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24
README.md
24
README.md
@@ -21,7 +21,7 @@
|
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```bash
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pip install -U homeharvest
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```
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_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
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_Python version >= [3.9](https://www.python.org/downloads/release/python-3100/) required_
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## Usage
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@@ -43,7 +43,6 @@ properties = scrape_property(
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# date_from="2023-05-01", # alternative to past_days
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# date_to="2023-05-28",
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# foreclosure=True
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# mls_only=True, # only fetch MLS listings
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)
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print(f"Number of properties: {len(properties)}")
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@@ -91,7 +90,13 @@ Optional
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│
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├── foreclosure (True/False): If set, fetches only foreclosures
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│
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└── proxy (string): In format 'http://user:pass@host:port'
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├── proxy (string): In format 'http://user:pass@host:port'
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│
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├── extra_property_data (True/False): Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
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│
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├── exclude_pending (True/False): If set, excludes pending properties from the results unless listing_type is 'pending'
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│
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└── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
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```
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### Property Schema
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@@ -139,17 +144,18 @@ Property
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├── Agent Info:
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│ ├── agent
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│ ├── broker
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│ └── broker_phone
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│ ├── agent_email
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│ └── agent_phone
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|
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├── Agent Info:
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│ ├── agent
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├── Broker Info:
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│ ├── broker
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│ └── broker_phone
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│ ├── broker_email
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│ └── broker_website
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```
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### Exceptions
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The following exceptions may be raised when using HomeHarvest:
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- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
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- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
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- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD.
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- `AuthenticationError` - Realtor.com token request failed.
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@@ -1,7 +1,7 @@
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import warnings
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import pandas as pd
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from .core.scrapers import ScraperInput
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from .utils import process_result, ordered_properties, validate_input, validate_dates
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from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit
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from .core.scrapers.realtor import RealtorScraper
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from .core.scrapers.models import ListingType
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@@ -13,22 +13,30 @@ def scrape_property(
|
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mls_only: bool = False,
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past_days: int = None,
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proxy: str = None,
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||||
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,
|
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foreclosure: bool = None,
|
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extra_property_data: bool = True,
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exclude_pending: bool = False,
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limit: int = 10000,
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) -> pd.DataFrame:
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"""
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Scrape properties from Realtor.com based on a given location and listing type.
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:param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
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:param listing_type: Listing Type (for_sale, for_rent, sold)
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: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.
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: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.
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||||
:param limit: Limit the number of results returned. Maximum is 10,000.
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"""
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validate_input(listing_type)
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||||
validate_dates(date_from, date_to)
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validate_limit(limit)
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||||
|
||||
scraper_input = ScraperInput(
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location=location,
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||||
@@ -40,15 +48,19 @@ def scrape_property(
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date_from=date_from,
|
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date_to=date_to,
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foreclosure=foreclosure,
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||||
extra_property_data=extra_property_data,
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||||
exclude_pending=exclude_pending,
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||||
limit=limit,
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||||
)
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site = RealtorScraper(scraper_input)
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results = site.search()
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properties_dfs = [process_result(result) for result in results]
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properties_dfs = [df for result in results if not (df := process_result(result)).empty]
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if not properties_dfs:
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return pd.DataFrame()
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=FutureWarning)
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return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties]
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return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace({"None": pd.NA, None: pd.NA, "": pd.NA})
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||||
@@ -1,8 +1,12 @@
|
||||
import uuid
|
||||
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
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||||
from .models import Property, ListingType, SiteName
|
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import json
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||||
|
||||
|
||||
@dataclass
|
||||
@@ -10,33 +14,42 @@ 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
|
||||
limit: int = 10000
|
||||
|
||||
|
||||
class Scraper:
|
||||
session = None
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||||
|
||||
def __init__(
|
||||
self,
|
||||
scraper_input: ScraperInput,
|
||||
session: requests.Session = None,
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||||
):
|
||||
self.location = scraper_input.location
|
||||
self.listing_type = scraper_input.listing_type
|
||||
|
||||
if not session:
|
||||
self.session = requests.Session()
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self.session.headers.update(
|
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if not self.session:
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Scraper.session = requests.Session()
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||||
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)
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||||
Scraper.session.headers.update(
|
||||
{
|
||||
"auth": f"Bearer {self.get_access_token()}",
|
||||
"apollographql-client-name": "com.move.Realtor-apollo-ios",
|
||||
}
|
||||
)
|
||||
else:
|
||||
self.session = session
|
||||
|
||||
if scraper_input.proxy:
|
||||
proxy_url = scraper_input.proxy
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||||
@@ -50,6 +63,9 @@ 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
|
||||
self.limit = scraper_input.limit
|
||||
|
||||
def search(self) -> list[Property]: ...
|
||||
|
||||
@@ -58,19 +74,34 @@ class Scraper:
|
||||
|
||||
def handle_location(self): ...
|
||||
|
||||
def get_access_token(self):
|
||||
url = "https://graph.realtor.com/auth/token"
|
||||
@staticmethod
|
||||
def get_access_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()
|
||||
return data["access_token"]
|
||||
|
||||
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
|
||||
|
||||
@@ -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"
|
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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
|
||||
@@ -73,12 +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
|
||||
@@ -101,6 +124,10 @@ class Property:
|
||||
latitude: float | None = None
|
||||
longitude: float | None = None
|
||||
neighborhoods: Optional[str] = None
|
||||
|
||||
agents: list[Agent] = 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
|
||||
|
||||
@@ -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 concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
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
|
||||
@@ -142,7 +144,8 @@ class RealtorScraper(Scraper):
|
||||
days_on_mls = None
|
||||
|
||||
property_id = property_info["details"]["permalink"]
|
||||
agents_schools = self.get_agents_schools(property_id)
|
||||
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"),
|
||||
@@ -176,10 +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,
|
||||
agents=agents_schools["agents"],
|
||||
nearby_schools=agents_schools["schools"],
|
||||
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]
|
||||
@@ -232,6 +243,7 @@ class RealtorScraper(Scraper):
|
||||
stories
|
||||
}
|
||||
address {
|
||||
line
|
||||
street_direction
|
||||
street_number
|
||||
street_name
|
||||
@@ -273,7 +285,7 @@ class RealtorScraper(Scraper):
|
||||
}"""
|
||||
|
||||
variables = {"property_id": property_id}
|
||||
agents_schools = self.get_agents_schools(property_id)
|
||||
prop_details = self.get_prop_details(property_id)
|
||||
|
||||
payload = {
|
||||
"query": query,
|
||||
@@ -291,8 +303,11 @@ class RealtorScraper(Scraper):
|
||||
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),
|
||||
agents=agents_schools["agents"],
|
||||
nearby_schools=agents_schools["schools"],
|
||||
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"),
|
||||
)
|
||||
]
|
||||
|
||||
@@ -330,6 +345,7 @@ class RealtorScraper(Scraper):
|
||||
type
|
||||
name
|
||||
stories
|
||||
text
|
||||
}
|
||||
source {
|
||||
id
|
||||
@@ -344,6 +360,7 @@ class RealtorScraper(Scraper):
|
||||
street_number
|
||||
street_name
|
||||
street_suffix
|
||||
line
|
||||
unit
|
||||
city
|
||||
state_code
|
||||
@@ -353,10 +370,17 @@ class RealtorScraper(Scraper):
|
||||
lat
|
||||
}
|
||||
}
|
||||
county {
|
||||
name
|
||||
fips_code
|
||||
}
|
||||
neighborhoods {
|
||||
name
|
||||
}
|
||||
}
|
||||
tax_record {
|
||||
public_record_id
|
||||
}
|
||||
primary_photo {
|
||||
href
|
||||
}
|
||||
@@ -457,7 +481,7 @@ class RealtorScraper(Scraper):
|
||||
)
|
||||
else: #: general search, came from an address
|
||||
query = (
|
||||
"""query Property_search(
|
||||
"""query Property_search(
|
||||
$property_id: [ID]!
|
||||
$offset: Int!,
|
||||
) {
|
||||
@@ -468,7 +492,7 @@ class RealtorScraper(Scraper):
|
||||
limit: 1
|
||||
offset: $offset
|
||||
) %s"""
|
||||
% results_query
|
||||
% results_query
|
||||
)
|
||||
|
||||
payload = {
|
||||
@@ -477,19 +501,18 @@ 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": []}
|
||||
|
||||
@@ -500,19 +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"]
|
||||
agents_schools = self.get_agents_schools(property_id)
|
||||
prop_details = self.get_prop_details(property_id) if self.extra_property_data else {}
|
||||
|
||||
realty_property = Property(
|
||||
mls=mls,
|
||||
@@ -536,9 +559,15 @@ class RealtorScraper(Scraper):
|
||||
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),
|
||||
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=agents_schools["agents"],
|
||||
nearby_schools=agents_schools["schools"],
|
||||
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 realty_property
|
||||
|
||||
@@ -618,14 +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):
|
||||
@@ -633,25 +662,87 @@ class RealtorScraper(Scraper):
|
||||
|
||||
return homes
|
||||
|
||||
def get_agents_schools(self, property_id: str) -> dict:
|
||||
payload = f'{{"query":"query GetHome($property_id: ID!) {{\\n home(property_id: $property_id) {{\\n __typename\\n\\n consumerAdvertisers: consumer_advertisers {{\\n __typename\\n type\\n advertiserId: advertiser_id\\n name\\n phone\\n type\\n href\\n slogan\\n photo {{\\n __typename\\n href\\n }}\\n showRealtorLogo: show_realtor_logo\\n hours\\n }}\\n\\n\\n nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {{ __typename schools {{ district {{ __typename id name }} }} }}}}\\n}}\\n","variables":{{"property_id":"{property_id}"}}}}'
|
||||
response = self.session.post(self.PROPERTY_GQL, data=payload)
|
||||
def get_prop_details(self, property_id: str) -> dict:
|
||||
if not self.extra_property_data:
|
||||
return {}
|
||||
|
||||
#: TODO: migrate "advertisers" and "estimates" to general query
|
||||
|
||||
query = """query GetHome($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:
|
||||
data = response.json()
|
||||
value = data
|
||||
for key in keys:
|
||||
data = data[key]
|
||||
return data
|
||||
except (KeyError, TypeError):
|
||||
return []
|
||||
value = value[key]
|
||||
|
||||
return value or {}
|
||||
except (KeyError, TypeError, IndexError):
|
||||
return {}
|
||||
|
||||
agents = get_key(["data", "home", "advertisers"])
|
||||
advertisers = get_key(["data", "home", "consumer_advertisers"])
|
||||
|
||||
ads = get_key(["data", "home", "consumerAdvertisers"])
|
||||
schools = get_key(["data", "home", "nearbySchools", "schools"])
|
||||
assessed_value = get_key(["data", "home", "taxHistory", 0, "assessment", "total"])
|
||||
estimated_value = get_key(["data", "home", "estimates", "currentValues", 0, "estimate"])
|
||||
|
||||
agents = [Agent(name=ad["name"], phone=ad["phone"]) for ad in ads]
|
||||
schools = [school["district"]["name"] for school in schools]
|
||||
return {"agents": agents, "schools": schools}
|
||||
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]:
|
||||
@@ -673,20 +764,24 @@ 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"]
|
||||
else:
|
||||
address = result["address"]
|
||||
|
||||
return Address(
|
||||
full_line=address.get("line"),
|
||||
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")),
|
||||
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"],
|
||||
@@ -695,7 +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):
|
||||
@@ -706,25 +804,27 @@ 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"),
|
||||
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
|
||||
|
||||
@@ -4,3 +4,11 @@ class InvalidListingType(Exception):
|
||||
|
||||
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"""
|
||||
|
||||
|
||||
class AuthenticationError(Exception):
|
||||
"""Raised when there is an issue with the authentication process."""
|
||||
def __init__(self, *args, response):
|
||||
super().__init__(*args)
|
||||
|
||||
self.response = response
|
||||
|
||||
@@ -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",
|
||||
@@ -24,16 +27,24 @@ 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",
|
||||
@@ -46,6 +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
|
||||
@@ -53,30 +65,39 @@ def process_result(result: Property) -> pd.DataFrame:
|
||||
prop_data["zip_code"] = address_data.zip
|
||||
|
||||
if "agents" in prop_data:
|
||||
agents = prop_data["agents"]
|
||||
agents: list[Agent] | None = prop_data["agents"]
|
||||
if agents:
|
||||
prop_data["agent"] = agents[0].name
|
||||
if len(agents) > 1:
|
||||
prop_data["broker"] = agents[1].name
|
||||
prop_data["broker_phone"] = agents[1].phone
|
||||
prop_data["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.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
|
||||
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)
|
||||
@@ -90,7 +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:
|
||||
@@ -100,5 +121,12 @@ 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")
|
||||
|
||||
|
||||
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
136
poetry.lock
generated
@@ -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"
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||||
optional = false
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||||
python-versions = ">=3.8"
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||||
files = [
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]
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||||
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||||
[[package]]
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||||
name = "certifi"
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||||
version = "2023.7.22"
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||||
@@ -391,6 +402,116 @@ nodeenv = ">=0.11.1"
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||||
pyyaml = ">=5.1"
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||||
virtualenv = ">=20.10.0"
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||||
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||||
[[package]]
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name = "pydantic"
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description = "Data validation using Python type hints"
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||||
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||||
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[package.dependencies]
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annotated-types = ">=0.4.0"
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[package.extras]
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email = ["email-validator (>=2.0.0)"]
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||||
[[package]]
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name = "pydantic-core"
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version = "2.18.4"
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description = "Core functionality for Pydantic validation and serialization"
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python-versions = ">=3.8"
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{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:293afe532740370aba8c060882f7d26cfd00c94cae32fd2e212a3a6e3b7bc15e"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b48ece5bde2e768197a2d0f6e925f9d7e3e826f0ad2271120f8144a9db18d5c8"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:eae237477a873ab46e8dd748e515c72c0c804fb380fbe6c85533c7de51f23a8f"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:834b5230b5dfc0c1ec37b2fda433b271cbbc0e507560b5d1588e2cc1148cf1ce"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:e858ac0a25074ba4bce653f9b5d0a85b7456eaddadc0ce82d3878c22489fa4ee"},
|
||||
{file = "pydantic_core-2.18.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:2fd41f6eff4c20778d717af1cc50eca52f5afe7805ee530a4fbd0bae284f16e9"},
|
||||
{file = "pydantic_core-2.18.4.tar.gz", hash = "sha256:ec3beeada09ff865c344ff3bc2f427f5e6c26401cc6113d77e372c3fdac73864"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
|
||||
|
||||
[[package]]
|
||||
name = "pytest"
|
||||
version = "7.4.2"
|
||||
@@ -557,6 +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"
|
||||
@@ -607,5 +739,5 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<3.13"
|
||||
content-hash = "371781da268d5f61d6e798c023777f337b620e9b07a48c316825d7b998b63f02"
|
||||
python-versions = ">=3.9,<3.13"
|
||||
content-hash = "21ef9cfb35c446a375a2b74c37691d7031afb1e4f66a8b63cb7c1669470689d2"
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[tool.poetry]
|
||||
name = "homeharvest"
|
||||
version = "0.3.18"
|
||||
version = "0.3.33"
|
||||
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]
|
||||
|
||||
@@ -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)
|
||||
@@ -142,3 +142,46 @@ def test_realtor_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
|
||||
Reference in New Issue
Block a user