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90
README.md
90
README.md
@@ -4,12 +4,11 @@
|
||||
|
||||
[](https://replit.com/@ZacharyHampton/HomeHarvestDemo)
|
||||
|
||||
\
|
||||
**Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
|
||||
|
||||
*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/zachary-products/15min)** *to work with us.*
|
||||
*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com)** *to work with us.*
|
||||
|
||||
Check out another project we wrote: ***[JobSpy](https://github.com/cullenwatson/JobSpy)** – a Python package for job scraping*
|
||||
Check out another project we wrote: ***[JobSpy](https://github.com/Bunsly/JobSpy)** – a Python package for job scraping*
|
||||
|
||||
## HomeHarvest Features
|
||||
|
||||
@@ -21,7 +20,7 @@ Check out another project we wrote: ***[JobSpy](https://github.com/cullenwatson/
|
||||
- **CLI**: For users who prefer command-line operations.
|
||||
|
||||
|
||||
[Video Guide for HomeHarvest](https://youtu.be/JnV7eR2Ve2o) - _updated for release v0.2.7_
|
||||
[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
|
||||
|
||||

|
||||
|
||||
@@ -46,9 +45,12 @@ filename = f"HomeHarvest_{current_timestamp}.csv"
|
||||
|
||||
properties = scrape_property(
|
||||
location="San Diego, CA",
|
||||
listing_type="sold", # or (for_sale, for_rent)
|
||||
property_younger_than=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
|
||||
# pending_or_contingent=True # use on for_sale listings to find pending / contingent listings
|
||||
listing_type="sold", # or (for_sale, for_rent, pending)
|
||||
past_days=30, # sold in last 30 days - listed in last 30 days if (for_sale, for_rent)
|
||||
|
||||
# date_from="2023-05-01", # alternative to past_days
|
||||
# date_to="2023-05-28",
|
||||
|
||||
# mls_only=True, # only fetch MLS listings
|
||||
# proxy="http://user:pass@host:port" # use a proxy to change your IP address
|
||||
)
|
||||
@@ -59,37 +61,6 @@ properties.to_csv(filename, index=False)
|
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print(properties.head())
|
||||
```
|
||||
|
||||
### CLI
|
||||
|
||||
```
|
||||
usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] [-c] location
|
||||
|
||||
Home Harvest Property Scraper
|
||||
|
||||
positional arguments:
|
||||
location Location to scrape (e.g., San Francisco, CA)
|
||||
|
||||
options:
|
||||
-l {for_sale,for_rent,sold}, --listing_type {for_sale,for_rent,sold}
|
||||
Listing type to scrape
|
||||
-o {excel,csv}, --output {excel,csv}
|
||||
Output format
|
||||
-f FILENAME, --filename FILENAME
|
||||
Name of the output file (without extension)
|
||||
-p PROXY, --proxy PROXY
|
||||
Proxy to use for scraping
|
||||
-d DAYS, --days DAYS Sold/listed in last _ days filter.
|
||||
-r RADIUS, --radius RADIUS
|
||||
Get comparable properties within _ (e.g., 0.0) miles. Only applicable for individual addresses.
|
||||
-m, --mls_only If set, fetches only MLS listings.
|
||||
-c, --pending_or_contingent
|
||||
If set, fetches only pending or contingent listings. Only applicable for for_sale listings from general area searches.
|
||||
|
||||
```
|
||||
```bash
|
||||
> homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
|
||||
```
|
||||
|
||||
|
||||
## Output
|
||||
```plaintext
|
||||
@@ -111,21 +82,55 @@ Required
|
||||
- 'for_rent'
|
||||
- 'for_sale'
|
||||
- 'sold'
|
||||
- 'pending'
|
||||
|
||||
Optional
|
||||
├── radius (decimal): Radius in miles to find comparable properties based on individual addresses.
|
||||
│ Example: 5.5 (fetches properties within a 5.5-mile radius if location is set to a specific address; otherwise, ignored)
|
||||
│
|
||||
├── property_younger_than (integer): Number of past days to filter properties. Utilizes 'last_sold_date' for 'sold' listing types, and 'list_date' for others (for_rent, for_sale).
|
||||
├── past_days (integer): Number of past days to filter properties. Utilizes 'last_sold_date' for 'sold' listing types, and 'list_date' for others (for_rent, for_sale).
|
||||
│ Example: 30 (fetches properties listed/sold in the last 30 days)
|
||||
|
|
||||
├── pending_or_contingent (True/False): If set, fetches only pending or contingent listings. Only applicable for `for_sale listings` from general area searches.
|
||||
│
|
||||
├── date_from, date_to (string): Start and end dates to filter properties listed or sold, both dates are required.
|
||||
} (use this to get properties in chunks as there's a 10k result limit)
|
||||
│ Format for both must be "YYYY-MM-DD".
|
||||
│ Example: "2023-05-01", "2023-05-15" (fetches properties listed/sold between these dates)
|
||||
│
|
||||
├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
|
||||
│
|
||||
└── proxy (string): In format 'http://user:pass@host:port'
|
||||
|
||||
|
||||
```
|
||||
|
||||
### CLI
|
||||
|
||||
```
|
||||
usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] [-c] location
|
||||
|
||||
Home Harvest Property Scraper
|
||||
|
||||
positional arguments:
|
||||
location Location to scrape (e.g., San Francisco, CA)
|
||||
|
||||
options:
|
||||
-l {for_sale,for_rent,sold,pending}, --listing_type {for_sale,for_rent,sold,pending}
|
||||
Listing type to scrape
|
||||
-o {excel,csv}, --output {excel,csv}
|
||||
Output format
|
||||
-f FILENAME, --filename FILENAME
|
||||
Name of the output file (without extension)
|
||||
-p PROXY, --proxy PROXY
|
||||
Proxy to use for scraping
|
||||
-d DAYS, --days DAYS Sold/listed in last _ days filter.
|
||||
-r RADIUS, --radius RADIUS
|
||||
Get comparable properties within _ (e.g., 0.0) miles. Only applicable for individual addresses.
|
||||
-m, --mls_only If set, fetches only MLS listings.
|
||||
```
|
||||
```bash
|
||||
homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
|
||||
```
|
||||
|
||||
### Property Schema
|
||||
```plaintext
|
||||
Property
|
||||
@@ -153,6 +158,7 @@ Property
|
||||
│ └── lot_sqft
|
||||
|
||||
├── Property Listing Details:
|
||||
│ ├── days_on_mls
|
||||
│ ├── list_price
|
||||
│ ├── list_date
|
||||
│ ├── sold_price
|
||||
@@ -172,7 +178,7 @@ Property
|
||||
The following exceptions may be raised when using HomeHarvest:
|
||||
|
||||
- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
|
||||
- `NoResultsFound` - no properties found from your search
|
||||
- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
|
||||
|
||||
|
||||
## Frequently Asked Questions
|
||||
|
||||
@@ -4,7 +4,9 @@
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cb48903e-5021-49fe-9688-45cd0bc05d0f",
|
||||
"metadata": {},
|
||||
"metadata": {
|
||||
"is_executing": true
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from homeharvest import scrape_property\n",
|
||||
@@ -84,10 +86,34 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# check sold properties\n",
|
||||
"scrape_property(\n",
|
||||
"properties = scrape_property(\n",
|
||||
" location=\"90210\",\n",
|
||||
" listing_type=\"sold\"\n",
|
||||
")"
|
||||
" listing_type=\"sold\",\n",
|
||||
" past_days=10\n",
|
||||
")\n",
|
||||
"display(properties)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "628c1ce2",
|
||||
"metadata": {
|
||||
"collapsed": false,
|
||||
"is_executing": true,
|
||||
"jupyter": {
|
||||
"outputs_hidden": false
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# display clickable URLs\n",
|
||||
"from IPython.display import display, HTML\n",
|
||||
"properties['property_url'] = '<a href=\"' + properties['property_url'] + '\" target=\"_blank\">' + properties['property_url'] + '</a>'\n",
|
||||
"\n",
|
||||
"html = properties.to_html(escape=False)\n",
|
||||
"truncate_width = f'<style>.dataframe td {{ max-width: 200px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }}</style>{html}'\n",
|
||||
"display(HTML(truncate_width))"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
@@ -8,7 +8,7 @@ filename = f"HomeHarvest_{current_timestamp}.csv"
|
||||
properties = scrape_property(
|
||||
location="San Diego, CA",
|
||||
listing_type="sold", # or (for_sale, for_rent)
|
||||
property_younger_than=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
|
||||
past_days=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
|
||||
# pending_or_contingent=True # use on for_sale listings to find pending / contingent listings
|
||||
# mls_only=True, # only fetch MLS listings
|
||||
# proxy="http://user:pass@host:port" # use a proxy to change your IP address
|
||||
|
||||
@@ -1,10 +1,9 @@
|
||||
import warnings
|
||||
import pandas as pd
|
||||
from .core.scrapers import ScraperInput
|
||||
from .utils import process_result, ordered_properties, validate_input
|
||||
from .utils import process_result, ordered_properties, validate_input, validate_dates
|
||||
from .core.scrapers.realtor import RealtorScraper
|
||||
from .core.scrapers.models import ListingType
|
||||
from .exceptions import InvalidListingType, NoResultsFound
|
||||
|
||||
|
||||
def scrape_property(
|
||||
@@ -12,9 +11,10 @@ def scrape_property(
|
||||
listing_type: str = "for_sale",
|
||||
radius: float = None,
|
||||
mls_only: bool = False,
|
||||
property_younger_than: int = None,
|
||||
pending_or_contingent: bool = False,
|
||||
past_days: int = None,
|
||||
proxy: str = None,
|
||||
date_from: str = None,
|
||||
date_to: str = None,
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
Scrape properties from Realtor.com based on a given location and listing type.
|
||||
@@ -22,11 +22,12 @@ def scrape_property(
|
||||
:param listing_type: Listing Type (for_sale, for_rent, sold)
|
||||
:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
|
||||
:param mls_only: If set, fetches only listings with MLS IDs.
|
||||
:param property_younger_than: Get properties sold/listed in last _ days.
|
||||
:param pending_or_contingent: If set, fetches only pending or contingent listings. Only applicable for for_sale listings from general area searches.
|
||||
: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
|
||||
"""
|
||||
validate_input(listing_type)
|
||||
validate_dates(date_from, date_to)
|
||||
|
||||
scraper_input = ScraperInput(
|
||||
location=location,
|
||||
@@ -34,8 +35,9 @@ def scrape_property(
|
||||
proxy=proxy,
|
||||
radius=radius,
|
||||
mls_only=mls_only,
|
||||
last_x_days=property_younger_than,
|
||||
pending_or_contingent=pending_or_contingent,
|
||||
last_x_days=past_days,
|
||||
date_from=date_from,
|
||||
date_to=date_to,
|
||||
)
|
||||
|
||||
site = RealtorScraper(scraper_input)
|
||||
@@ -43,7 +45,7 @@ def scrape_property(
|
||||
|
||||
properties_dfs = [process_result(result) for result in results]
|
||||
if not properties_dfs:
|
||||
raise NoResultsFound("no results found for the query")
|
||||
return pd.DataFrame()
|
||||
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("ignore", category=FutureWarning)
|
||||
|
||||
@@ -14,7 +14,7 @@ def main():
|
||||
"--listing_type",
|
||||
type=str,
|
||||
default="for_sale",
|
||||
choices=["for_sale", "for_rent", "sold"],
|
||||
choices=["for_sale", "for_rent", "sold", "pending"],
|
||||
help="Listing type to scrape",
|
||||
)
|
||||
|
||||
@@ -60,13 +60,6 @@ def main():
|
||||
help="If set, fetches only MLS listings.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"-c",
|
||||
"--pending_or_contingent",
|
||||
action="store_true",
|
||||
help="If set, fetches only pending or contingent listings. Only applicable for for_sale listings from general area searches.",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
result = scrape_property(
|
||||
@@ -75,8 +68,7 @@ def main():
|
||||
radius=args.radius,
|
||||
proxy=args.proxy,
|
||||
mls_only=args.mls_only,
|
||||
property_younger_than=args.days,
|
||||
pending_or_contingent=args.pending_or_contingent,
|
||||
past_days=args.days,
|
||||
)
|
||||
|
||||
if not args.filename:
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
from dataclasses import dataclass
|
||||
import requests
|
||||
import tls_client
|
||||
from .models import Property, ListingType, SiteName
|
||||
|
||||
|
||||
@@ -12,14 +11,15 @@ class ScraperInput:
|
||||
mls_only: bool | None = None
|
||||
proxy: str | None = None
|
||||
last_x_days: int | None = None
|
||||
pending_or_contingent: bool | None = None
|
||||
date_from: str | None = None
|
||||
date_to: str | None = None
|
||||
|
||||
|
||||
class Scraper:
|
||||
def __init__(
|
||||
self,
|
||||
scraper_input: ScraperInput,
|
||||
session: requests.Session | tls_client.Session = None,
|
||||
session: requests.Session = None,
|
||||
):
|
||||
self.location = scraper_input.location
|
||||
self.listing_type = scraper_input.listing_type
|
||||
@@ -38,7 +38,8 @@ class Scraper:
|
||||
self.radius = scraper_input.radius
|
||||
self.last_x_days = scraper_input.last_x_days
|
||||
self.mls_only = scraper_input.mls_only
|
||||
self.pending_or_contingent = scraper_input.pending_or_contingent
|
||||
self.date_from = scraper_input.date_from
|
||||
self.date_to = scraper_input.date_to
|
||||
|
||||
def search(self) -> list[Property]:
|
||||
...
|
||||
|
||||
@@ -19,6 +19,7 @@ class SiteName(Enum):
|
||||
class ListingType(Enum):
|
||||
FOR_SALE = "FOR_SALE"
|
||||
FOR_RENT = "FOR_RENT"
|
||||
PENDING = "PENDING"
|
||||
SOLD = "SOLD"
|
||||
|
||||
|
||||
@@ -58,6 +59,7 @@ class Property:
|
||||
last_sold_date: str | None = None
|
||||
prc_sqft: int | None = None
|
||||
hoa_fee: int | None = None
|
||||
days_on_mls: int | None = None
|
||||
description: Description | None = None
|
||||
|
||||
latitude: float | None = None
|
||||
|
||||
@@ -4,11 +4,11 @@ homeharvest.realtor.__init__
|
||||
|
||||
This module implements the scraper for realtor.com
|
||||
"""
|
||||
from datetime import datetime
|
||||
from typing import Dict, Union, Optional
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
from .. import Scraper
|
||||
from ....exceptions import NoResultsFound
|
||||
from ..models import Property, Address, ListingType, Description
|
||||
|
||||
|
||||
@@ -18,7 +18,6 @@ class RealtorScraper(Scraper):
|
||||
ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
|
||||
|
||||
def __init__(self, scraper_input):
|
||||
self.counter = 1
|
||||
super().__init__(scraper_input)
|
||||
|
||||
def handle_location(self):
|
||||
@@ -38,7 +37,7 @@ class RealtorScraper(Scraper):
|
||||
result = response_json["autocomplete"]
|
||||
|
||||
if not result:
|
||||
raise NoResultsFound("No results found for location: " + self.location)
|
||||
return None
|
||||
|
||||
return result[0]
|
||||
|
||||
@@ -50,6 +49,7 @@ class RealtorScraper(Scraper):
|
||||
listing_id
|
||||
}
|
||||
address {
|
||||
street_direction
|
||||
street_number
|
||||
street_name
|
||||
street_suffix
|
||||
@@ -105,11 +105,29 @@ 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 = datetime.strptime(list_date_str, "%Y-%m-%d") if list_date_str else None
|
||||
last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d") if last_sold_date_str else None
|
||||
today = datetime.now()
|
||||
|
||||
days_on_mls = None
|
||||
status = property_info["basic"]["status"].lower()
|
||||
if list_date:
|
||||
if status == "sold" and last_sold_date:
|
||||
days_on_mls = (last_sold_date - list_date).days
|
||||
elif status in ('for_sale', 'for_rent'):
|
||||
days_on_mls = (today - list_date).days
|
||||
if days_on_mls and days_on_mls < 0:
|
||||
days_on_mls = None
|
||||
|
||||
listing = Property(
|
||||
mls=mls,
|
||||
@@ -119,17 +137,13 @@ class RealtorScraper(Scraper):
|
||||
property_url=f"{self.PROPERTY_URL}{property_info['details']['permalink']}",
|
||||
status=property_info["basic"]["status"].upper(),
|
||||
list_price=property_info["basic"]["price"],
|
||||
list_date=property_info["basic"]["list_date"].split("T")[0]
|
||||
if property_info["basic"].get("list_date")
|
||||
else None,
|
||||
list_date=list_date,
|
||||
prc_sqft=property_info["basic"].get("price")
|
||||
/ property_info["basic"].get("sqft")
|
||||
/ property_info["basic"].get("sqft")
|
||||
if property_info["basic"].get("price")
|
||||
and property_info["basic"].get("sqft")
|
||||
else None,
|
||||
last_sold_date=property_info["basic"]["sold_date"].split("T")[0]
|
||||
if property_info["basic"].get("sold_date")
|
||||
and property_info["basic"].get("sqft")
|
||||
else None,
|
||||
last_sold_date=last_sold_date,
|
||||
latitude=property_info["address"]["location"]["coordinate"].get("lat")
|
||||
if able_to_get_lat_long
|
||||
else None,
|
||||
@@ -149,6 +163,7 @@ class RealtorScraper(Scraper):
|
||||
garage=property_info["details"].get("garage"),
|
||||
stories=property_info["details"].get("stories"),
|
||||
),
|
||||
days_on_mls=days_on_mls
|
||||
)
|
||||
|
||||
return [listing]
|
||||
@@ -201,6 +216,7 @@ class RealtorScraper(Scraper):
|
||||
stories
|
||||
}
|
||||
address {
|
||||
street_direction
|
||||
street_number
|
||||
street_name
|
||||
street_suffix
|
||||
@@ -274,6 +290,10 @@ class RealtorScraper(Scraper):
|
||||
last_sold_date
|
||||
list_price
|
||||
price_per_sqft
|
||||
flags {
|
||||
is_contingent
|
||||
is_pending
|
||||
}
|
||||
description {
|
||||
sqft
|
||||
beds
|
||||
@@ -297,6 +317,7 @@ class RealtorScraper(Scraper):
|
||||
}
|
||||
location {
|
||||
address {
|
||||
street_direction
|
||||
street_number
|
||||
street_name
|
||||
street_suffix
|
||||
@@ -317,15 +338,17 @@ class RealtorScraper(Scraper):
|
||||
}
|
||||
}"""
|
||||
|
||||
date_param = (
|
||||
'sold_date: { min: "$today-%sD" }' % self.last_x_days
|
||||
if self.listing_type == ListingType.SOLD and self.last_x_days
|
||||
else (
|
||||
'list_date: { min: "$today-%sD" }' % self.last_x_days
|
||||
if self.last_x_days
|
||||
else ""
|
||||
)
|
||||
)
|
||||
date_param = ""
|
||||
if self.listing_type == ListingType.SOLD:
|
||||
if self.date_from and self.date_to:
|
||||
date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
|
||||
elif self.last_x_days:
|
||||
date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
|
||||
else:
|
||||
if self.date_from and self.date_to:
|
||||
date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
|
||||
elif self.last_x_days:
|
||||
date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
|
||||
|
||||
sort_param = (
|
||||
"sort: [{ field: sold_date, direction: desc }]"
|
||||
@@ -335,17 +358,19 @@ class RealtorScraper(Scraper):
|
||||
|
||||
pending_or_contingent_param = (
|
||||
"or_filters: { contingent: true, pending: true }"
|
||||
if self.pending_or_contingent
|
||||
if self.listing_type == ListingType.PENDING
|
||||
else ""
|
||||
)
|
||||
|
||||
listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
|
||||
|
||||
if search_type == "comps": #: comps search, came from an address
|
||||
query = """query Property_search(
|
||||
$coordinates: [Float]!
|
||||
$radius: String!
|
||||
$offset: Int!,
|
||||
) {
|
||||
property_search(
|
||||
home_search(
|
||||
query: {
|
||||
nearby: {
|
||||
coordinates: $coordinates
|
||||
@@ -353,13 +378,15 @@ class RealtorScraper(Scraper):
|
||||
}
|
||||
status: %s
|
||||
%s
|
||||
%s
|
||||
}
|
||||
%s
|
||||
limit: 200
|
||||
offset: $offset
|
||||
) %s""" % (
|
||||
self.listing_type.value.lower(),
|
||||
listing_type.value.lower(),
|
||||
date_param,
|
||||
pending_or_contingent_param,
|
||||
sort_param,
|
||||
results_query,
|
||||
)
|
||||
@@ -385,7 +412,7 @@ class RealtorScraper(Scraper):
|
||||
limit: 200
|
||||
offset: $offset
|
||||
) %s""" % (
|
||||
self.listing_type.value.lower(),
|
||||
listing_type.value.lower(),
|
||||
date_param,
|
||||
pending_or_contingent_param,
|
||||
sort_param,
|
||||
@@ -415,7 +442,7 @@ class RealtorScraper(Scraper):
|
||||
response = self.session.post(self.SEARCH_GQL_URL, json=payload)
|
||||
response.raise_for_status()
|
||||
response_json = response.json()
|
||||
search_key = "home_search" if search_type == "area" else "property_search"
|
||||
search_key = "home_search" if "home_search" in query else "property_search"
|
||||
|
||||
properties: list[Property] = []
|
||||
|
||||
@@ -430,7 +457,6 @@ class RealtorScraper(Scraper):
|
||||
return {"total": 0, "properties": []}
|
||||
|
||||
for result in response_json["data"][search_key]["results"]:
|
||||
self.counter += 1
|
||||
mls = (
|
||||
result["source"].get("id")
|
||||
if "source" in result and isinstance(result["source"], dict)
|
||||
@@ -447,13 +473,18 @@ class RealtorScraper(Scraper):
|
||||
and result["location"]["address"].get("coordinate")
|
||||
)
|
||||
|
||||
is_pending = result["flags"].get("is_pending") or result["flags"].get("is_contingent")
|
||||
|
||||
if is_pending and self.listing_type != ListingType.PENDING:
|
||||
continue
|
||||
|
||||
realty_property = Property(
|
||||
mls=mls,
|
||||
mls_id=result["source"].get("listing_id")
|
||||
if "source" in result and isinstance(result["source"], dict)
|
||||
else None,
|
||||
property_url=f"{self.PROPERTY_URL}{result['property_id']}",
|
||||
status=result["status"].upper(),
|
||||
status="PENDING" if is_pending else result["status"].upper(),
|
||||
list_price=result["list_price"],
|
||||
list_date=result["list_date"].split("T")[0]
|
||||
if result.get("list_date")
|
||||
@@ -470,8 +501,8 @@ class RealtorScraper(Scraper):
|
||||
if able_to_get_lat_long
|
||||
else None,
|
||||
address=self._parse_address(result, search_type="general_search"),
|
||||
#: neighborhoods=self._parse_neighborhoods(result),
|
||||
description=self._parse_description(result),
|
||||
days_on_mls=self.calculate_days_on_mls(result)
|
||||
)
|
||||
properties.append(realty_property)
|
||||
|
||||
@@ -482,6 +513,9 @@ class RealtorScraper(Scraper):
|
||||
|
||||
def search(self):
|
||||
location_info = self.handle_location()
|
||||
if not location_info:
|
||||
return []
|
||||
|
||||
location_type = location_info["area_type"]
|
||||
|
||||
search_variables = {
|
||||
@@ -560,21 +594,29 @@ class RealtorScraper(Scraper):
|
||||
return ", ".join(neighborhoods_list) if neighborhoods_list else None
|
||||
|
||||
@staticmethod
|
||||
def _parse_address(result: dict, search_type):
|
||||
def handle_none_safely(address_part):
|
||||
if address_part is None:
|
||||
return ""
|
||||
|
||||
return address_part
|
||||
|
||||
def _parse_address(self, result: dict, search_type):
|
||||
if search_type == "general_search":
|
||||
return Address(
|
||||
street=f"{result['location']['address']['street_number']} {result['location']['address']['street_name']} {result['location']['address']['street_suffix']}",
|
||||
unit=result["location"]["address"]["unit"],
|
||||
city=result["location"]["address"]["city"],
|
||||
state=result["location"]["address"]["state_code"],
|
||||
zip=result["location"]["address"]["postal_code"],
|
||||
)
|
||||
address = result['location']['address']
|
||||
else:
|
||||
address = result["address"]
|
||||
|
||||
return Address(
|
||||
street=f"{result['address']['street_number']} {result['address']['street_name']} {result['address']['street_suffix']}",
|
||||
unit=result["address"]["unit"],
|
||||
city=result["address"]["city"],
|
||||
state=result["address"]["state_code"],
|
||||
zip=result["address"]["postal_code"],
|
||||
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(),
|
||||
unit=address["unit"],
|
||||
city=address["city"],
|
||||
state=address["state_code"],
|
||||
zip=address["postal_code"],
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
@@ -582,7 +624,6 @@ class RealtorScraper(Scraper):
|
||||
description_data = result.get("description", {})
|
||||
|
||||
if description_data is None or not isinstance(description_data, dict):
|
||||
print("Warning: description_data is invalid!")
|
||||
description_data = {}
|
||||
|
||||
style = description_data.get("type", "")
|
||||
@@ -601,3 +642,22 @@ class RealtorScraper(Scraper):
|
||||
garage=description_data.get("garage"),
|
||||
stories=description_data.get("stories"),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def calculate_days_on_mls(result: dict) -> Optional[int]:
|
||||
list_date_str = result.get("list_date")
|
||||
list_date = datetime.strptime(list_date_str.split("T")[0], "%Y-%m-%d") if list_date_str else None
|
||||
last_sold_date_str = result.get("last_sold_date")
|
||||
last_sold_date = datetime.strptime(last_sold_date_str, "%Y-%m-%d") if last_sold_date_str else None
|
||||
today = datetime.now()
|
||||
|
||||
if list_date:
|
||||
if result["status"] == 'sold':
|
||||
if last_sold_date:
|
||||
days = (last_sold_date - list_date).days
|
||||
if days >= 0:
|
||||
return days
|
||||
elif result["status"] in ('for_sale', 'for_rent'):
|
||||
days = (today - list_date).days
|
||||
if days >= 0:
|
||||
return days
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
class InvalidListingType(Exception):
|
||||
"""Raised when a provided listing type is does not exist."""
|
||||
|
||||
|
||||
class NoResultsFound(Exception):
|
||||
"""Raised when no results are found for the given location"""
|
||||
class InvalidDate(Exception):
|
||||
"""Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23 """
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
from .core.scrapers.models import Property, ListingType
|
||||
import pandas as pd
|
||||
from .exceptions import InvalidListingType
|
||||
from datetime import datetime
|
||||
from .core.scrapers.models import Property, ListingType
|
||||
from .exceptions import InvalidListingType, InvalidDate
|
||||
|
||||
ordered_properties = [
|
||||
"property_url",
|
||||
@@ -18,6 +19,7 @@ ordered_properties = [
|
||||
"half_baths",
|
||||
"sqft",
|
||||
"year_built",
|
||||
"days_on_mls",
|
||||
"list_price",
|
||||
"list_date",
|
||||
"sold_price",
|
||||
@@ -69,3 +71,18 @@ def validate_input(listing_type: str) -> None:
|
||||
raise InvalidListingType(
|
||||
f"Provided listing type, '{listing_type}', does not exist."
|
||||
)
|
||||
|
||||
|
||||
def validate_dates(date_from: str | None, date_to: str | None) -> None:
|
||||
if (date_from is not None and date_to is None) or (date_from is None and date_to is not None):
|
||||
raise InvalidDate("Both date_from and date_to must be provided.")
|
||||
|
||||
if date_from and date_to:
|
||||
try:
|
||||
date_from_obj = datetime.strptime(date_from, "%Y-%m-%d")
|
||||
date_to_obj = datetime.strptime(date_to, "%Y-%m-%d")
|
||||
|
||||
if date_to_obj < date_from_obj:
|
||||
raise InvalidDate("date_to must be after date_from.")
|
||||
except ValueError as e:
|
||||
raise InvalidDate(f"Invalid date format or range")
|
||||
|
||||
277
poetry.lock
generated
277
poetry.lock
generated
@@ -13,86 +13,101 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.2.0"
|
||||
version = "3.3.0"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c70087bfee18a42b4040bb9ec1ca15a08242cf5867c58726530bdf3945672ed"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b0dac0ff919ba34d4df1b6131f59ce95b08b9065233446be7e459f95554c0dc8"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:c04a46716adde8d927adb9457bbe39cf473e1e2c2f5d0a16ceb837e5d841ad4f"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:aaf63899c94de41fe3cf934601b0f7ccb6b428c6e4eeb80da72c58eab077b19a"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d62e51710986674142526ab9f78663ca2b0726066ae26b78b22e0f5e571238dd"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-win32.whl", hash = "sha256:04e57ab9fbf9607b77f7d057974694b4f6b142da9ed4a199859d9d4d5c63fe96"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:48021783bdf96e3d6de03a6e39a1171ed5bd7e8bb93fc84cc649d11490f87cea"},
|
||||
{file = "charset_normalizer-3.2.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:4957669ef390f0e6719db3613ab3a7631e68424604a7b448f079bee145da6e09"},
|
||||
{file = "charset_normalizer-3.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:46fb8c61d794b78ec7134a715a3e564aafc8f6b5e338417cb19fe9f57a5a9bf2"},
|
||||
{file = "charset_normalizer-3.2.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f779d3ad205f108d14e99bb3859aa7dd8e9c68874617c72354d7ecaec2a054ac"},
|
||||
{file = "charset_normalizer-3.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f25c229a6ba38a35ae6e25ca1264621cc25d4d38dca2942a7fce0b67a4efe918"},
|
||||
{file = "charset_normalizer-3.2.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2efb1bd13885392adfda4614c33d3b68dee4921fd0ac1d3988f8cbb7d589e72a"},
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[[package]]
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||||
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@@ -244,47 +225,54 @@ et-xmlfile = "*"
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[[package]]
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||||
{file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
|
||||
{file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
|
||||
{file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pandas"
|
||||
version = "2.1.0"
|
||||
version = "2.1.1"
|
||||
description = "Powerful data structures for data analysis, time series, and statistics"
|
||||
optional = false
|
||||
python-versions = ">=3.9"
|
||||
files = [
|
||||
{file = "pandas-2.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:40dd20439ff94f1b2ed55b393ecee9cb6f3b08104c2c40b0cb7186a2f0046242"},
|
||||
{file = "pandas-2.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d4f38e4fedeba580285eaac7ede4f686c6701a9e618d8a857b138a126d067f2f"},
|
||||
{file = "pandas-2.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6e6a0fe052cf27ceb29be9429428b4918f3740e37ff185658f40d8702f0b3e09"},
|
||||
{file = "pandas-2.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d81e1813191070440d4c7a413cb673052b3b4a984ffd86b8dd468c45742d3cc"},
|
||||
{file = "pandas-2.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:eb20252720b1cc1b7d0b2879ffc7e0542dd568f24d7c4b2347cb035206936421"},
|
||||
{file = "pandas-2.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:38f74ef7ebc0ffb43b3d633e23d74882bce7e27bfa09607f3c5d3e03ffd9a4a5"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:cda72cc8c4761c8f1d97b169661f23a86b16fdb240bdc341173aee17e4d6cedd"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d97daeac0db8c993420b10da4f5f5b39b01fc9ca689a17844e07c0a35ac96b4b"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d8c58b1113892e0c8078f006a167cc210a92bdae23322bb4614f2f0b7a4b510f"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:629124923bcf798965b054a540f9ccdfd60f71361255c81fa1ecd94a904b9dd3"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:70cf866af3ab346a10debba8ea78077cf3a8cd14bd5e4bed3d41555a3280041c"},
|
||||
{file = "pandas-2.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:d53c8c1001f6a192ff1de1efe03b31a423d0eee2e9e855e69d004308e046e694"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:86f100b3876b8c6d1a2c66207288ead435dc71041ee4aea789e55ef0e06408cb"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:28f330845ad21c11db51e02d8d69acc9035edfd1116926ff7245c7215db57957"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b9a6ccf0963db88f9b12df6720e55f337447aea217f426a22d71f4213a3099a6"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d99e678180bc59b0c9443314297bddce4ad35727a1a2656dbe585fd78710b3b9"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b31da36d376d50a1a492efb18097b9101bdbd8b3fbb3f49006e02d4495d4c644"},
|
||||
{file = "pandas-2.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:0164b85937707ec7f70b34a6c3a578dbf0f50787f910f21ca3b26a7fd3363437"},
|
||||
{file = "pandas-2.1.0.tar.gz", hash = "sha256:62c24c7fc59e42b775ce0679cfa7b14a5f9bfb7643cfbe708c960699e05fb918"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:58d997dbee0d4b64f3cb881a24f918b5f25dd64ddf31f467bb9b67ae4c63a1e4"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:02304e11582c5d090e5a52aec726f31fe3f42895d6bfc1f28738f9b64b6f0614"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffa8f0966de2c22de408d0e322db2faed6f6e74265aa0856f3824813cf124363"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c1f84c144dee086fe4f04a472b5cd51e680f061adf75c1ae4fc3a9275560f8f4"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:75ce97667d06d69396d72be074f0556698c7f662029322027c226fd7a26965cb"},
|
||||
{file = "pandas-2.1.1-cp310-cp310-win_amd64.whl", hash = "sha256:4c3f32fd7c4dccd035f71734df39231ac1a6ff95e8bdab8d891167197b7018d2"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:9e2959720b70e106bb1d8b6eadd8ecd7c8e99ccdbe03ee03260877184bb2877d"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:25e8474a8eb258e391e30c288eecec565bfed3e026f312b0cbd709a63906b6f8"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b8bd1685556f3374520466998929bade3076aeae77c3e67ada5ed2b90b4de7f0"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dc3657869c7902810f32bd072f0740487f9e030c1a3ab03e0af093db35a9d14e"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:05674536bd477af36aa2effd4ec8f71b92234ce0cc174de34fd21e2ee99adbc2"},
|
||||
{file = "pandas-2.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:b407381258a667df49d58a1b637be33e514b07f9285feb27769cedb3ab3d0b3a"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:c747793c4e9dcece7bb20156179529898abf505fe32cb40c4052107a3c620b49"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3bcad1e6fb34b727b016775bea407311f7721db87e5b409e6542f4546a4951ea"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f5ec7740f9ccb90aec64edd71434711f58ee0ea7f5ed4ac48be11cfa9abf7317"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:29deb61de5a8a93bdd033df328441a79fcf8dd3c12d5ed0b41a395eef9cd76f0"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:4f99bebf19b7e03cf80a4e770a3e65eee9dd4e2679039f542d7c1ace7b7b1daa"},
|
||||
{file = "pandas-2.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:84e7e910096416adec68075dc87b986ff202920fb8704e6d9c8c9897fe7332d6"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:366da7b0e540d1b908886d4feb3d951f2f1e572e655c1160f5fde28ad4abb750"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:9e50e72b667415a816ac27dfcfe686dc5a0b02202e06196b943d54c4f9c7693e"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cc1ab6a25da197f03ebe6d8fa17273126120874386b4ac11c1d687df288542dd"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0dbfea0dd3901ad4ce2306575c54348d98499c95be01b8d885a2737fe4d7a98"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:0489b0e6aa3d907e909aef92975edae89b1ee1654db5eafb9be633b0124abe97"},
|
||||
{file = "pandas-2.1.1-cp39-cp39-win_amd64.whl", hash = "sha256:4cdb0fab0400c2cb46dafcf1a0fe084c8bb2480a1fa8d81e19d15e12e6d4ded2"},
|
||||
{file = "pandas-2.1.1.tar.gz", hash = "sha256:fecb198dc389429be557cde50a2d46da8434a17fe37d7d41ff102e3987fd947b"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = [
|
||||
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
|
||||
{version = ">=1.23.2", markers = "python_version >= \"3.11\""},
|
||||
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
|
||||
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
|
||||
]
|
||||
python-dateutil = ">=2.8.2"
|
||||
pytz = ">=2020.1"
|
||||
@@ -408,17 +396,6 @@ files = [
|
||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tls-client"
|
||||
version = "0.2.2"
|
||||
description = "Advanced Python HTTP Client."
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "tls_client-0.2.2-py3-none-any.whl", hash = "sha256:30934871397cdad6862e00b5634f382666314a452ddd3d774e18323a0ad9b765"},
|
||||
{file = "tls_client-0.2.2.tar.gz", hash = "sha256:78bc0e291e3aadc6c5e903b62bb26c01374577691f2a9e5e17899900a5927a13"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
@@ -443,13 +420,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "2.0.4"
|
||||
version = "2.0.6"
|
||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "urllib3-2.0.4-py3-none-any.whl", hash = "sha256:de7df1803967d2c2a98e4b11bb7d6bd9210474c46e8a0401514e3a42a75ebde4"},
|
||||
{file = "urllib3-2.0.4.tar.gz", hash = "sha256:8d22f86aae8ef5e410d4f539fde9ce6b2113a001bb4d189e0aed70642d602b11"},
|
||||
{file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"},
|
||||
{file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
@@ -460,5 +437,5 @@ zstd = ["zstandard (>=0.18.0)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "9b77e1a09fcf2cf5e7e6be53f304cd21a6a51ea51680d661a178afe5e5343670"
|
||||
python-versions = ">=3.10,<3.13"
|
||||
content-hash = "09ad811d74a42363ff4c3ccd012d8f73c89d7d978e5a6445b0f3d2e231922f1b"
|
||||
|
||||
@@ -1,20 +1,19 @@
|
||||
[tool.poetry]
|
||||
name = "homeharvest"
|
||||
version = "0.3.1"
|
||||
version = "0.3.9"
|
||||
description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
|
||||
authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
|
||||
homepage = "https://github.com/ZacharyHampton/HomeHarvest"
|
||||
homepage = "https://github.com/Bunsly/HomeHarvest"
|
||||
readme = "README.md"
|
||||
|
||||
[tool.poetry.scripts]
|
||||
homeharvest = "homeharvest.cli:main"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.10"
|
||||
python = ">=3.10,<3.13"
|
||||
requests = "^2.31.0"
|
||||
pandas = "^2.1.0"
|
||||
pandas = "^2.1.1"
|
||||
openpyxl = "^3.1.2"
|
||||
tls-client = "^0.2.2"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
||||
@@ -1,20 +1,15 @@
|
||||
from homeharvest import scrape_property
|
||||
from homeharvest.exceptions import (
|
||||
InvalidListingType,
|
||||
NoResultsFound,
|
||||
)
|
||||
|
||||
|
||||
def test_realtor_pending_or_contingent():
|
||||
pending_or_contingent_result = scrape_property(
|
||||
location="Surprise, AZ",
|
||||
pending_or_contingent=True,
|
||||
location="Surprise, AZ", listing_type="pending"
|
||||
)
|
||||
|
||||
regular_result = scrape_property(
|
||||
location="Surprise, AZ",
|
||||
pending_or_contingent=False,
|
||||
)
|
||||
regular_result = scrape_property(location="Surprise, AZ", listing_type="for_sale")
|
||||
|
||||
assert all(
|
||||
[
|
||||
@@ -25,11 +20,50 @@ def test_realtor_pending_or_contingent():
|
||||
assert len(pending_or_contingent_result) != len(regular_result)
|
||||
|
||||
|
||||
def test_realtor_pending_comps():
|
||||
pending_comps = scrape_property(
|
||||
location="2530 Al Lipscomb Way",
|
||||
radius=5,
|
||||
past_days=180,
|
||||
listing_type="pending",
|
||||
)
|
||||
|
||||
for_sale_comps = scrape_property(
|
||||
location="2530 Al Lipscomb Way",
|
||||
radius=5,
|
||||
past_days=180,
|
||||
listing_type="for_sale",
|
||||
)
|
||||
|
||||
sold_comps = scrape_property(
|
||||
location="2530 Al Lipscomb Way",
|
||||
radius=5,
|
||||
past_days=180,
|
||||
listing_type="sold",
|
||||
)
|
||||
|
||||
results = [pending_comps, for_sale_comps, sold_comps]
|
||||
assert all([result is not None for result in results])
|
||||
|
||||
#: assert all lengths are different
|
||||
assert len(set([len(result) for result in results])) == len(results)
|
||||
|
||||
|
||||
def test_realtor_sold_past():
|
||||
result = scrape_property(
|
||||
location="San Diego, CA",
|
||||
past_days=30,
|
||||
listing_type="sold",
|
||||
)
|
||||
|
||||
assert result is not None and len(result) > 0
|
||||
|
||||
|
||||
def test_realtor_comps():
|
||||
result = scrape_property(
|
||||
location="2530 Al Lipscomb Way",
|
||||
radius=0.5,
|
||||
property_younger_than=180,
|
||||
past_days=180,
|
||||
listing_type="sold",
|
||||
)
|
||||
|
||||
@@ -38,11 +72,11 @@ def test_realtor_comps():
|
||||
|
||||
def test_realtor_last_x_days_sold():
|
||||
days_result_30 = scrape_property(
|
||||
location="Dallas, TX", listing_type="sold", property_younger_than=30
|
||||
location="Dallas, TX", listing_type="sold", past_days=30
|
||||
)
|
||||
|
||||
days_result_10 = scrape_property(
|
||||
location="Dallas, TX", listing_type="sold", property_younger_than=10
|
||||
location="Dallas, TX", listing_type="sold", past_days=10
|
||||
)
|
||||
|
||||
assert all(
|
||||
@@ -50,6 +84,20 @@ def test_realtor_last_x_days_sold():
|
||||
) and len(days_result_30) != len(days_result_10)
|
||||
|
||||
|
||||
def test_realtor_date_range_sold():
|
||||
days_result_30 = scrape_property(
|
||||
location="Dallas, TX", listing_type="sold", date_from="2023-05-01", date_to="2023-05-28"
|
||||
)
|
||||
|
||||
days_result_60 = scrape_property(
|
||||
location="Dallas, TX", listing_type="sold", date_from="2023-04-01", date_to="2023-06-10"
|
||||
)
|
||||
|
||||
assert all(
|
||||
[result is not None for result in [days_result_30, days_result_60]]
|
||||
) and len(days_result_30) < len(days_result_60)
|
||||
|
||||
|
||||
def test_realtor_single_property():
|
||||
results = [
|
||||
scrape_property(
|
||||
@@ -82,15 +130,12 @@ def test_realtor():
|
||||
|
||||
assert all([result is not None for result in results])
|
||||
|
||||
bad_results = []
|
||||
try:
|
||||
bad_results += [
|
||||
scrape_property(
|
||||
location="abceefg ju098ot498hh9",
|
||||
listing_type="for_sale",
|
||||
)
|
||||
]
|
||||
except (InvalidListingType, NoResultsFound):
|
||||
|
||||
def test_realtor_bad_address():
|
||||
bad_results = scrape_property(
|
||||
location="abceefg ju098ot498hh9",
|
||||
listing_type="for_sale",
|
||||
)
|
||||
if len(bad_results) == 0:
|
||||
assert True
|
||||
|
||||
assert all([result is None for result in bad_results])
|
||||
|
||||
Reference in New Issue
Block a user