type=self.listing_type,
-            unit_count=building["numUnitsForSale"],
-        )
-
-    def handle_address(self, home_id: str):
-        """
-        EPs:
-        https://www.redfin.com/stingray/api/home/details/initialInfo?al=1&path=/TX/Austin/70-Rainey-St-78701/unit-1608/home/147337694
-        https://www.redfin.com/stingray/api/home/details/mainHouseInfoPanelInfo?propertyId=147337694&accessLevel=3
-        https://www.redfin.com/stingray/api/home/details/aboveTheFold?propertyId=147337694&accessLevel=3
-        https://www.redfin.com/stingray/api/home/details/belowTheFold?propertyId=147337694&accessLevel=3
-        """
-        url = "https://www.redfin.com/stingray/api/home/details/aboveTheFold?propertyId={}&accessLevel=3".format(
-            home_id
-        )
-
-        response = self.session.get(url)
-        response_json = json.loads(response.text.replace("{}&&", ""))
-
-        parsed_home = self._parse_home(response_json["payload"]["addressSectionInfo"], single_search=True)
-        return [parsed_home]
-
-    def search(self):
-        region_id, region_type = self._handle_location()
-
-        if region_type == "address":
-            home_id = region_id
-            return self.handle_address(home_id)
-
-        if self.listing_type == ListingType.FOR_RENT:
-            return self._handle_rentals(region_id, region_type)
-        else:
-            if self.listing_type == ListingType.FOR_SALE:
-                url = f"https://www.redfin.com/stingray/api/gis?al=1&region_id={region_id}&region_type={region_type}&num_homes=100000"
-            else:
-                url = f"https://www.redfin.com/stingray/api/gis?al=1&region_id={region_id}&region_type={region_type}&sold_within_days=30&num_homes=100000"
-            response = self.session.get(url)
-            response_json = json.loads(response.text.replace("{}&&", ""))
-            homes = [self._parse_home(home) for home in response_json["payload"]["homes"]] + [
-                self._parse_building(building) for building in response_json["payload"]["buildings"].values()
-            ]
-            return homes

homeharvest/core/scrapers/zillow/__init__.py

@@ -1,315 +0,0 @@
-"""
-homeharvest.zillow.__init__
-~~~~~~~~~~~~
-
-This module implements the scraper for zillow.com
-"""
-import re
-import json
-from .. import Scraper
-from ....utils import parse_address_one, parse_address_two
-from ....exceptions import GeoCoordsNotFound, NoResultsFound
-from ..models import Property, Address, ListingType, PropertyType
-
-
-class ZillowScraper(Scraper):
-    def __init__(self, scraper_input):
-        super().__init__(scraper_input)
-
-        if not self.is_plausible_location(self.location):
-            raise NoResultsFound("Invalid location input: {}".format(self.location))
-
-        listing_type_to_url_path = {
-            ListingType.FOR_SALE: "for_sale",
-            ListingType.FOR_RENT: "for_rent",
-            ListingType.SOLD: "recently_sold",
-        }
-
-        self.url = f"https://www.zillow.com/homes/{listing_type_to_url_path[self.listing_type]}/{self.location}_rb/"
-
-    def is_plausible_location(self, location: str) -> bool:
-        url = (
-            "https://www.zillowstatic.com/autocomplete/v3/suggestions?q={"
-            "}&abKey=6666272a-4b99-474c-b857-110ec438732b&clientId=homepage-render"
-        ).format(location)
-
-        response = self.session.get(url)
-
-        return response.json()["results"] != []
-
-    def search(self):
-        resp = self.session.get(self.url, headers=self._get_headers())
-        resp.raise_for_status()
-        content = resp.text
-
-        match = re.search(
-            r'<script id="__NEXT_DATA__" type="application/json">(.*?)</script>',
-            content,
-            re.DOTALL,
-        )
-        if not match:
-            raise NoResultsFound("No results were found for Zillow with the given Location.")
-
-        json_str = match.group(1)
-        data = json.loads(json_str)
-
-        if "searchPageState" in data["props"]["pageProps"]:
-            pattern = r'window\.mapBounds = \{\s*"west":\s*(-?\d+\.\d+),\s*"east":\s*(-?\d+\.\d+),\s*"south":\s*(-?\d+\.\d+),\s*"north":\s*(-?\d+\.\d+)\s*\};'
-
-            match = re.search(pattern, content)
-
-            if match:
-                coords = [float(coord) for coord in match.groups()]
-                return self._fetch_properties_backend(coords)
-
-            else:
-                raise GeoCoordsNotFound("Box bounds could not be located.")
-
-        elif "gdpClientCache" in data["props"]["pageProps"]:
-            gdp_client_cache = json.loads(data["props"]["pageProps"]["gdpClientCache"])
-            main_key = list(gdp_client_cache.keys())[0]
-
-            property_data = gdp_client_cache[main_key]["property"]
-            property = self._get_single_property_page(property_data)
-
-            return [property]
-        raise NoResultsFound("Specific property data not found in the response.")
-
-    def _fetch_properties_backend(self, coords):
-        url = "https://www.zillow.com/async-create-search-page-state"
-
-        filter_state_for_sale = {
-            "sortSelection": {
-                # "value": "globalrelevanceex"
-                "value": "days"
-            },
-            "isAllHomes": {"value": True},
-        }
-
-        filter_state_for_rent = {
-            "isForRent": {"value": True},
-            "isForSaleByAgent": {"value": False},
-            "isForSaleByOwner": {"value": False},
-            "isNewConstruction": {"value": False},
-            "isComingSoon": {"value": False},
-            "isAuction": {"value": False},
-            "isForSaleForeclosure": {"value": False},
-            "isAllHomes": {"value": True},
-        }
-
-        filter_state_sold = {
-            "isRecentlySold": {"value": True},
-            "isForSaleByAgent": {"value": False},
-            "isForSaleByOwner": {"value": False},
-            "isNewConstruction": {"value": False},
-            "isComingSoon": {"value": False},
-            "isAuction": {"value": False},
-            "isForSaleForeclosure": {"value": False},
-            "isAllHomes": {"value": True},
-        }
-
-        selected_filter = (
-            filter_state_for_rent
-            if self.listing_type == ListingType.FOR_RENT
-            else filter_state_for_sale
-            if self.listing_type == ListingType.FOR_SALE
-            else filter_state_sold
-        )
-
-        payload = {
-            "searchQueryState": {
-                "pagination": {},
-                "isMapVisible": True,
-                "mapBounds": {
-                    "west": coords[0],
-                    "east": coords[1],
-                    "south": coords[2],
-                    "north": coords[3],
-                },
-                "filterState": selected_filter,
-                "isListVisible": True,
-                "mapZoom": 11,
-            },
-            "wants": {"cat1": ["mapResults"]},
-            "isDebugRequest": False,
-        }
-        resp = self.session.put(url, headers=self._get_headers(), json=payload)
-        resp.raise_for_status()
-        a = resp.json()
-        return self._parse_properties(resp.json())
-
-    def _parse_properties(self, property_data: dict):
-        mapresults = property_data["cat1"]["searchResults"]["mapResults"]
-
-        properties_list = []
-
-        for result in mapresults:
-            if "hdpData" in result:
-                home_info = result["hdpData"]["homeInfo"]
-                address_data = {
-                    "address_one": parse_address_one(home_info["streetAddress"])[0],
-                    "address_two": parse_address_two(home_info["unit"]) if "unit" in home_info else "#",
-                    "city": home_info["city"],
-                    "state": home_info["state"],
-                    "zip_code": home_info["zipcode"],
-                }
-                property_obj = Property(
-                    site_name=self.site_name,
-                    address=Address(**address_data),
-                    property_url=f"https://www.zillow.com{result['detailUrl']}",
-                    tax_assessed_value=int(home_info["taxAssessedValue"]) if "taxAssessedValue" in home_info else None,
-                    property_type=PropertyType(home_info["homeType"]),
-                    listing_type=ListingType(
-                        home_info["statusType"] if "statusType" in home_info else self.listing_type
-                    ),
-                    status_text=result.get("statusText"),
-                    posted_time=result["variableData"]["text"]
-                    if "variableData" in result
-                    and "text" in result["variableData"]
-                    and result["variableData"]["type"] == "TIME_ON_INFO"
-                    else None,
-                    price_min=home_info.get("price"),
-                    price_max=home_info.get("price"),
-                    beds_min=int(home_info["bedrooms"]) if "bedrooms" in home_info else None,
-                    beds_max=int(home_info["bedrooms"]) if "bedrooms" in home_info else None,
-                    baths_min=home_info.get("bathrooms"),
-                    baths_max=home_info.get("bathrooms"),
-                    sqft_min=int(home_info["livingArea"]) if "livingArea" in home_info else None,
-                    sqft_max=int(home_info["livingArea"]) if "livingArea" in home_info else None,
-                    price_per_sqft=int(home_info["price"] // home_info["livingArea"])
-                    if "livingArea" in home_info and home_info["livingArea"] != 0 and "price" in home_info
-                    else None,
-                    latitude=result["latLong"]["latitude"],
-                    longitude=result["latLong"]["longitude"],
-                    lot_area_value=round(home_info["lotAreaValue"], 2) if "lotAreaValue" in home_info else None,
-                    lot_area_unit=home_info.get("lotAreaUnit"),
-                    img_src=result.get("imgSrc"),
-                )
-
-                properties_list.append(property_obj)
-
-            elif "isBuilding" in result:
-                price_string = result["price"].replace("$", "").replace(",", "").replace("+/mo", "")
-
-                match = re.search(r"(\d+)", price_string)
-                price_value = int(match.group(1)) if match else None
-                building_obj = Property(
-                    property_url=f"https://www.zillow.com{result['detailUrl']}",
-                    site_name=self.site_name,
-                    property_type=PropertyType("BUILDING"),
-                    listing_type=ListingType(result["statusType"]),
-                    img_src=result["imgSrc"],
-                    address=self._extract_address(result["address"]),
-                    baths_min=result["minBaths"],
-                    area_min=result.get("minArea"),
-                    bldg_name=result.get("communityName"),
-                    status_text=result["statusText"],
-                    beds_min=result["minBeds"],
-                    price_min=price_value if "+/mo" in result["price"] else None,
-                    price_max=price_value if "+/mo" in result["price"] else None,
-                    latitude=result["latLong"]["latitude"],
-                    longitude=result["latLong"]["longitude"],
-                    unit_count=result["unitCount"],
-                )
-
-                properties_list.append(building_obj)
-
-        return properties_list
-
-    def _get_single_property_page(self, property_data: dict):
-        """
-        This method is used when a user enters the exact location & zillow returns just one property
-        """
-        url = (
-            f"https://www.zillow.com{property_data['hdpUrl']}"
-            if "zillow.com" not in property_data["hdpUrl"]
-            else property_data["hdpUrl"]
-        )
-        address_data = property_data["address"]
-        address_one, address_two = parse_address_one(address_data["streetAddress"])
-        address = Address(
-            address_one=address_one,
-            address_two=address_two if address_two else "#",
-            city=address_data["city"],
-            state=address_data["state"],
-            zip_code=address_data["zipcode"],
-        )
-        property_type = property_data.get("homeType", None)
-        return Property(
-            site_name=self.site_name,
-            property_url=url,
-            property_type=PropertyType(property_type),
-            listing_type=self.listing_type,
-            address=address,
-            year_built=property_data.get("yearBuilt"),
-            tax_assessed_value=property_data.get("taxAssessedValue"),
-            lot_area_value=property_data.get("lotAreaValue"),
-            lot_area_unit=property_data["lotAreaUnits"].lower() if "lotAreaUnits" in property_data else None,
-            agent_name=property_data.get("attributionInfo", {}).get("agentName"),
-            stories=property_data.get("resoFacts", {}).get("stories"),
-            mls_id=property_data.get("attributionInfo", {}).get("mlsId"),
-            beds_min=property_data.get("bedrooms"),
-            beds_max=property_data.get("bedrooms"),
-            baths_min=property_data.get("bathrooms"),
-            baths_max=property_data.get("bathrooms"),
-            price_min=property_data.get("price"),
-            price_max=property_data.get("price"),
-            sqft_min=property_data.get("livingArea"),
-            sqft_max=property_data.get("livingArea"),
-            price_per_sqft=property_data.get("resoFacts", {}).get("pricePerSquareFoot"),
-            latitude=property_data.get("latitude"),
-            longitude=property_data.get("longitude"),
-            img_src=property_data.get("streetViewTileImageUrlMediumAddress"),
-            description=property_data.get("description"),
-        )
-
-    def _extract_address(self, address_str):
-        """
-        Extract address components from a string formatted like '555 Wedglea Dr, Dallas, TX',
-        and return an Address object.
-        """
-        parts = address_str.split(", ")
-
-        if len(parts) != 3:
-            raise ValueError(f"Unexpected address format: {address_str}")
-
-        address_one = parts[0].strip()
-        city = parts[1].strip()
-        state_zip = parts[2].split(" ")
-
-        if len(state_zip) == 1:
-            state = state_zip[0].strip()
-            zip_code = None
-        elif len(state_zip) == 2:
-            state = state_zip[0].strip()
-            zip_code = state_zip[1].strip()
-        else:
-            raise ValueError(f"Unexpected state/zip format in address: {address_str}")
-
-        address_one, address_two = parse_address_one(address_one)
-        return Address(
-            address_one=address_one,
-            address_two=address_two if address_two else "#",
-            city=city,
-            state=state,
-            zip_code=zip_code,
-        )
-
-    @staticmethod
-    def _get_headers():
-        return {
-            "authority": "www.zillow.com",
-            "accept": "*/*",
-            "accept-language": "en-US,en;q=0.9",
-            "content-type": "application/json",
-            "cookie": 'zjs_user_id=null; zg_anonymous_id=%220976ab81-2950-4013-98f0-108b15a554d2%22; zguid=24|%246b1bc625-3955-4d1e-a723-e59602e4ed08; g_state={"i_p":1693611172520,"i_l":1}; zgsession=1|d48820e2-1659-4d2f-b7d2-99a8127dd4f3; zjs_anonymous_id=%226b1bc625-3955-4d1e-a723-e59602e4ed08%22; JSESSIONID=82E8274D3DC8AF3AB9C8E613B38CF861; search=6|1697585860120%7Crb%3DDallas%252C-TX%26rect%3D33.016646%252C-96.555516%252C32.618763%252C-96.999347%26disp%3Dmap%26mdm%3Dauto%26sort%3Ddays%26listPriceActive%3D1%26fs%3D1%26fr%3D0%26mmm%3D0%26rs%3D0%26ah%3D0%26singlestory%3D0%26abo%3D0%26garage%3D0%26pool%3D0%26ac%3D0%26waterfront%3D0%26finished%3D0%26unfinished%3D0%26cityview%3D0%26mountainview%3D0%26parkview%3D0%26waterview%3D0%26hoadata%3D1%263dhome%3D0%26commuteMode%3Ddriving%26commuteTimeOfDay%3Dnow%09%0938128%09%7B%22isList%22%3Atrue%2C%22isMap%22%3Atrue%7D%09%09%09%09%09; AWSALB=gAlFj5Ngnd4bWP8k7CME/+YlTtX9bHK4yEkdPHa3VhL6K523oGyysFxBEpE1HNuuyL+GaRPvt2i/CSseAb+zEPpO4SNjnbLAJzJOOO01ipnWN3ZgPaa5qdv+fAki; AWSALBCORS=gAlFj5Ngnd4bWP8k7CME/+YlTtX9bHK4yEkdPHa3VhL6K523oGyysFxBEpE1HNuuyL+GaRPvt2i/CSseAb+zEPpO4SNjnbLAJzJOOO01ipnWN3ZgPaa5qdv+fAki; search=6|1697587741808%7Crect%3D33.37188814545521%2C-96.34484483007813%2C32.260490641365685%2C-97.21001816992188%26disp%3Dmap%26mdm%3Dauto%26p%3D1%26sort%3Ddays%26z%3D1%26listPriceActive%3D1%26fs%3D1%26fr%3D0%26mmm%3D0%26rs%3D0%26ah%3D0%26singlestory%3D0%26housing-connector%3D0%26abo%3D0%26garage%3D0%26pool%3D0%26ac%3D0%26waterfront%3D0%26finished%3D0%26unfinished%3D0%26cityview%3D0%26mountainview%3D0%26parkview%3D0%26waterview%3D0%26hoadata%3D1%26zillow-owned%3D0%263dhome%3D0%26featuredMultiFamilyBuilding%3D0%26commuteMode%3Ddriving%26commuteTimeOfDay%3Dnow%09%09%09%7B%22isList%22%3Atrue%2C%22isMap%22%3Atrue%7D%09%09%09%09%09',
-            "origin": "https://www.zillow.com",
-            "referer": "https://www.zillow.com",
-            "sec-ch-ua": '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
-            "sec-ch-ua-mobile": "?0",
-            "sec-ch-ua-platform": '"Windows"',
-            "sec-fetch-dest": "empty",
-            "sec-fetch-mode": "cors",
-            "sec-fetch-site": "same-origin",
-            "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36",
-        }

homeharvest/exceptions.py

@@ -1,14 +1,6 @@
-class InvalidSite(Exception):
-    """Raised when a provided site is does not exist."""
-
-
 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 GeoCoordsNotFound(Exception):
-    """Raised when no property is found for the given address"""

homeharvest/utils.py

@@ -1,38 +1,72 @@
-import re
+from .core.scrapers.models import Property, ListingType
+import pandas as pd
+from .exceptions import InvalidListingType
+
+ordered_properties = [
+    "property_url",
+    "mls",
+    "mls_id",
+    "status",
+    "style",
+    "street",
+    "unit",
+    "city",
+    "state",
+    "zip_code",
+    "beds",
+    "full_baths",
+    "half_baths",
+    "sqft",
+    "year_built",
+    "days_on_mls",
+    "list_price",
+    "list_date",
+    "sold_price",
+    "last_sold_date",
+    "lot_sqft",
+    "price_per_sqft",
+    "latitude",
+    "longitude",
+    "stories",
+    "hoa_fee",
+    "parking_garage",
+]
 
 
-def parse_address_one(street_address: str) -> tuple:
-    if not street_address:
-        return street_address, "#"
+def process_result(result: Property) -> pd.DataFrame:
+    prop_data = {prop: None for prop in ordered_properties}
+    prop_data.update(result.__dict__)
 
-    apt_match = re.search(
-        r"(APT\s*[\dA-Z]+|#[\dA-Z]+|UNIT\s*[\dA-Z]+|LOT\s*[\dA-Z]+|SUITE\s*[\dA-Z]+)$",
-        street_address,
-        re.I,
+    if "address" in prop_data:
+        address_data = prop_data["address"]
+        prop_data["street"] = address_data.street
+        prop_data["unit"] = address_data.unit
+        prop_data["city"] = address_data.city
+        prop_data["state"] = address_data.state
+        prop_data["zip_code"] = address_data.zip
+
+    prop_data["price_per_sqft"] = prop_data["prc_sqft"]
+
+    description = result.description
+    prop_data["style"] = description.style
+    prop_data["beds"] = description.beds
+    prop_data["full_baths"] = description.baths_full
+    prop_data["half_baths"] = description.baths_half
+    prop_data["sqft"] = description.sqft
+    prop_data["lot_sqft"] = description.lot_sqft
+    prop_data["sold_price"] = description.sold_price
+    prop_data["year_built"] = description.year_built
+    prop_data["parking_garage"] = description.garage
+    prop_data["stories"] = description.stories
+
+    properties_df = pd.DataFrame([prop_data])
+    properties_df = properties_df.reindex(columns=ordered_properties)
+
+    return properties_df[ordered_properties]
+
+
+def validate_input(listing_type: str) -> None:
+    if listing_type.upper() not in ListingType.__members__:
+        raise InvalidListingType(
+            f"Provided listing type, '{listing_type}', does not exist."
         )
-
-    if apt_match:
-        apt_str = apt_match.group().strip()
-        cleaned_apt_str = re.sub(r"(APT\s*|UNIT\s*|LOT\s*|SUITE\s*)", "#", apt_str, flags=re.I)
-
-        main_address = street_address.replace(apt_str, "").strip()
-        return main_address, cleaned_apt_str
-    else:
-        return street_address, "#"
-
-
-def parse_address_two(street_address: str):
-    if not street_address:
-        return "#"
-    apt_match = re.search(
-        r"(APT\s*[\dA-Z]+|#[\dA-Z]+|UNIT\s*[\dA-Z]+|LOT\s*[\dA-Z]+|SUITE\s*[\dA-Z]+)$",
-        street_address,
-        re.I,
-    )
-
-    if apt_match:
-        apt_str = apt_match.group().strip()
-        apt_str = re.sub(r"(APT\s*|UNIT\s*|LOT\s*|SUITE\s*)", "#", apt_str, flags=re.I)
-        return apt_str
-    else:
-        return "#"

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 = [
-    {file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c70087bfee18a42b4040bb9ec1ca15a08242cf5867c58726530bdf3945672ed"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b0dac0ff919ba34d4df1b6131f59ce95b08b9065233446be7e459f95554c0dc8"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
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-    {file = "charset_normalizer-3.2.0-cp310-cp310-win32.whl", hash = "sha256:04e57ab9fbf9607b77f7d057974694b4f6b142da9ed4a199859d9d4d5c63fe96"},
-    {file = "charset_normalizer-3.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:48021783bdf96e3d6de03a6e39a1171ed5bd7e8bb93fc84cc649d11490f87cea"},
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+    {file = "pandas-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dc3657869c7902810f32bd072f0740487f9e030c1a3ab03e0af093db35a9d14e"},
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+    {file = "pandas-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:29deb61de5a8a93bdd033df328441a79fcf8dd3c12d5ed0b41a395eef9cd76f0"},
+    {file = "pandas-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:4f99bebf19b7e03cf80a4e770a3e65eee9dd4e2679039f542d7c1ace7b7b1daa"},
+    {file = "pandas-2.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:84e7e910096416adec68075dc87b986ff202920fb8704e6d9c8c9897fe7332d6"},
+    {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-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc1ab6a25da197f03ebe6d8fa17273126120874386b4ac11c1d687df288542dd"},
+    {file = "pandas-2.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0dbfea0dd3901ad4ce2306575c54348d98499c95be01b8d885a2737fe4d7a98"},
+    {file = "pandas-2.1.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:0489b0e6aa3d907e909aef92975edae89b1ee1654db5eafb9be633b0124abe97"},
+    {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"
@@ -432,13 +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 = "urllib3-2.0.4.tar.gz", hash = "sha256:8d22f86aae8ef5e410d4f539fde9ce6b2113a001bb4d189e0aed70642d602b11"},
+    {file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"},
+    {file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"},
 ]
 
 [package.extras]
@@ -449,5 +437,5 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.10"
-content-hash = "3647d568f5623dd762f19029230626a62e68309fa2ef8be49a36382c19264a5f"
+python-versions = ">=3.10,<3.13"
+content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"

pyproject.toml

@@ -1,18 +1,18 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.2.8"
+version = "0.3.6"
 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"
+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"
 
 

tests/test_realtor.py

@@ -1,26 +1,108 @@
 from homeharvest import scrape_property
 from homeharvest.exceptions import (
-    InvalidSite,
     InvalidListingType,
     NoResultsFound,
-    GeoCoordsNotFound,
 )
 
 
+def test_realtor_pending_or_contingent():
+    pending_or_contingent_result = scrape_property(
+        location="Surprise, AZ", listing_type="pending"
+    )
+
+    regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
+
+    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_comps():
+    result = scrape_property(
+        location="2530 Al Lipscomb Way",
+        radius=0.5,
+        past_days=180,
+        listing_type="sold",
+    )
+
+    assert result is not None and len(result) > 0
+
+
+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_single_property():
+    results = [
+        scrape_property(
+            location="15509 N 172nd Dr, Surprise, AZ 85388",
+            listing_type="for_sale",
+        ),
+        scrape_property(
+            location="2530 Al Lipscomb Way",
+            listing_type="for_sale",
+        ),
+    ]
+
+    assert all([result is not None for result in results])
+
+
 def test_realtor():
     results = [
         scrape_property(
             location="2530 Al Lipscomb Way",
-            site_name="realtor.com",
             listing_type="for_sale",
         ),
         scrape_property(
-            location="Phoenix, AZ", site_name=["realtor.com"], listing_type="for_rent"
+            location="Phoenix, AZ", listing_type="for_rent"
         ),  #: does not support "city, state, USA" format
         scrape_property(
-            location="Dallas, TX", site_name="realtor.com", listing_type="sold"
+            location="Dallas, TX", listing_type="sold"
         ),  #: does not support "city, state, USA" format
-        scrape_property(location="85281", site_name="realtor.com"),
+        scrape_property(location="85281"),
     ]
 
     assert all([result is not None for result in results])
@@ -30,11 +112,10 @@ def test_realtor():
         bad_results += [
             scrape_property(
                 location="abceefg ju098ot498hh9",
-                site_name="realtor.com",
                 listing_type="for_sale",
             )
         ]
-    except (InvalidSite, InvalidListingType, NoResultsFound, GeoCoordsNotFound):
+    except (InvalidListingType, NoResultsFound):
         assert True
 
     assert all([result is None for result in bad_results])

tests/test_redfin.py

@@ -1,32 +0,0 @@
-from homeharvest import scrape_property
-from homeharvest.exceptions import (
-    InvalidSite,
-    InvalidListingType,
-    NoResultsFound,
-    GeoCoordsNotFound,
-)
-
-
-def test_redfin():
-    results = [
-        scrape_property(location="2530 Al Lipscomb Way", site_name="redfin", listing_type="for_sale"),
-        scrape_property(location="Phoenix, AZ, USA", site_name=["redfin"], listing_type="for_rent"),
-        scrape_property(location="Dallas, TX, USA", site_name="redfin", listing_type="sold"),
-        scrape_property(location="85281", site_name="redfin"),
-    ]
-
-    assert all([result is not None for result in results])
-
-    bad_results = []
-    try:
-        bad_results += [
-            scrape_property(
-                location="abceefg ju098ot498hh9",
-                site_name="redfin",
-                listing_type="for_sale",
-            )
-        ]
-    except (InvalidSite, InvalidListingType, NoResultsFound, GeoCoordsNotFound):
-        assert True
-
-    assert all([result is None for result in bad_results])

tests/test_utils.py

@@ -1,24 +0,0 @@
-from homeharvest.utils import parse_address_one, parse_address_two
-
-
-def test_parse_address_one():
-    test_data = [
-        ("4303 E Cactus Rd Apt 126", ("4303 E Cactus Rd", "#126")),
-        ("1234 Elm Street apt 2B", ("1234 Elm Street", "#2B")),
-        ("1234 Elm Street UNIT 3A", ("1234 Elm Street", "#3A")),
-        ("1234 Elm Street unit 3A", ("1234 Elm Street", "#3A")),
-        ("1234 Elm Street SuIte 3A", ("1234 Elm Street", "#3A")),
-    ]
-
-    for input_data, (exp_addr_one, exp_addr_two) in test_data:
-        address_one, address_two = parse_address_one(input_data)
-        assert address_one == exp_addr_one
-        assert address_two == exp_addr_two
-
-
-def test_parse_address_two():
-    test_data = [("Apt 126", "#126"), ("apt 2B", "#2B"), ("UNIT 3A", "#3A"), ("unit 3A", "#3A"), ("SuIte 3A", "#3A")]
-
-    for input_data, expected in test_data:
-        output = parse_address_two(input_data)
-        assert output == expected

tests/test_zillow.py

@@ -1,32 +0,0 @@
-from homeharvest import scrape_property
-from homeharvest.exceptions import (
-    InvalidSite,
-    InvalidListingType,
-    NoResultsFound,
-    GeoCoordsNotFound,
-)
-
-
-def test_zillow():
-    results = [
-        scrape_property(location="2530 Al Lipscomb Way", site_name="zillow", listing_type="for_sale"),
-        scrape_property(location="Phoenix, AZ, USA", site_name=["zillow"], listing_type="for_rent"),
-        scrape_property(location="Dallas, TX, USA", site_name="zillow", listing_type="sold"),
-        scrape_property(location="85281", site_name="zillow"),
-    ]
-
-    assert all([result is not None for result in results])
-
-    bad_results = []
-    try:
-        bad_results += [
-            scrape_property(
-                location="abceefg ju098ot498hh9",
-                site_name="zillow",
-                listing_type="for_sale",
-            )
-        ]
-    except (InvalidSite, InvalidListingType, NoResultsFound, GeoCoordsNotFound):
-        assert True
-
-    assert all([result is None for result in bad_results])