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21 Commits

Author SHA1 Message Date
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
Zachary Hampton
c3e24a4ce0 - extra_property_details parameter
- updated docs
- classified exception
2024-05-02 09:04:49 -07:00
Zachary Hampton
46985dcee4 - various data quality fixes (including #70) 2024-05-02 08:48:53 -07:00
Cullen Watson
04ae968716 enh: assessed/estimated value (#77) 2024-04-30 15:29:54 -05:00
Cullen
c5b15e9be5 chore: version 2024-04-20 17:45:29 -05:00
joecryptotoo
7a525caeb8 added county, fips, and text desciption fields (#72) 2024-04-20 17:44:28 -05:00
Cullen Watson
7246703999 Schools (#69) 2024-04-16 20:01:20 -05:00
Cullen Watson
6076b0f961 enh: add agent (#68) 2024-04-16 15:09:32 -05:00
Cullen Watson
cdc6f2a2a8 docs: readme 2024-04-16 14:59:50 -05:00
Cullen Watson
0bdf56568e enh: add agent name/phone (#66) 2024-04-16 14:55:44 -05:00
Cullen Watson
1f47fc3b7e fix: use enum value (#65) 2024-04-12 01:41:15 -05:00
14 changed files with 855 additions and 223 deletions

21
.pre-commit-config.yaml Normal file
View File

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

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
@@ -43,7 +43,6 @@ properties = scrape_property(
# date_from="2023-05-01", # alternative to past_days
# date_to="2023-05-28",
# foreclosure=True
# mls_only=True, # only fetch MLS listings
)
print(f"Number of properties: {len(properties)}")
@@ -91,7 +90,11 @@ 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 (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'
```
### Property Schema
@@ -128,19 +131,29 @@ Property
│ ├── sold_price
│ ├── last_sold_date
│ ├── price_per_sqft
│ ├── parking_garage
│ └── hoa_fee
├── Location Details:
│ ├── latitude
│ ├── longitude
│ ├── nearby_schools
└── Parking Details:
└── parking_garage
├── Agent Info:
│ ├── agent
│ ├── agent_email
│ └── agent_phone
├── Broker Info:
│ ├── broker
│ ├── broker_email
│ └── broker_website
```
### Exceptions
The following exceptions may be raised when using HomeHarvest:
- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD.
- `AuthenticationError` - Realtor.com token request failed.

View File

@@ -13,19 +13,24 @@ def scrape_property(
mls_only: bool = False,
past_days: int = None,
proxy: str = None,
date_from: str = None,
date_from: str = None, #: TODO: Switch to one parameter, Date, with date_from and date_to, pydantic validation
date_to: str = None,
foreclosure: bool = None,
extra_property_data: bool = True,
exclude_pending: bool = False,
) -> pd.DataFrame:
"""
Scrape properties from Realtor.com based on a given location and listing type.
:param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
:param listing_type: Listing Type (for_sale, for_rent, sold)
:param listing_type: Listing Type (for_sale, for_rent, sold, pending)
:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
:param mls_only: If set, fetches only listings with MLS IDs.
:param proxy: Proxy to use for scraping
:param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
:param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
:param proxy: Proxy to use for scraping
:param foreclosure: If set, fetches only foreclosure listings.
:param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
:param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
"""
validate_input(listing_type)
validate_dates(date_from, date_to)
@@ -40,15 +45,18 @@ def scrape_property(
date_from=date_from,
date_to=date_to,
foreclosure=foreclosure,
extra_property_data=extra_property_data,
exclude_pending=exclude_pending,
)
site = RealtorScraper(scraper_input)
results = site.search()
properties_dfs = [process_result(result) for result in results]
properties_dfs = [df for result in results if not (df := process_result(result)).empty]
if not properties_dfs:
return pd.DataFrame()
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=FutureWarning)
return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties]
return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace({"None": pd.NA, None: pd.NA, "": pd.NA})

View File

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

View File

@@ -1,6 +1,12 @@
from __future__ import annotations
from dataclasses import dataclass
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
import uuid
from ...exceptions import AuthenticationError
from .models import Property, ListingType, SiteName
import json
@dataclass
@@ -8,27 +14,41 @@ class ScraperInput:
location: str
listing_type: ListingType
radius: float | None = None
mls_only: bool | None = None
mls_only: bool | None = False
proxy: str | None = None
last_x_days: int | None = None
date_from: str | None = None
date_to: str | None = None
foreclosure: bool | None = None
foreclosure: bool | None = False
extra_property_data: bool | None = True
exclude_pending: bool | None = False
class Scraper:
session = None
def __init__(
self,
scraper_input: ScraperInput,
session: requests.Session = None,
):
self.location = scraper_input.location
self.listing_type = scraper_input.listing_type
if not session:
self.session = requests.Session()
else:
self.session = session
if not self.session:
Scraper.session = requests.Session()
retries = Retry(
total=3, backoff_factor=3, status_forcelist=[429, 403], allowed_methods=frozenset(["GET", "POST"])
)
adapter = HTTPAdapter(max_retries=retries)
Scraper.session.mount("http://", adapter)
Scraper.session.mount("https://", adapter)
Scraper.session.headers.update(
{
"auth": f"Bearer {self.get_access_token()}",
"apollographql-client-name": "com.move.Realtor-apollo-ios",
}
)
if scraper_input.proxy:
proxy_url = scraper_input.proxy
@@ -42,13 +62,44 @@ class Scraper:
self.date_from = scraper_input.date_from
self.date_to = scraper_input.date_to
self.foreclosure = scraper_input.foreclosure
self.extra_property_data = scraper_input.extra_property_data
self.exclude_pending = scraper_input.exclude_pending
def search(self) -> list[Property]:
...
def search(self) -> list[Property]: ...
@staticmethod
def _parse_home(home) -> Property:
...
def _parse_home(home) -> Property: ...
def handle_location(self):
...
def handle_location(self): ...
@staticmethod
def get_access_token():
device_id = str(uuid.uuid4()).upper()
response = requests.post(
"https://graph.realtor.com/auth/token",
headers={
'Host': 'graph.realtor.com',
'Accept': '*/*',
'Content-Type': 'Application/json',
'X-Client-ID': 'rdc_mobile_native,iphone',
'X-Visitor-ID': device_id,
'X-Client-Version': '24.21.23.679885',
'Accept-Language': 'en-US,en;q=0.9',
'User-Agent': 'Realtor.com/24.21.23.679885 CFNetwork/1494.0.7 Darwin/23.4.0',
},
data=json.dumps({
"grant_type": "device_mobile",
"device_id": device_id,
"client_app_id": "rdc_mobile_native,24.21.23.679885,iphone"
}))
data = response.json()
if not (access_token := data.get("access_token")):
raise AuthenticationError(
"Failed to get access token, use a proxy/vpn or wait a moment and try again.",
response=response
)
return access_token

View File

@@ -1,3 +1,4 @@
from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from typing import Optional
@@ -23,13 +24,22 @@ class ListingType(Enum):
SOLD = "SOLD"
@dataclass
class Agent:
name: str | None = None
phone: str | None = None
class PropertyType(Enum):
APARTMENT = "APARTMENT"
BUILDING = "BUILDING"
COMMERCIAL = "COMMERCIAL"
GOVERNMENT = "GOVERNMENT"
INDUSTRIAL = "INDUSTRIAL"
CONDO_TOWNHOME = "CONDO_TOWNHOME"
CONDO_TOWNHOME_ROWHOME_COOP = "CONDO_TOWNHOME_ROWHOME_COOP"
CONDO = "CONDO"
CONDOP = "CONDOP"
CONDOS = "CONDOS"
COOP = "COOP"
DUPLEX_TRIPLEX = "DUPLEX_TRIPLEX"
@@ -46,6 +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
@@ -67,6 +78,30 @@ class Description:
year_built: int | None = None
garage: float | None = None
stories: int | None = None
text: str | None = None
@dataclass
class AgentPhone: #: For documentation purposes only (at the moment)
number: str | None = None
type: str | None = None
primary: bool | None = None
ext: str | None = None
@dataclass
class Agent:
name: str | None = None
phones: list[dict] | AgentPhone | None = None
email: str | None = None
href: str | None = None
@dataclass
class Broker:
name: str | None = None
phone: str | None = None
website: str | None = None
@dataclass
@@ -89,3 +124,10 @@ class Property:
latitude: float | None = None
longitude: float | None = None
neighborhoods: Optional[str] = None
county: Optional[str] = None
fips_code: Optional[str] = None
agents: list[Agent] | None = None
brokers: list[Broker] | None = None
nearby_schools: list[str] = None
assessed_value: int | None = None
estimated_value: int | None = None

View File

@@ -4,18 +4,22 @@ homeharvest.realtor.__init__
This module implements the scraper for realtor.com
"""
from __future__ import annotations
from concurrent.futures import ThreadPoolExecutor, as_completed
from datetime import datetime
from typing import Dict, Union, Optional
from concurrent.futures import ThreadPoolExecutor, as_completed
from .. import Scraper
from ..models import Property, Address, ListingType, Description, PropertyType
from ..models import Property, Address, ListingType, Description, PropertyType, Agent, Broker
class RealtorScraper(Scraper):
SEARCH_GQL_URL = "https://www.realtor.com/api/v1/rdc_search_srp?client_id=rdc-search-new-communities&schema=vesta"
PROPERTY_URL = "https://www.realtor.com/realestateandhomes-detail/"
PROPERTY_GQL = "https://graph.realtor.com/graphql"
ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
NUM_PROPERTY_WORKERS = 20
def __init__(self, scraper_input):
super().__init__(scraper_input)
@@ -49,6 +53,7 @@ class RealtorScraper(Scraper):
listing_id
}
address {
line
street_direction
street_number
street_name
@@ -110,15 +115,17 @@ 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
)
last_sold_date_str = (
property_info["basic"]["sold_date"].split("T")[0] if property_info["basic"].get("sold_date") else None
)
list_date_str = property_info["basic"]["list_date"].split("T")[0] if property_info["basic"].get(
"list_date") else None
last_sold_date_str = property_info["basic"]["sold_date"].split("T")[0] if property_info["basic"].get(
"sold_date") else None
pending_date_str = property_info["pending_date"].split("T")[0] if property_info.get("pending_date") else None
list_date = datetime.strptime(list_date_str, "%Y-%m-%d") if list_date_str else None
@@ -131,37 +138,42 @@ class RealtorScraper(Scraper):
if list_date:
if status == "sold" and last_sold_date:
days_on_mls = (last_sold_date - list_date).days
elif status in ('for_sale', 'for_rent'):
elif status in ("for_sale", "for_rent"):
days_on_mls = (today - list_date).days
if days_on_mls and days_on_mls < 0:
days_on_mls = None
property_id = property_info["details"]["permalink"]
prop_details = self.get_prop_details(property_id)
style = property_info["basic"].get("type", "").upper()
listing = Property(
mls=mls,
mls_id=property_info["source"].get("listing_id")
if "source" in property_info and isinstance(property_info["source"], dict)
else None,
property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
mls_id=(
property_info["source"].get("listing_id")
if "source" in property_info and isinstance(property_info["source"], dict)
else None
),
property_url=f"{self.PROPERTY_URL}{property_id}",
status=property_info["basic"]["status"].upper(),
list_price=property_info["basic"]["price"],
list_date=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,
prc_sqft=(
property_info["basic"].get("price") / property_info["basic"].get("sqft")
if property_info["basic"].get("price") and property_info["basic"].get("sqft")
else None
),
last_sold_date=last_sold_date,
pending_date=pending_date,
latitude=property_info["address"]["location"]["coordinate"].get("lat")
if able_to_get_lat_long
else None,
longitude=property_info["address"]["location"]["coordinate"].get("lon")
if able_to_get_lat_long
else None,
latitude=property_info["address"]["location"]["coordinate"].get("lat") if able_to_get_lat_long else None,
longitude=property_info["address"]["location"]["coordinate"].get("lon") if able_to_get_lat_long else None,
address=self._parse_address(property_info, search_type="handle_listing"),
description=Description(
alt_photos=self.process_alt_photos(property_info.get("media", {}).get("photos", [])),
style=property_info["basic"].get("type", "").upper(),
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"),
@@ -171,8 +183,14 @@ class RealtorScraper(Scraper):
year_built=property_info["details"].get("year_built"),
garage=property_info["details"].get("garage"),
stories=property_info["details"].get("stories"),
text=property_info.get("description", {}).get("text"),
),
days_on_mls=days_on_mls
days_on_mls=days_on_mls,
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
)
return [listing]
@@ -225,6 +243,7 @@ class RealtorScraper(Scraper):
stories
}
address {
line
street_direction
street_number
street_name
@@ -266,6 +285,7 @@ class RealtorScraper(Scraper):
}"""
variables = {"property_id": property_id}
prop_details = self.get_prop_details(property_id)
payload = {
"query": query,
@@ -281,16 +301,17 @@ class RealtorScraper(Scraper):
Property(
mls_id=property_id,
property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
address=self._parse_address(
property_info, search_type="handle_address"
),
address=self._parse_address(property_info, search_type="handle_address"),
description=self._parse_description(property_info),
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
)
]
def general_search(
self, variables: dict, search_type: str
) -> Dict[str, Union[int, list[Property]]]:
def general_search(self, variables: dict, search_type: str) -> Dict[str, Union[int, list[Property]]]:
"""
Handles a location area & returns a list of properties
"""
@@ -324,6 +345,7 @@ class RealtorScraper(Scraper):
type
name
stories
text
}
source {
id
@@ -338,6 +360,7 @@ class RealtorScraper(Scraper):
street_number
street_name
street_suffix
line
unit
city
state_code
@@ -347,10 +370,17 @@ class RealtorScraper(Scraper):
lat
}
}
county {
name
fips_code
}
neighborhoods {
name
}
}
tax_record {
public_record_id
}
primary_photo {
href
}
@@ -380,17 +410,15 @@ class RealtorScraper(Scraper):
)
pending_or_contingent_param = (
"or_filters: { contingent: true, pending: true }"
if self.listing_type == ListingType.PENDING
else ""
"or_filters: { contingent: true, pending: true }" if self.listing_type == ListingType.PENDING else ""
)
listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
is_foreclosure = ""
if variables.get('foreclosure') is True:
if variables.get("foreclosure") is True:
is_foreclosure = "foreclosure: true"
elif variables.get('foreclosure') is False:
elif variables.get("foreclosure") is False:
is_foreclosure = "foreclosure: false"
if search_type == "comps": #: comps search, came from an address
@@ -453,7 +481,7 @@ class RealtorScraper(Scraper):
)
else: #: general search, came from an address
query = (
"""query Property_search(
"""query Property_search(
$property_id: [ID]!
$offset: Int!,
) {
@@ -464,7 +492,7 @@ class RealtorScraper(Scraper):
limit: 1
offset: $offset
) %s"""
% results_query
% results_query
)
payload = {
@@ -473,71 +501,85 @@ class RealtorScraper(Scraper):
}
response = self.session.post(self.SEARCH_GQL_URL, json=payload)
response.raise_for_status()
response_json = response.json()
search_key = "home_search" if "home_search" in query else "property_search"
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": []}
for result in response_json["data"][search_key]["results"]:
mls = (
result["source"].get("id")
if "source" in result and isinstance(result["source"], dict)
else None
)
def process_property(result: dict) -> Property | None:
mls = result["source"].get("id") if "source" in result and isinstance(result["source"], dict) else None
if not mls and self.mls_only:
continue
return
able_to_get_lat_long = (
result
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:
continue
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) if self.extra_property_data else {}
realty_property = Property(
mls=mls,
mls_id=result["source"].get("listing_id")
if "source" in result and isinstance(result["source"], dict)
else None,
property_url=f"{self.PROPERTY_URL}{result['property_id']}" if self.listing_type != ListingType.FOR_RENT else f"{self.PROPERTY_URL}M{result['property_id']}?listing_status=rental",
mls_id=(
result["source"].get("listing_id")
if "source" in result and isinstance(result["source"], dict)
else None
),
property_url=(
f"{self.PROPERTY_URL}{property_id}"
if self.listing_type != ListingType.FOR_RENT
else f"{self.PROPERTY_URL}M{property_id}?listing_status=rental"
),
status="PENDING" if is_pending else result["status"].upper(),
list_price=result["list_price"],
list_date=result["list_date"].split("T")[0]
if result.get("list_date")
else None,
list_date=result["list_date"].split("T")[0] if result.get("list_date") else None,
prc_sqft=result.get("price_per_sqft"),
last_sold_date=result.get("last_sold_date"),
hoa_fee=result["hoa"]["fee"]
if result.get("hoa") and isinstance(result["hoa"], dict)
else None,
latitude=result["location"]["address"]["coordinate"].get("lat")
if able_to_get_lat_long
else None,
longitude=result["location"]["address"]["coordinate"].get("lon")
if able_to_get_lat_long
else None,
hoa_fee=result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) else None,
latitude=result["location"]["address"]["coordinate"].get("lat") if able_to_get_lat_long else None,
longitude=result["location"]["address"]["coordinate"].get("lon") if able_to_get_lat_long else None,
address=self._parse_address(result, search_type="general_search"),
description=self._parse_description(result),
days_on_mls=self.calculate_days_on_mls(result)
neighborhoods=self._parse_neighborhoods(result),
county=result["location"]["county"].get("name") if result["location"]["county"] else None,
fips_code=result["location"]["county"].get("fips_code") if result["location"]["county"] else None,
days_on_mls=self.calculate_days_on_mls(result),
agents=prop_details.get("agents"),
brokers=prop_details.get("brokers"),
nearby_schools=prop_details.get("schools"),
assessed_value=prop_details.get("assessed_value"),
estimated_value=prop_details.get("estimated_value"),
)
properties.append(realty_property)
return realty_property
with ThreadPoolExecutor(max_workers=self.NUM_PROPERTY_WORKERS) as executor:
futures = [
executor.submit(process_property, result) for result in response_json["data"][search_key]["results"]
]
for future in as_completed(futures):
result = future.result()
if result:
properties.append(result)
return {
"total": response_json["data"][search_key]["total"],
@@ -558,18 +600,14 @@ class RealtorScraper(Scraper):
search_type = (
"comps"
if self.radius and location_type == "address"
else "address"
if location_type == "address" and not self.radius
else "area"
else "address" if location_type == "address" and not self.radius else "area"
)
if location_type == "address":
if not self.radius: #: single address search, non comps
property_id = location_info["mpr_id"]
search_variables |= {"property_id": property_id}
gql_results = self.general_search(
search_variables, search_type=search_type
)
gql_results = self.general_search(search_variables, search_type=search_type)
if gql_results["total"] == 0:
listing_id = self.get_latest_listing_id(property_id)
if listing_id is None:
@@ -603,13 +641,13 @@ class RealtorScraper(Scraper):
}
if self.foreclosure:
search_variables['foreclosure'] = self.foreclosure
search_variables["foreclosure"] = self.foreclosure
result = self.general_search(search_variables, search_type=search_type)
total = result["total"]
homes = result["properties"]
with ThreadPoolExecutor(max_workers=10) as executor:
with ThreadPoolExecutor() as executor:
futures = [
executor.submit(
self.general_search,
@@ -624,6 +662,88 @@ class RealtorScraper(Scraper):
return homes
def get_prop_details(self, property_id: str) -> dict:
if not self.extra_property_data:
return {}
#: TODO: migrate "advertisers" and "estimates" to general query
query = """query GetHome($property_id: ID!) {
home(property_id: $property_id) {
__typename
advertisers {
__typename
type
name
email
phones { number type ext primary }
}
consumer_advertisers {
name
phone
href
type
}
nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {
__typename schools { district { __typename id name } }
}
taxHistory: tax_history { __typename tax year assessment { __typename building land total } }
estimates {
__typename
currentValues: current_values {
__typename
source { __typename type name }
estimate
estimateHigh: estimate_high
estimateLow: estimate_low
date
isBestHomeValue: isbest_homevalue
}
}
}
}"""
variables = {"property_id": property_id}
response = self.session.post(self.PROPERTY_GQL, json={"query": query, "variables": variables})
data = response.json()
def get_key(keys: list):
try:
value = data
for key in keys:
value = value[key]
return value or {}
except (KeyError, TypeError, IndexError):
return {}
agents = get_key(["data", "home", "advertisers"])
advertisers = get_key(["data", "home", "consumer_advertisers"])
schools = get_key(["data", "home", "nearbySchools", "schools"])
assessed_value = get_key(["data", "home", "taxHistory", 0, "assessment", "total"])
estimated_value = get_key(["data", "home", "estimates", "currentValues", 0, "estimate"])
agents = [Agent(name=ad["name"], email=ad["email"], phones=ad["phones"]) for ad in agents]
brokers = [
Broker(name=ad["name"], phone=ad["phone"], website=ad["href"])
for ad in advertisers
if ad.get("type") != "Agent"
]
schools = [school["district"]["name"] for school in schools if school["district"].get("name")]
return {
"agents": agents if agents else None,
"brokers": brokers if brokers else None,
"schools": schools if schools else None,
"assessed_value": assessed_value if assessed_value else None,
"estimated_value": estimated_value if estimated_value else None,
}
@staticmethod
def _parse_neighborhoods(result: dict) -> Optional[str]:
neighborhoods_list = []
@@ -644,19 +764,25 @@ class RealtorScraper(Scraper):
return address_part
def _parse_address(self, result: dict, search_type):
@staticmethod
def _parse_address(result: dict, search_type):
if search_type == "general_search":
address = result['location']['address']
address = result["location"]["address"]
else:
address = result["address"]
return Address(
street=" ".join([
self.handle_none_safely(address.get('street_number')),
self.handle_none_safely(address.get('street_direction')),
self.handle_none_safely(address.get('street_name')),
self.handle_none_safely(address.get('street_suffix')),
]).strip(),
full_line=address.get("line"),
street=" ".join(
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
).strip(),
unit=address["unit"],
city=address["city"],
state=address["state_code"],
@@ -683,17 +809,22 @@ class RealtorScraper(Scraper):
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"),
sold_price=(
description_data.get("sold_price")
if result.get("last_sold_date") or result["list_price"] != description_data.get("sold_price")
else None
), #: has a sold date or list and sold price are different
year_built=description_data.get("year_built"),
garage=description_data.get("garage"),
stories=description_data.get("stories"),
text=description_data.get("text"),
)
@staticmethod
@@ -705,12 +836,12 @@ class RealtorScraper(Scraper):
today = datetime.now()
if list_date:
if result["status"] == 'sold':
if result["status"] == "sold":
if last_sold_date:
days = (last_sold_date - list_date).days
if days >= 0:
return days
elif result["status"] in ('for_sale', 'for_rent'):
elif result["status"] in ("for_sale", "for_rent"):
days = (today - list_date).days
if days >= 0:
return days

View File

@@ -1,5 +1,14 @@
class InvalidListingType(Exception):
"""Raised when a provided listing type is does not exist."""
class InvalidDate(Exception):
"""Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23 """
"""Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23"""
class AuthenticationError(Exception):
"""Raised when there is an issue with the authentication process."""
def __init__(self, *args, response):
super().__init__(*args)
self.response = response

View File

@@ -1,6 +1,7 @@
from __future__ import annotations
import pandas as pd
from datetime import datetime
from .core.scrapers.models import Property, ListingType
from .core.scrapers.models import Property, ListingType, Agent
from .exceptions import InvalidListingType, InvalidDate
ordered_properties = [
@@ -8,7 +9,9 @@ ordered_properties = [
"mls",
"mls_id",
"status",
"text",
"style",
"full_street_line",
"street",
"unit",
"city",
@@ -24,13 +27,25 @@ ordered_properties = [
"list_date",
"sold_price",
"last_sold_date",
"assessed_value",
"estimated_value",
"lot_sqft",
"price_per_sqft",
"latitude",
"longitude",
"neighborhoods",
"county",
"fips_code",
"stories",
"hoa_fee",
"parking_garage",
"agent",
"agent_email",
"agent_phones",
"broker",
"broker_phone",
"broker_website",
"nearby_schools",
"primary_photo",
"alt_photos",
]
@@ -42,27 +57,46 @@ def process_result(result: Property) -> pd.DataFrame:
if "address" in prop_data:
address_data = prop_data["address"]
prop_data["full_street_line"] = address_data.full_line
prop_data["street"] = address_data.street
prop_data["unit"] = address_data.unit
prop_data["city"] = address_data.city
prop_data["state"] = address_data.state
prop_data["zip_code"] = address_data.zip
if "agents" in prop_data:
agents: list[Agent] | None = prop_data["agents"]
if agents:
prop_data["agent"] = agents[0].name
prop_data["agent_email"] = agents[0].email
prop_data["agent_phones"] = agents[0].phones
if "brokers" in prop_data:
brokers = prop_data["brokers"]
if brokers:
prop_data["broker"] = brokers[0].name
prop_data["broker_phone"] = brokers[0].phone
prop_data["broker_website"] = brokers[0].website
prop_data["price_per_sqft"] = prop_data["prc_sqft"]
prop_data["nearby_schools"] = filter(None, prop_data["nearby_schools"]) if prop_data["nearby_schools"] else None
prop_data["nearby_schools"] = ", ".join(set(prop_data["nearby_schools"])) if prop_data["nearby_schools"] else None
description = result.description
prop_data["primary_photo"] = description.primary_photo
prop_data["alt_photos"] = ", ".join(description.alt_photos)
prop_data["style"] = description.style
prop_data["beds"] = description.beds
prop_data["full_baths"] = description.baths_full
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
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)
@@ -72,9 +106,7 @@ def process_result(result: Property) -> pd.DataFrame:
def validate_input(listing_type: str) -> None:
if listing_type.upper() not in ListingType.__members__:
raise InvalidListingType(
f"Provided listing type, '{listing_type}', does not exist."
)
raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
def validate_dates(date_from: str | None, date_to: str | None) -> None:
@@ -88,5 +120,5 @@ def validate_dates(date_from: str | None, date_to: str | None) -> None:
if date_to_obj < date_from_obj:
raise InvalidDate("date_to must be after date_from.")
except ValueError as e:
except ValueError:
raise InvalidDate(f"Invalid date format or range")

348
poetry.lock generated
View File

@@ -1,4 +1,15 @@
# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "annotated-types"
version = "0.7.0"
description = "Reusable constraint types to use with typing.Annotated"
optional = false
python-versions = ">=3.8"
files = [
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
{file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
]
[[package]]
name = "certifi"
@@ -11,6 +22,17 @@ files = [
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
]
[[package]]
name = "cfgv"
version = "3.4.0"
description = "Validate configuration and produce human readable error messages."
optional = false
python-versions = ">=3.8"
files = [
{file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
{file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
]
[[package]]
name = "charset-normalizer"
version = "3.3.0"
@@ -122,14 +144,14 @@ files = [
]
[[package]]
name = "et-xmlfile"
version = "1.1.0"
description = "An implementation of lxml.xmlfile for the standard library"
name = "distlib"
version = "0.3.8"
description = "Distribution utilities"
optional = false
python-versions = ">=3.6"
python-versions = "*"
files = [
{file = "et_xmlfile-1.1.0-py3-none-any.whl", hash = "sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada"},
{file = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
{file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"},
{file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
]
[[package]]
@@ -146,6 +168,36 @@ files = [
[package.extras]
test = ["pytest (>=6)"]
[[package]]
name = "filelock"
version = "3.13.4"
description = "A platform independent file lock."
optional = false
python-versions = ">=3.8"
files = [
{file = "filelock-3.13.4-py3-none-any.whl", hash = "sha256:404e5e9253aa60ad457cae1be07c0f0ca90a63931200a47d9b6a6af84fd7b45f"},
{file = "filelock-3.13.4.tar.gz", hash = "sha256:d13f466618bfde72bd2c18255e269f72542c6e70e7bac83a0232d6b1cc5c8cf4"},
]
[package.extras]
docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
typing = ["typing-extensions (>=4.8)"]
[[package]]
name = "identify"
version = "2.5.35"
description = "File identification library for Python"
optional = false
python-versions = ">=3.8"
files = [
{file = "identify-2.5.35-py2.py3-none-any.whl", hash = "sha256:c4de0081837b211594f8e877a6b4fad7ca32bbfc1a9307fdd61c28bfe923f13e"},
{file = "identify-2.5.35.tar.gz", hash = "sha256:10a7ca245cfcd756a554a7288159f72ff105ad233c7c4b9c6f0f4d108f5f6791"},
]
[package.extras]
license = ["ukkonen"]
[[package]]
name = "idna"
version = "3.4"
@@ -168,6 +220,20 @@ files = [
{file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
]
[[package]]
name = "nodeenv"
version = "1.8.0"
description = "Node.js virtual environment builder"
optional = false
python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
files = [
{file = "nodeenv-1.8.0-py2.py3-none-any.whl", hash = "sha256:df865724bb3c3adc86b3876fa209771517b0cfe596beff01a92700e0e8be4cec"},
{file = "nodeenv-1.8.0.tar.gz", hash = "sha256:d51e0c37e64fbf47d017feac3145cdbb58836d7eee8c6f6d3b6880c5456227d2"},
]
[package.dependencies]
setuptools = "*"
[[package]]
name = "numpy"
version = "1.26.0"
@@ -209,20 +275,6 @@ files = [
{file = "numpy-1.26.0.tar.gz", hash = "sha256:f93fc78fe8bf15afe2b8d6b6499f1c73953169fad1e9a8dd086cdff3190e7fdf"},
]
[[package]]
name = "openpyxl"
version = "3.1.2"
description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
optional = false
python-versions = ">=3.6"
files = [
{file = "openpyxl-3.1.2-py2.py3-none-any.whl", hash = "sha256:f91456ead12ab3c6c2e9491cf33ba6d08357d802192379bb482f1033ade496f5"},
{file = "openpyxl-3.1.2.tar.gz", hash = "sha256:a6f5977418eff3b2d5500d54d9db50c8277a368436f4e4f8ddb1be3422870184"},
]
[package.dependencies]
et-xmlfile = "*"
[[package]]
name = "packaging"
version = "23.2"
@@ -302,6 +354,21 @@ sql-other = ["SQLAlchemy (>=1.4.36)"]
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
xml = ["lxml (>=4.8.0)"]
[[package]]
name = "platformdirs"
version = "4.2.0"
description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
optional = false
python-versions = ">=3.8"
files = [
{file = "platformdirs-4.2.0-py3-none-any.whl", hash = "sha256:0614df2a2f37e1a662acbd8e2b25b92ccf8632929bc6d43467e17fe89c75e068"},
{file = "platformdirs-4.2.0.tar.gz", hash = "sha256:ef0cc731df711022c174543cb70a9b5bd22e5a9337c8624ef2c2ceb8ddad8768"},
]
[package.extras]
docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
[[package]]
name = "pluggy"
version = "1.3.0"
@@ -317,6 +384,134 @@ files = [
dev = ["pre-commit", "tox"]
testing = ["pytest", "pytest-benchmark"]
[[package]]
name = "pre-commit"
version = "3.7.0"
description = "A framework for managing and maintaining multi-language pre-commit hooks."
optional = false
python-versions = ">=3.9"
files = [
{file = "pre_commit-3.7.0-py2.py3-none-any.whl", hash = "sha256:5eae9e10c2b5ac51577c3452ec0a490455c45a0533f7960f993a0d01e59decab"},
{file = "pre_commit-3.7.0.tar.gz", hash = "sha256:e209d61b8acdcf742404408531f0c37d49d2c734fd7cff2d6076083d191cb060"},
]
[package.dependencies]
cfgv = ">=2.0.0"
identify = ">=1.0.0"
nodeenv = ">=0.11.1"
pyyaml = ">=5.1"
virtualenv = ">=20.10.0"
[[package]]
name = "pydantic"
version = "2.7.4"
description = "Data validation using Python type hints"
optional = false
python-versions = ">=3.8"
files = [
{file = "pydantic-2.7.4-py3-none-any.whl", hash = "sha256:ee8538d41ccb9c0a9ad3e0e5f07bf15ed8015b481ced539a1759d8cc89ae90d0"},
{file = "pydantic-2.7.4.tar.gz", hash = "sha256:0c84efd9548d545f63ac0060c1e4d39bb9b14db8b3c0652338aecc07b5adec52"},
]
[package.dependencies]
annotated-types = ">=0.4.0"
pydantic-core = "2.18.4"
typing-extensions = ">=4.6.1"
[package.extras]
email = ["email-validator (>=2.0.0)"]
[[package]]
name = "pydantic-core"
version = "2.18.4"
description = "Core functionality for Pydantic validation and serialization"
optional = false
python-versions = ">=3.8"
files = [
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{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
]
[[package]]
name = "requests"
version = "2.31.0"
@@ -385,6 +640,22 @@ urllib3 = ">=1.21.1,<3"
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
[[package]]
name = "setuptools"
version = "69.5.1"
description = "Easily download, build, install, upgrade, and uninstall Python packages"
optional = false
python-versions = ">=3.8"
files = [
{file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
{file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
]
[package.extras]
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
[[package]]
name = "six"
version = "1.16.0"
@@ -407,6 +678,17 @@ files = [
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
]
[[package]]
name = "typing-extensions"
version = "4.12.2"
description = "Backported and Experimental Type Hints for Python 3.8+"
optional = false
python-versions = ">=3.8"
files = [
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
]
[[package]]
name = "tzdata"
version = "2023.3"
@@ -435,7 +717,27 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"]
[[package]]
name = "virtualenv"
version = "20.25.1"
description = "Virtual Python Environment builder"
optional = false
python-versions = ">=3.7"
files = [
{file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
{file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
]
[package.dependencies]
distlib = ">=0.3.7,<1"
filelock = ">=3.12.2,<4"
platformdirs = ">=3.9.1,<5"
[package.extras]
docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.10,<3.13"
content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"
python-versions = ">=3.9,<3.13"
content-hash = "21ef9cfb35c446a375a2b74c37691d7031afb1e4f66a8b63cb7c1669470689d2"

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "homeharvest"
version = "0.3.14"
version = "0.3.32"
description = "Real estate scraping library"
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
homepage = "https://github.com/Bunsly/HomeHarvest"
@@ -10,13 +10,15 @@ readme = "README.md"
homeharvest = "homeharvest.cli:main"
[tool.poetry.dependencies]
python = ">=3.10,<3.13"
python = ">=3.9,<3.13"
requests = "^2.31.0"
pandas = "^2.1.1"
pydantic = "^2.7.4"
[tool.poetry.group.dev.dependencies]
pytest = "^7.4.2"
pre-commit = "^3.7.0"
[build-system]
requires = ["poetry-core"]

View File

@@ -1,22 +1,12 @@
from homeharvest import scrape_property
from homeharvest.exceptions import (
InvalidListingType,
)
def test_realtor_pending_or_contingent():
pending_or_contingent_result = scrape_property(
location="Surprise, AZ", listing_type="pending"
)
pending_or_contingent_result = scrape_property(location="Surprise, AZ", listing_type="pending")
regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale", exclude_pending=True)
assert all(
[
result is not None
for result in [pending_or_contingent_result, regular_result]
]
)
assert all([result is not None for result in [pending_or_contingent_result, regular_result]])
assert len(pending_or_contingent_result) != len(regular_result)
@@ -71,17 +61,13 @@ def test_realtor_comps():
def test_realtor_last_x_days_sold():
days_result_30 = scrape_property(
location="Dallas, TX", listing_type="sold", past_days=30
)
days_result_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
)
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)
assert all([result is not None for result in [days_result_30, days_result_10]]) and len(days_result_30) != len(
days_result_10
)
def test_realtor_date_range_sold():
@@ -93,9 +79,9 @@ def test_realtor_date_range_sold():
location="Dallas, TX", listing_type="sold", date_from="2023-04-01", date_to="2023-06-10"
)
assert all(
[result is not None for result in [days_result_30, days_result_60]]
) and len(days_result_30) < len(days_result_60)
assert all([result is not None for result in [days_result_30, days_result_60]]) and len(days_result_30) < len(
days_result_60
)
def test_realtor_single_property():
@@ -119,12 +105,8 @@ def test_realtor():
location="2530 Al Lipscomb Way",
listing_type="for_sale",
),
scrape_property(
location="Phoenix, AZ", listing_type="for_rent"
), #: does not support "city, state, USA" format
scrape_property(
location="Dallas, TX", listing_type="sold"
), #: does not support "city, state, USA" format
scrape_property(location="Phoenix, AZ", listing_type="for_rent"), #: does not support "city, state, USA" format
scrape_property(location="Dallas, TX", listing_type="sold"), #: does not support "city, state, USA" format
scrape_property(location="85281"),
]
@@ -142,21 +124,64 @@ def test_realtor_city():
def test_realtor_bad_address():
bad_results = scrape_property(
location="abceefg ju098ot498hh9",
listing_type="for_sale",
)
location="abceefg ju098ot498hh9",
listing_type="for_sale",
)
if len(bad_results) == 0:
assert True
def test_realtor_foreclosed():
foreclosed = scrape_property(
location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=True
)
foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=True)
not_foreclosed = scrape_property(
location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=False
)
not_foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=False)
assert len(foreclosed) != len(not_foreclosed)
def test_realtor_agent():
scraped = scrape_property(location="Detroit, MI", listing_type="for_sale")
assert scraped["agent"].nunique() > 1
def test_realtor_without_extra_details():
results = [
scrape_property(
location="15509 N 172nd Dr, Surprise, AZ 85388",
extra_property_data=False,
),
scrape_property(
location="15509 N 172nd Dr, Surprise, AZ 85388",
),
]
assert not results[0].equals(results[1])
def test_pr_zip_code():
results = scrape_property(
location="00741",
listing_type="for_sale",
)
assert results is not None and len(results) > 0
def test_exclude_pending():
results = scrape_property(
location="33567",
listing_type="pending",
exclude_pending=True,
)
assert results is not None and len(results) > 0
def test_style_value_error():
results = scrape_property(
location="Alaska, AK",
listing_type="sold",
extra_property_data=False,
)
assert results is not None and len(results) > 0