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...

12 Commits

Author SHA1 Message Date
Zachary Hampton
3f44744d61 - primary photo bug fix
- limit parameter
2024-07-15 07:19:57 -07:00
Zachary Hampton
ac0cad62a7 - optimizations 2024-06-14 21:50:23 -07:00
Cullen Watson
beb885cc8d fix: govt type (#82) 2024-06-12 17:34:34 -05:00
Zachary Hampton
011680f7d8 - style error bug fix 2024-06-06 15:24:12 -07:00
Zachary Hampton
93e6778a48 - exclude_pending parameter 2024-05-31 22:17:29 -07:00
Zachary Hampton
ec036bb989 - optimizations & updated realtor headers 2024-05-20 12:13:30 -07:00
Zachary Hampton
aacd168545 - alt photos bug fix 2024-05-18 17:47:55 -07:00
Zachary Hampton
0d70007000 - alt photos bug fix 2024-05-16 23:04:07 -07:00
Zachary Hampton
018d3fbac4 - Python 3.9 support (tested) (could potentially work for lower versions, but I have not validated such) 2024-05-14 19:13:04 -07:00
Zachary Hampton
803fd618e9 - data cleaning & CONDOP bug fixes 2024-05-12 21:12:12 -07:00
Zachary Hampton
b23b55ca80 - full street line (data quality improvement) 2024-05-12 18:49:44 -07:00
Zachary Hampton
3458a08383 - broker data 2024-05-11 21:35:29 -07:00
9 changed files with 346 additions and 95 deletions

View File

@@ -21,7 +21,7 @@
```bash
pip install -U homeharvest
```
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
_Python version >= [3.9](https://www.python.org/downloads/release/python-3100/) required_
## Usage
@@ -90,9 +90,13 @@ Optional
├── foreclosure (True/False): If set, fetches only foreclosures
── proxy (string): In format 'http://user:pass@host:port'
── proxy (string): In format 'http://user:pass@host:port'
── extra_property_data (bool): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
── extra_property_data (True/False): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
├── exclude_pending (True/False): If set, excludes pending properties from the results unless listing_type is 'pending'
└── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
```
### Property Schema
@@ -142,6 +146,11 @@ Property
│ ├── agent
│ ├── agent_email
│ └── agent_phone
├── Broker Info:
│ ├── broker
│ ├── broker_email
│ └── broker_website
```
### Exceptions

View File

@@ -1,7 +1,7 @@
import warnings
import pandas as pd
from .core.scrapers import ScraperInput
from .utils import process_result, ordered_properties, validate_input, validate_dates
from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit
from .core.scrapers.realtor import RealtorScraper
from .core.scrapers.models import ListingType
@@ -17,11 +17,13 @@ def scrape_property(
date_to: str = None,
foreclosure: bool = None,
extra_property_data: bool = True,
exclude_pending: bool = False,
limit: int = 10000,
) -> pd.DataFrame:
"""
Scrape properties from Realtor.com based on a given location and listing type.
:param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
:param listing_type: Listing Type (for_sale, for_rent, sold)
:param listing_type: Listing Type (for_sale, for_rent, sold, pending)
:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
:param mls_only: If set, fetches only listings with MLS IDs.
:param proxy: Proxy to use for scraping
@@ -29,9 +31,12 @@ def scrape_property(
:param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
:param foreclosure: If set, fetches only foreclosure listings.
:param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
:param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
:param limit: Limit the number of results returned. Maximum is 10,000.
"""
validate_input(listing_type)
validate_dates(date_from, date_to)
validate_limit(limit)
scraper_input = ScraperInput(
location=location,
@@ -44,16 +49,18 @@ def scrape_property(
date_to=date_to,
foreclosure=foreclosure,
extra_property_data=extra_property_data,
exclude_pending=exclude_pending,
limit=limit,
)
site = RealtorScraper(scraper_input)
results = site.search()
properties_dfs = [process_result(result) for result in results]
properties_dfs = [df for result in results if not (df := process_result(result)).empty]
if not properties_dfs:
return pd.DataFrame()
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=FutureWarning)
return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace({"None": "", None: ""})
return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace({"None": pd.NA, None: pd.NA, "": pd.NA})

View File

@@ -1,3 +1,4 @@
from __future__ import annotations
from dataclasses import dataclass
import requests
from requests.adapters import HTTPAdapter
@@ -5,6 +6,7 @@ from urllib3.util.retry import Retry
import uuid
from ...exceptions import AuthenticationError
from .models import Property, ListingType, SiteName
import json
@dataclass
@@ -19,6 +21,8 @@ class ScraperInput:
date_to: str | None = None
foreclosure: bool | None = False
extra_property_data: bool | None = True
exclude_pending: bool | None = False
limit: int = 10000
class Scraper:
@@ -60,6 +64,8 @@ class Scraper:
self.date_to = scraper_input.date_to
self.foreclosure = scraper_input.foreclosure
self.extra_property_data = scraper_input.extra_property_data
self.exclude_pending = scraper_input.exclude_pending
self.limit = scraper_input.limit
def search(self) -> list[Property]: ...
@@ -70,18 +76,25 @@ class Scraper:
@staticmethod
def get_access_token():
url = "https://graph.realtor.com/auth/token"
device_id = str(uuid.uuid4()).upper()
payload = f'{{"client_app_id":"rdc_mobile_native,24.20.4.149916,iphone","device_id":"{str(uuid.uuid4()).upper()}","grant_type":"device_mobile"}}'
headers = {
"Host": "graph.realtor.com",
"x-client-version": "24.20.4.149916",
"accept": "*/*",
"content-type": "Application/json",
"user-agent": "Realtor.com/24.20.4.149916 CFNetwork/1410.0.3 Darwin/22.6.0",
"accept-language": "en-US,en;q=0.9",
}
response = requests.post(url, headers=headers, data=payload)
response = requests.post(
"https://graph.realtor.com/auth/token",
headers={
'Host': 'graph.realtor.com',
'Accept': '*/*',
'Content-Type': 'Application/json',
'X-Client-ID': 'rdc_mobile_native,iphone',
'X-Visitor-ID': device_id,
'X-Client-Version': '24.21.23.679885',
'Accept-Language': 'en-US,en;q=0.9',
'User-Agent': 'Realtor.com/24.21.23.679885 CFNetwork/1494.0.7 Darwin/23.4.0',
},
data=json.dumps({
"grant_type": "device_mobile",
"device_id": device_id,
"client_app_id": "rdc_mobile_native,24.21.23.679885,iphone"
}))
data = response.json()

View File

@@ -1,3 +1,4 @@
from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from typing import Optional
@@ -33,9 +34,12 @@ class PropertyType(Enum):
APARTMENT = "APARTMENT"
BUILDING = "BUILDING"
COMMERCIAL = "COMMERCIAL"
GOVERNMENT = "GOVERNMENT"
INDUSTRIAL = "INDUSTRIAL"
CONDO_TOWNHOME = "CONDO_TOWNHOME"
CONDO_TOWNHOME_ROWHOME_COOP = "CONDO_TOWNHOME_ROWHOME_COOP"
CONDO = "CONDO"
CONDOP = "CONDOP"
CONDOS = "CONDOS"
COOP = "COOP"
DUPLEX_TRIPLEX = "DUPLEX_TRIPLEX"
@@ -52,6 +56,7 @@ class PropertyType(Enum):
@dataclass
class Address:
full_line: str | None = None
street: str | None = None
unit: str | None = None
city: str | None = None
@@ -121,7 +126,8 @@ class Property:
neighborhoods: Optional[str] = None
county: Optional[str] = None
fips_code: Optional[str] = None
agents: list[Agent] = None
agents: list[Agent] | None = None
brokers: list[Broker] | None = None
nearby_schools: list[str] = None
assessed_value: int | None = None
estimated_value: int | None = None

View File

@@ -5,12 +5,13 @@ homeharvest.realtor.__init__
This module implements the scraper for realtor.com
"""
from __future__ import annotations
from concurrent.futures import ThreadPoolExecutor, as_completed
from datetime import datetime
from typing import Dict, Union, Optional
from .. import Scraper
from ..models import Property, Address, ListingType, Description, PropertyType, Agent
from ..models import Property, Address, ListingType, Description, PropertyType, Agent, Broker
class RealtorScraper(Scraper):
@@ -52,6 +53,7 @@ class RealtorScraper(Scraper):
listing_id
}
address {
line
street_direction
street_number
street_name
@@ -113,10 +115,10 @@ class RealtorScraper(Scraper):
)
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")
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
@@ -143,6 +145,7 @@ class RealtorScraper(Scraper):
property_id = property_info["details"]["permalink"]
prop_details = self.get_prop_details(property_id)
style = property_info["basic"].get("type", "").upper()
listing = Property(
mls=mls,
mls_id=(
@@ -165,8 +168,12 @@ class RealtorScraper(Scraper):
longitude=property_info["address"]["location"]["coordinate"].get("lon") if able_to_get_lat_long else None,
address=self._parse_address(property_info, search_type="handle_listing"),
description=Description(
alt_photos=self.process_alt_photos(property_info.get("media", {}).get("photos", [])),
style=property_info["basic"].get("type", "").upper(),
alt_photos=(
self.process_alt_photos(property_info["media"].get("photos", []))
if property_info.get("media")
else None
),
style=PropertyType.__getitem__(style) if style and style in PropertyType.__members__ else None,
beds=property_info["basic"].get("beds"),
baths_full=property_info["basic"].get("baths_full"),
baths_half=property_info["basic"].get("baths_half"),
@@ -180,6 +187,7 @@ class RealtorScraper(Scraper):
),
days_on_mls=days_on_mls,
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
@@ -235,6 +243,7 @@ class RealtorScraper(Scraper):
stories
}
address {
line
street_direction
street_number
street_name
@@ -295,6 +304,7 @@ class RealtorScraper(Scraper):
address=self._parse_address(property_info, search_type="handle_address"),
description=self._parse_description(property_info),
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
@@ -350,6 +360,7 @@ class RealtorScraper(Scraper):
street_number
street_name
street_suffix
line
unit
city
state_code
@@ -470,7 +481,7 @@ class RealtorScraper(Scraper):
)
else: #: general search, came from an address
query = (
"""query Property_search(
"""query Property_search(
$property_id: [ID]!
$offset: Int!,
) {
@@ -481,7 +492,7 @@ class RealtorScraper(Scraper):
limit: 1
offset: $offset
) %s"""
% results_query
% results_query
)
payload = {
@@ -496,12 +507,12 @@ class RealtorScraper(Scraper):
properties: list[Property] = []
if (
response_json is None
or "data" not in response_json
or response_json["data"] is None
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]
response_json is None
or "data" not in response_json
or response_json["data"] is None
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 {"total": 0, "properties": []}
@@ -512,19 +523,19 @@ class RealtorScraper(Scraper):
return
able_to_get_lat_long = (
result
and result.get("location")
and result["location"].get("address")
and result["location"]["address"].get("coordinate")
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")
if is_pending and self.listing_type != ListingType.PENDING:
if is_pending and (self.exclude_pending and self.listing_type != ListingType.PENDING):
return
property_id = result["property_id"]
prop_details = self.get_prop_details(property_id)
prop_details = self.get_prop_details(property_id) if self.extra_property_data else {}
realty_property = Property(
mls=mls,
@@ -553,6 +564,7 @@ class RealtorScraper(Scraper):
fips_code=result["location"]["county"].get("fips_code") if result["location"]["county"] else None,
days_on_mls=self.calculate_days_on_mls(result),
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
@@ -635,14 +647,14 @@ class RealtorScraper(Scraper):
total = result["total"]
homes = result["properties"]
with ThreadPoolExecutor(max_workers=10) as executor:
with ThreadPoolExecutor() as executor:
futures = [
executor.submit(
self.general_search,
variables=search_variables | {"offset": i},
search_type=search_type,
)
for i in range(200, min(total, 10000), 200)
for i in range(200, min(total, self.limit), 200)
]
for future in as_completed(futures):
@@ -654,10 +666,12 @@ class RealtorScraper(Scraper):
if not self.extra_property_data:
return {}
#: TODO: migrate "advertisers" and "estimates" to general query
query = """query GetHome($property_id: ID!) {
home(property_id: $property_id) {
__typename
advertisers {
__typename
type
@@ -665,23 +679,29 @@ class RealtorScraper(Scraper):
email
phones { number type ext primary }
}
nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {
__typename schools { district { __typename id name } }
}
consumer_advertisers {
name
phone
href
type
}
nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {
__typename schools { district { __typename id name } }
}
taxHistory: tax_history { __typename tax year assessment { __typename building land total } }
estimates {
__typename
currentValues: current_values {
estimates {
__typename
currentValues: current_values {
__typename
source { __typename type name }
estimate
source { __typename type name }
estimate
estimateHigh: estimate_high
estimateLow: estimate_low
date
isBestHomeValue: isbest_homevalue
}
estimateLow: estimate_low
date
isBestHomeValue: isbest_homevalue
}
}
}
}"""
@@ -700,20 +720,25 @@ class RealtorScraper(Scraper):
except (KeyError, TypeError, IndexError):
return {}
ads = get_key(["data", "home", "advertisers"])
agents = get_key(["data", "home", "advertisers"])
advertisers = get_key(["data", "home", "consumer_advertisers"])
schools = get_key(["data", "home", "nearbySchools", "schools"])
assessed_value = get_key(["data", "home", "taxHistory", 0, "assessment", "total"])
estimated_value = get_key(["data", "home", "estimates", "currentValues", 0, "estimate"])
agents = [Agent(
name=ad["name"],
email=ad["email"],
phones=ad["phones"]
) for ad in ads]
agents = [Agent(name=ad["name"], email=ad["email"], phones=ad["phones"]) for ad in agents]
schools = [school["district"]["name"] for school in schools if school['district'].get('name')]
brokers = [
Broker(name=ad["name"], phone=ad["phone"], website=ad["href"])
for ad in advertisers
if ad.get("type") != "Agent"
]
schools = [school["district"]["name"] for school in schools if school["district"].get("name")]
return {
"agents": agents if agents else None,
"brokers": brokers if brokers else None,
"schools": schools if schools else None,
"assessed_value": assessed_value if assessed_value else None,
"estimated_value": estimated_value if estimated_value else None,
@@ -747,13 +772,16 @@ class RealtorScraper(Scraper):
address = result["address"]
return Address(
full_line=address.get("line"),
street=" ".join(
part for part in [
part
for part in [
address.get("street_number"),
address.get("street_direction"),
address.get("street_name"),
address.get("street_suffix"),
] if part is not None
]
if part is not None
).strip(),
unit=address["unit"],
city=address["city"],
@@ -762,7 +790,10 @@ class RealtorScraper(Scraper):
)
@staticmethod
def _parse_description(result: dict) -> Description:
def _parse_description(result: dict) -> Description | None:
if not result:
return None
description_data = result.get("description", {})
if description_data is None or not isinstance(description_data, dict):
@@ -773,22 +804,23 @@ class RealtorScraper(Scraper):
style = style.upper()
primary_photo = ""
if result and "primary_photo" in result:
primary_photo_info = result["primary_photo"]
if primary_photo_info and "href" in primary_photo_info:
primary_photo_href = primary_photo_info["href"]
primary_photo = primary_photo_href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
if (primary_photo_info := result.get('primary_photo')) and (primary_photo_href := primary_photo_info.get("href")):
primary_photo = primary_photo_href.replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
return Description(
primary_photo=primary_photo,
alt_photos=RealtorScraper.process_alt_photos(result.get("photos")),
style=PropertyType(style) if style else None,
alt_photos=RealtorScraper.process_alt_photos(result.get("photos", [])),
style=PropertyType.__getitem__(style) if style and style in PropertyType.__members__ else None,
beds=description_data.get("beds"),
baths_full=description_data.get("baths_full"),
baths_half=description_data.get("baths_half"),
sqft=description_data.get("sqft"),
lot_sqft=description_data.get("lot_sqft"),
sold_price=description_data.get("sold_price") if result.get('last_sold_date') or result["list_price"] != description_data.get("sold_price") else None, #: has a sold date or list and sold price are different
sold_price=(
description_data.get("sold_price")
if result.get("last_sold_date") or result["list_price"] != description_data.get("sold_price")
else None
), #: has a sold date or list and sold price are different
year_built=description_data.get("year_built"),
garage=description_data.get("garage"),
stories=description_data.get("stories"),

View File

@@ -1,3 +1,4 @@
from __future__ import annotations
import pandas as pd
from datetime import datetime
from .core.scrapers.models import Property, ListingType, Agent
@@ -10,6 +11,7 @@ ordered_properties = [
"status",
"text",
"style",
"full_street_line",
"street",
"unit",
"city",
@@ -40,6 +42,9 @@ ordered_properties = [
"agent",
"agent_email",
"agent_phones",
"broker",
"broker_phone",
"broker_website",
"nearby_schools",
"primary_photo",
"alt_photos",
@@ -52,6 +57,7 @@ def process_result(result: Property) -> pd.DataFrame:
if "address" in prop_data:
address_data = prop_data["address"]
prop_data["full_street_line"] = address_data.full_line
prop_data["street"] = address_data.street
prop_data["unit"] = address_data.unit
prop_data["city"] = address_data.city
@@ -65,24 +71,33 @@ def process_result(result: Property) -> pd.DataFrame:
prop_data["agent_email"] = agents[0].email
prop_data["agent_phones"] = agents[0].phones
if "brokers" in prop_data:
brokers = prop_data["brokers"]
if brokers:
prop_data["broker"] = brokers[0].name
prop_data["broker_phone"] = brokers[0].phone
prop_data["broker_website"] = brokers[0].website
prop_data["price_per_sqft"] = prop_data["prc_sqft"]
prop_data["nearby_schools"] = filter(None, prop_data["nearby_schools"]) if prop_data["nearby_schools"] else None
prop_data["nearby_schools"] = ", ".join(set(prop_data["nearby_schools"])) if prop_data["nearby_schools"] else None
description = result.description
prop_data["primary_photo"] = description.primary_photo
prop_data["alt_photos"] = ", ".join(description.alt_photos)
prop_data["style"] = description.style if type(description.style) == str else description.style.value
prop_data["beds"] = description.beds
prop_data["full_baths"] = description.baths_full
prop_data["half_baths"] = description.baths_half
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
prop_data["text"] = description.text
if description:
prop_data["primary_photo"] = description.primary_photo
prop_data["alt_photos"] = ", ".join(description.alt_photos) if description.alt_photos else None
prop_data["style"] = description.style if isinstance(description.style,
str) else description.style.value if description.style else None
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
prop_data["text"] = description.text
properties_df = pd.DataFrame([prop_data])
properties_df = properties_df.reindex(columns=ordered_properties)
@@ -96,7 +111,7 @@ def validate_input(listing_type: str) -> None:
def validate_dates(date_from: str | None, date_to: str | None) -> None:
if (date_from is not None and date_to is None) or (date_from is None and date_to is not None):
if isinstance(date_from, str) != isinstance(date_to, str):
raise InvalidDate("Both date_from and date_to must be provided.")
if date_from and date_to:
@@ -108,3 +123,10 @@ def validate_dates(date_from: str | None, date_to: str | None) -> None:
raise InvalidDate("date_to must be after date_from.")
except ValueError:
raise InvalidDate(f"Invalid date format or range")
def validate_limit(limit: int) -> None:
#: 1 -> 10000 limit
if limit is not None and (limit < 1 or limit > 10000):
raise ValueError("Property limit must be between 1 and 10,000.")

136
poetry.lock generated
View File

@@ -1,5 +1,16 @@
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "annotated-types"
version = "0.7.0"
description = "Reusable constraint types to use with typing.Annotated"
optional = false
python-versions = ">=3.8"
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View File

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description = "Real estate scraping library"
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
homepage = "https://github.com/Bunsly/HomeHarvest"
@@ -10,9 +10,10 @@ readme = "README.md"
homeharvest = "homeharvest.cli:main"
[tool.poetry.dependencies]
python = ">=3.10,<3.13"
python = ">=3.9,<3.13"
requests = "^2.31.0"
pandas = "^2.1.1"
pydantic = "^2.7.4"
[tool.poetry.group.dev.dependencies]

View File

@@ -4,7 +4,7 @@ from homeharvest import scrape_property
def test_realtor_pending_or_contingent():
pending_or_contingent_result = scrape_property(location="Surprise, AZ", listing_type="pending")
regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale", exclude_pending=True)
assert all([result is not None for result in [pending_or_contingent_result, regular_result]])
assert len(pending_or_contingent_result) != len(regular_result)
@@ -155,4 +155,33 @@ def test_realtor_without_extra_details():
),
]
assert results[0] != results[1]
assert not results[0].equals(results[1])
def test_pr_zip_code():
results = scrape_property(
location="00741",
listing_type="for_sale",
)
assert results is not None and len(results) > 0
def test_exclude_pending():
results = scrape_property(
location="33567",
listing_type="pending",
exclude_pending=True,
)
assert results is not None and len(results) > 0
def test_style_value_error():
results = scrape_property(
location="Alaska, AK",
listing_type="sold",
extra_property_data=False,
)
assert results is not None and len(results) > 0