Compare commits
No commits in common. "master" and "v0.1.3" have entirely different histories.
|
|
@ -1 +0,0 @@
|
||||||
github: Bunsly
|
|
||||||
|
|
@ -30,4 +30,4 @@ jobs:
|
||||||
if: startsWith(github.ref, 'refs/tags')
|
if: startsWith(github.ref, 'refs/tags')
|
||||||
uses: pypa/gh-action-pypi-publish@release/v1
|
uses: pypa/gh-action-pypi-publish@release/v1
|
||||||
with:
|
with:
|
||||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||||
|
|
@ -3,5 +3,4 @@
|
||||||
**/__pycache__/
|
**/__pycache__/
|
||||||
**/.pytest_cache/
|
**/.pytest_cache/
|
||||||
*.pyc
|
*.pyc
|
||||||
/.ipynb_checkpoints/
|
/.ipynb_checkpoints/
|
||||||
*.csv
|
|
||||||
|
|
@ -1,21 +0,0 @@
|
||||||
---
|
|
||||||
repos:
|
|
||||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
|
||||||
rev: v4.2.0
|
|
||||||
hooks:
|
|
||||||
- id: trailing-whitespace
|
|
||||||
- id: end-of-file-fixer
|
|
||||||
- id: check-added-large-files
|
|
||||||
- id: check-yaml
|
|
||||||
- repo: https://github.com/adrienverge/yamllint
|
|
||||||
rev: v1.29.0
|
|
||||||
hooks:
|
|
||||||
- id: yamllint
|
|
||||||
verbose: true # create awareness of linter findings
|
|
||||||
args: ["-d", "{extends: relaxed, rules: {line-length: {max: 120}}}"]
|
|
||||||
- repo: https://github.com/psf/black
|
|
||||||
rev: 24.2.0
|
|
||||||
hooks:
|
|
||||||
- id: black
|
|
||||||
language_version: python
|
|
||||||
args: [--line-length=120, --quiet]
|
|
||||||
|
|
@ -0,0 +1,73 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "cb48903e-5021-49fe-9688-45cd0bc05d0f",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from homeharvest import scrape_property\n",
|
||||||
|
"import pandas as pd"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "156488ce-0d5f-43c5-87f4-c33e9c427860",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"pd.set_option('display.max_columns', None) # Show all columns\n",
|
||||||
|
"pd.set_option('display.max_rows', None) # Show all rows\n",
|
||||||
|
"pd.set_option('display.width', None) # Auto-adjust display width to fit console\n",
|
||||||
|
"pd.set_option('display.max_colwidth', 50) # Limit max column width to 50 characters"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "1c8b9744-8606-4e9b-8add-b90371a249a7",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"scrape_property(\n",
|
||||||
|
" location=\"dallas\", site_name=\"zillow\", listing_type=\"for_sale\"\n",
|
||||||
|
")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "ab7b4c21-da1d-4713-9df4-d7425d8ce21e",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"scrape_property(\n",
|
||||||
|
" location=\"dallas\", site_name=\"redfin\", listing_type=\"for_sale\"\n",
|
||||||
|
")"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.10.11"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
197
README.md
197
README.md
|
|
@ -1,198 +1,33 @@
|
||||||
<img src="https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/d1a2bf8b-09f5-4c57-b33a-0ada8a34f12d" width="400">
|
# HomeHarvest
|
||||||
|
|
||||||
**HomeHarvest** is a real estate scraping library that extracts and formats data in the style of MLS listings.
|
**HomeHarvest** aims to be the top Python real estate scraping library.
|
||||||
|
|
||||||
## HomeHarvest Features
|
_**Under Consideration**: We're looking into the possibility of an Excel plugin to cater to a broader audience._
|
||||||
|
|
||||||
- **Source**: Fetches properties directly from **Realtor.com**.
|
|
||||||
- **Data Format**: Structures data to resemble MLS listings.
|
|
||||||
- **Export Flexibility**: Options to save as either CSV or Excel.
|
|
||||||
|
|
||||||
[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
## Installation
|
## Installation
|
||||||
|
|
||||||
```bash
|
```bash
|
||||||
pip install -U homeharvest
|
pip install --upgrade homeharvest
|
||||||
```
|
```
|
||||||
_Python version >= [3.9](https://www.python.org/downloads/release/python-3100/) required_
|
|
||||||
|
|
||||||
## Usage
|
## Example Usage
|
||||||
|
```
|
||||||
### Python
|
|
||||||
|
|
||||||
```py
|
|
||||||
from homeharvest import scrape_property
|
from homeharvest import scrape_property
|
||||||
from datetime import datetime
|
|
||||||
|
|
||||||
# Generate filename based on current timestamp
|
|
||||||
current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
|
||||||
filename = f"HomeHarvest_{current_timestamp}.csv"
|
|
||||||
|
|
||||||
properties = scrape_property(
|
properties = scrape_property(
|
||||||
location="San Diego, CA",
|
location="85281", site_name="zillow", listing_type="for_rent"
|
||||||
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)
|
|
||||||
|
|
||||||
# property_type=['single_family','multi_family'],
|
|
||||||
# date_from="2023-05-01", # alternative to past_days
|
|
||||||
# date_to="2023-05-28",
|
|
||||||
# foreclosure=True
|
|
||||||
# mls_only=True, # only fetch MLS listings
|
|
||||||
)
|
)
|
||||||
print(f"Number of properties: {len(properties)}")
|
print(properties)
|
||||||
|
|
||||||
# Export to csv
|
|
||||||
properties.to_csv(filename, index=False)
|
|
||||||
print(properties.head())
|
|
||||||
```
|
```
|
||||||
|
|
||||||
## Output
|
### Site Name Options
|
||||||
```plaintext
|
|
||||||
>>> properties.head()
|
|
||||||
MLS MLS # Status Style ... COEDate LotSFApx PrcSqft Stories
|
|
||||||
0 SDCA 230018348 SOLD CONDOS ... 2023-10-03 290110 803 2
|
|
||||||
1 SDCA 230016614 SOLD TOWNHOMES ... 2023-10-03 None 838 3
|
|
||||||
2 SDCA 230016367 SOLD CONDOS ... 2023-10-03 30056 649 1
|
|
||||||
3 MRCA NDP2306335 SOLD SINGLE_FAMILY ... 2023-10-03 7519 661 2
|
|
||||||
4 SDCA 230014532 SOLD CONDOS ... 2023-10-03 None 752 1
|
|
||||||
[5 rows x 22 columns]
|
|
||||||
```
|
|
||||||
|
|
||||||
### Parameters for `scrape_property()`
|
- `zillow`
|
||||||
```
|
- `redfin`
|
||||||
Required
|
- `realtor.com`
|
||||||
├── location (str): The address in various formats - this could be just a zip code, a full address, or city/state, etc.
|
|
||||||
├── listing_type (option): Choose the type of listing.
|
|
||||||
- 'for_rent'
|
|
||||||
- 'for_sale'
|
|
||||||
- 'sold'
|
|
||||||
- 'pending' (for pending/contingent sales)
|
|
||||||
|
|
||||||
Optional
|
### Listing Types
|
||||||
├── property_type (list): Choose the type of properties.
|
|
||||||
- 'single_family'
|
|
||||||
- 'multi_family'
|
|
||||||
- 'condos'
|
|
||||||
- 'condo_townhome_rowhome_coop'
|
|
||||||
- 'condo_townhome'
|
|
||||||
- 'townhomes'
|
|
||||||
- 'duplex_triplex'
|
|
||||||
- 'farm'
|
|
||||||
- 'land'
|
|
||||||
- 'mobile'
|
|
||||||
│
|
|
||||||
├── return_type (option): Choose the return type.
|
|
||||||
│ - 'pandas' (default)
|
|
||||||
│ - 'pydantic'
|
|
||||||
│ - 'raw' (json)
|
|
||||||
│
|
|
||||||
├── radius (decimal): Radius in miles to find comparable properties based on individual addresses.
|
|
||||||
│ Example: 5.5 (fetches properties within a 5.5-mile radius if location is set to a specific address; otherwise, ignored)
|
|
||||||
│
|
|
||||||
├── past_days (integer): Number of past days to filter properties. Utilizes 'last_sold_date' for 'sold' listing types, and 'list_date' for others (for_rent, for_sale).
|
|
||||||
│ Example: 30 (fetches properties listed/sold in the last 30 days)
|
|
||||||
│
|
|
||||||
├── 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)
|
|
||||||
│
|
|
||||||
├── foreclosure (True/False): If set, fetches only foreclosures
|
|
||||||
│
|
|
||||||
├── proxy (string): In format 'http://user:pass@host:port'
|
|
||||||
│
|
|
||||||
├── extra_property_data (True/False): Increases requests by O(n). If set, this fetches additional property data for general searches (e.g. schools, tax appraisals etc.)
|
|
||||||
│
|
|
||||||
├── exclude_pending (True/False): If set, excludes 'pending' properties from the 'for_sale' results unless listing_type is 'pending'
|
|
||||||
│
|
|
||||||
└── limit (integer): Limit the number of properties to fetch. Max & default is 10000.
|
|
||||||
```
|
|
||||||
|
|
||||||
### Property Schema
|
- `for_rent`
|
||||||
```plaintext
|
- `for_sale`
|
||||||
Property
|
- `sold`
|
||||||
├── Basic Information:
|
|
||||||
│ ├── property_url
|
|
||||||
│ ├── property_id
|
|
||||||
│ ├── listing_id
|
|
||||||
│ ├── mls
|
|
||||||
│ ├── mls_id
|
|
||||||
│ └── status
|
|
||||||
|
|
||||||
├── Address Details:
|
|
||||||
│ ├── street
|
|
||||||
│ ├── unit
|
|
||||||
│ ├── city
|
|
||||||
│ ├── state
|
|
||||||
│ └── zip_code
|
|
||||||
|
|
||||||
├── Property Description:
|
|
||||||
│ ├── style
|
|
||||||
│ ├── beds
|
|
||||||
│ ├── full_baths
|
|
||||||
│ ├── half_baths
|
|
||||||
│ ├── sqft
|
|
||||||
│ ├── year_built
|
|
||||||
│ ├── stories
|
|
||||||
│ ├── garage
|
|
||||||
│ └── lot_sqft
|
|
||||||
|
|
||||||
├── Property Listing Details:
|
|
||||||
│ ├── days_on_mls
|
|
||||||
│ ├── list_price
|
|
||||||
│ ├── list_price_min
|
|
||||||
│ ├── list_price_max
|
|
||||||
│ ├── list_date
|
|
||||||
│ ├── pending_date
|
|
||||||
│ ├── sold_price
|
|
||||||
│ ├── last_sold_date
|
|
||||||
│ ├── price_per_sqft
|
|
||||||
│ ├── new_construction
|
|
||||||
│ └── hoa_fee
|
|
||||||
|
|
||||||
├── Tax Information:
|
|
||||||
│ ├── year
|
|
||||||
│ ├── tax
|
|
||||||
│ ├── assessment
|
|
||||||
│ │ ├── building
|
|
||||||
│ │ ├── land
|
|
||||||
│ │ └── total
|
|
||||||
|
|
||||||
├── Location Details:
|
|
||||||
│ ├── latitude
|
|
||||||
│ ├── longitude
|
|
||||||
│ ├── nearby_schools
|
|
||||||
|
|
||||||
├── Agent Info:
|
|
||||||
│ ├── agent_id
|
|
||||||
│ ├── agent_name
|
|
||||||
│ ├── agent_email
|
|
||||||
│ └── agent_phone
|
|
||||||
|
|
||||||
├── Broker Info:
|
|
||||||
│ ├── broker_id
|
|
||||||
│ └── broker_name
|
|
||||||
|
|
||||||
├── Builder Info:
|
|
||||||
│ ├── builder_id
|
|
||||||
│ └── builder_name
|
|
||||||
|
|
||||||
├── Office Info:
|
|
||||||
│ ├── office_id
|
|
||||||
│ ├── office_name
|
|
||||||
│ ├── office_phones
|
|
||||||
│ └── office_email
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
### Exceptions
|
|
||||||
The following exceptions may be raised when using HomeHarvest:
|
|
||||||
|
|
||||||
- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`, `pending`.
|
|
||||||
- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD.
|
|
||||||
- `AuthenticationError` - Realtor.com token request failed.
|
|
||||||
|
|
|
||||||
|
|
@ -1,104 +0,0 @@
|
||||||
"""
|
|
||||||
This script scrapes sold and pending sold land listings in past year for a list of zip codes and saves the data to individual Excel files.
|
|
||||||
It adds two columns to the data: 'lot_acres' and 'ppa' (price per acre) for user to analyze average price of land in a zip code.
|
|
||||||
"""
|
|
||||||
|
|
||||||
import os
|
|
||||||
import pandas as pd
|
|
||||||
from homeharvest import scrape_property
|
|
||||||
|
|
||||||
|
|
||||||
def get_property_details(zip: str, listing_type):
|
|
||||||
properties = scrape_property(location=zip, listing_type=listing_type, property_type=["land"], past_days=365)
|
|
||||||
if not properties.empty:
|
|
||||||
properties["lot_acres"] = properties["lot_sqft"].apply(lambda x: x / 43560 if pd.notnull(x) else None)
|
|
||||||
|
|
||||||
properties = properties[properties["sqft"].isnull()]
|
|
||||||
properties["ppa"] = properties.apply(
|
|
||||||
lambda row: (
|
|
||||||
int(
|
|
||||||
(
|
|
||||||
row["sold_price"]
|
|
||||||
if (pd.notnull(row["sold_price"]) and row["status"] == "SOLD")
|
|
||||||
else row["list_price"]
|
|
||||||
)
|
|
||||||
/ row["lot_acres"]
|
|
||||||
)
|
|
||||||
if pd.notnull(row["lot_acres"])
|
|
||||||
and row["lot_acres"] > 0
|
|
||||||
and (pd.notnull(row["sold_price"]) or pd.notnull(row["list_price"]))
|
|
||||||
else None
|
|
||||||
),
|
|
||||||
axis=1,
|
|
||||||
)
|
|
||||||
properties["ppa"] = properties["ppa"].astype("Int64")
|
|
||||||
selected_columns = [
|
|
||||||
"property_url",
|
|
||||||
"property_id",
|
|
||||||
"style",
|
|
||||||
"status",
|
|
||||||
"street",
|
|
||||||
"city",
|
|
||||||
"state",
|
|
||||||
"zip_code",
|
|
||||||
"county",
|
|
||||||
"list_date",
|
|
||||||
"last_sold_date",
|
|
||||||
"list_price",
|
|
||||||
"sold_price",
|
|
||||||
"lot_sqft",
|
|
||||||
"lot_acres",
|
|
||||||
"ppa",
|
|
||||||
]
|
|
||||||
properties = properties[selected_columns]
|
|
||||||
return properties
|
|
||||||
|
|
||||||
|
|
||||||
def output_to_excel(zip_code, sold_df, pending_df):
|
|
||||||
root_folder = os.getcwd()
|
|
||||||
zip_folder = os.path.join(root_folder, "zips", zip_code)
|
|
||||||
|
|
||||||
# Create zip code folder if it doesn't exist
|
|
||||||
os.makedirs(zip_folder, exist_ok=True)
|
|
||||||
|
|
||||||
# Define file paths
|
|
||||||
sold_file = os.path.join(zip_folder, f"{zip_code}_sold.xlsx")
|
|
||||||
pending_file = os.path.join(zip_folder, f"{zip_code}_pending.xlsx")
|
|
||||||
|
|
||||||
# Save individual sold and pending files
|
|
||||||
sold_df.to_excel(sold_file, index=False)
|
|
||||||
pending_df.to_excel(pending_file, index=False)
|
|
||||||
|
|
||||||
|
|
||||||
zip_codes = map(
|
|
||||||
str,
|
|
||||||
[
|
|
||||||
22920,
|
|
||||||
77024,
|
|
||||||
78028,
|
|
||||||
24553,
|
|
||||||
22967,
|
|
||||||
22971,
|
|
||||||
22922,
|
|
||||||
22958,
|
|
||||||
22969,
|
|
||||||
22949,
|
|
||||||
22938,
|
|
||||||
24599,
|
|
||||||
24562,
|
|
||||||
22976,
|
|
||||||
24464,
|
|
||||||
22964,
|
|
||||||
24581,
|
|
||||||
],
|
|
||||||
)
|
|
||||||
|
|
||||||
combined_df = pd.DataFrame()
|
|
||||||
for zip in zip_codes:
|
|
||||||
sold_df = get_property_details(zip, "sold")
|
|
||||||
pending_df = get_property_details(zip, "pending")
|
|
||||||
combined_df = pd.concat([combined_df, sold_df, pending_df], ignore_index=True)
|
|
||||||
output_to_excel(zip, sold_df, pending_df)
|
|
||||||
|
|
||||||
combined_file = os.path.join(os.getcwd(), "zips", "combined.xlsx")
|
|
||||||
combined_df.to_excel(combined_file, index=False)
|
|
||||||
|
|
@ -1,77 +1,117 @@
|
||||||
import warnings
|
from .core.scrapers.redfin import RedfinScraper
|
||||||
import pandas as pd
|
|
||||||
from .core.scrapers import ScraperInput
|
|
||||||
from .utils import process_result, ordered_properties, validate_input, validate_dates, validate_limit
|
|
||||||
from .core.scrapers.realtor import RealtorScraper
|
from .core.scrapers.realtor import RealtorScraper
|
||||||
from .core.scrapers.models import ListingType, SearchPropertyType, ReturnType, Property
|
from .core.scrapers.zillow import ZillowScraper
|
||||||
|
from .core.scrapers.models import ListingType, Property, Building, SiteName
|
||||||
|
from .core.scrapers import ScraperInput
|
||||||
|
from .exceptions import InvalidSite, InvalidListingType
|
||||||
|
from typing import Union
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
|
||||||
|
_scrapers = {
|
||||||
|
"redfin": RedfinScraper,
|
||||||
|
"realtor.com": RealtorScraper,
|
||||||
|
"zillow": ZillowScraper,
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def validate_input(site_name: str, listing_type: str) -> None:
|
||||||
|
if site_name.lower() not in _scrapers:
|
||||||
|
raise InvalidSite(f"Provided site, '{site_name}', does not exist.")
|
||||||
|
|
||||||
|
if listing_type.upper() not in ListingType.__members__:
|
||||||
|
raise InvalidListingType(
|
||||||
|
f"Provided listing type, '{listing_type}', does not exist."
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def get_ordered_properties(result: Union[Building, Property]) -> list[str]:
|
||||||
|
if isinstance(result, Property):
|
||||||
|
return [
|
||||||
|
"listing_type",
|
||||||
|
"address_one",
|
||||||
|
"city",
|
||||||
|
"state",
|
||||||
|
"zip_code",
|
||||||
|
"address_two",
|
||||||
|
"url",
|
||||||
|
"property_type",
|
||||||
|
"price",
|
||||||
|
"beds",
|
||||||
|
"baths",
|
||||||
|
"square_feet",
|
||||||
|
"price_per_square_foot",
|
||||||
|
"lot_size",
|
||||||
|
"stories",
|
||||||
|
"year_built",
|
||||||
|
"agent_name",
|
||||||
|
"mls_id",
|
||||||
|
"description",
|
||||||
|
]
|
||||||
|
elif isinstance(result, Building):
|
||||||
|
return [
|
||||||
|
"address_one",
|
||||||
|
"city",
|
||||||
|
"state",
|
||||||
|
"zip_code",
|
||||||
|
"address_two",
|
||||||
|
"url",
|
||||||
|
"num_units",
|
||||||
|
"min_unit_price",
|
||||||
|
"max_unit_price",
|
||||||
|
"avg_unit_price",
|
||||||
|
"listing_type",
|
||||||
|
]
|
||||||
|
return []
|
||||||
|
|
||||||
|
|
||||||
|
def process_result(result: Union[Building, Property]) -> pd.DataFrame:
|
||||||
|
prop_data = result.__dict__
|
||||||
|
|
||||||
|
address_data = prop_data["address"]
|
||||||
|
prop_data["site_name"] = prop_data["site_name"]
|
||||||
|
prop_data["listing_type"] = prop_data["listing_type"].value
|
||||||
|
prop_data["property_type"] = prop_data["property_type"].value.lower() if prop_data.get("property_type") else None
|
||||||
|
prop_data["address_one"] = address_data.address_one
|
||||||
|
prop_data["city"] = address_data.city
|
||||||
|
prop_data["state"] = address_data.state
|
||||||
|
prop_data["zip_code"] = address_data.zip_code
|
||||||
|
prop_data["address_two"] = address_data.address_two
|
||||||
|
|
||||||
|
del prop_data["address"]
|
||||||
|
|
||||||
|
properties_df = pd.DataFrame([prop_data])
|
||||||
|
properties_df = properties_df[get_ordered_properties(result)]
|
||||||
|
|
||||||
|
return properties_df
|
||||||
|
|
||||||
|
|
||||||
def scrape_property(
|
def scrape_property(
|
||||||
location: str,
|
location: str,
|
||||||
listing_type: str = "for_sale",
|
site_name: str,
|
||||||
return_type: str = "pandas",
|
listing_type: str = "for_sale", #: for_sale, for_rent, sold
|
||||||
property_type: list[str] | None = None,
|
) -> pd.DataFrame:
|
||||||
radius: float = None,
|
|
||||||
mls_only: bool = False,
|
|
||||||
past_days: int = None,
|
|
||||||
proxy: str = None,
|
|
||||||
date_from: str = None, #: TODO: Switch to one parameter, Date, with date_from and date_to, pydantic validation
|
|
||||||
date_to: str = None,
|
|
||||||
foreclosure: bool = None,
|
|
||||||
extra_property_data: bool = True,
|
|
||||||
exclude_pending: bool = False,
|
|
||||||
limit: int = 10000
|
|
||||||
) -> pd.DataFrame | list[dict] | list[Property]:
|
|
||||||
"""
|
"""
|
||||||
Scrape properties from Realtor.com based on a given location and listing type.
|
Scrape property from various sites from a given location and listing type.
|
||||||
:param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")
|
|
||||||
:param listing_type: Listing Type (for_sale, for_rent, sold, pending)
|
:returns: pd.DataFrame
|
||||||
:param return_type: Return type (pandas, pydantic, raw)
|
:param location: US Location (e.g. 'San Francisco, CA', 'Cook County, IL', '85281', '2530 Al Lipscomb Way')
|
||||||
:param property_type: Property Type (single_family, multi_family, condos, condo_townhome_rowhome_coop, condo_townhome, townhomes, duplex_triplex, farm, land, mobile)
|
:param site_name: Site name (e.g. 'realtor.com', 'zillow', 'redfin')
|
||||||
:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
|
:param listing_type: Listing type (e.g. 'for_sale', 'for_rent', 'sold')
|
||||||
:param mls_only: If set, fetches only listings with MLS IDs.
|
:return: pd.DataFrame containing properties
|
||||||
: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 foreclosure: If set, fetches only foreclosure listings.
|
|
||||||
:param extra_property_data: Increases requests by O(n). If set, this fetches additional property data (e.g. agent, broker, property evaluations etc.)
|
|
||||||
:param exclude_pending: If true, this excludes pending or contingent properties from the results, unless listing type is pending.
|
|
||||||
:param limit: Limit the number of results returned. Maximum is 10,000.
|
|
||||||
"""
|
"""
|
||||||
validate_input(listing_type)
|
|
||||||
validate_dates(date_from, date_to)
|
validate_input(site_name, listing_type)
|
||||||
validate_limit(limit)
|
|
||||||
|
|
||||||
scraper_input = ScraperInput(
|
scraper_input = ScraperInput(
|
||||||
location=location,
|
location=location,
|
||||||
listing_type=ListingType(listing_type.upper()),
|
listing_type=ListingType[listing_type.upper()],
|
||||||
return_type=ReturnType(return_type.lower()),
|
site_name=site_name.lower(),
|
||||||
property_type=[SearchPropertyType[prop.upper()] for prop in property_type] if property_type else None,
|
|
||||||
proxy=proxy,
|
|
||||||
radius=radius,
|
|
||||||
mls_only=mls_only,
|
|
||||||
last_x_days=past_days,
|
|
||||||
date_from=date_from,
|
|
||||||
date_to=date_to,
|
|
||||||
foreclosure=foreclosure,
|
|
||||||
extra_property_data=extra_property_data,
|
|
||||||
exclude_pending=exclude_pending,
|
|
||||||
limit=limit,
|
|
||||||
)
|
)
|
||||||
|
|
||||||
site = RealtorScraper(scraper_input)
|
site = _scrapers[site_name.lower()](scraper_input)
|
||||||
results = site.search()
|
results = site.search()
|
||||||
|
|
||||||
if scraper_input.return_type != ReturnType.pandas:
|
properties_dfs = [process_result(result) for result in results]
|
||||||
return results
|
|
||||||
|
|
||||||
properties_dfs = [df for result in results if not (df := process_result(result)).empty]
|
return pd.concat(properties_dfs, ignore_index=True)
|
||||||
if not properties_dfs:
|
|
||||||
return pd.DataFrame()
|
|
||||||
|
|
||||||
with warnings.catch_warnings():
|
|
||||||
warnings.simplefilter("ignore", category=FutureWarning)
|
|
||||||
|
|
||||||
return pd.concat(properties_dfs, ignore_index=True, axis=0)[ordered_properties].replace(
|
|
||||||
{"None": pd.NA, None: pd.NA, "": pd.NA}
|
|
||||||
)
|
|
||||||
|
|
|
||||||
|
|
@ -1,85 +0,0 @@
|
||||||
import argparse
|
|
||||||
import datetime
|
|
||||||
from homeharvest import scrape_property
|
|
||||||
|
|
||||||
|
|
||||||
def main():
|
|
||||||
parser = argparse.ArgumentParser(description="Home Harvest Property Scraper")
|
|
||||||
parser.add_argument("location", type=str, help="Location to scrape (e.g., San Francisco, CA)")
|
|
||||||
|
|
||||||
parser.add_argument(
|
|
||||||
"-l",
|
|
||||||
"--listing_type",
|
|
||||||
type=str,
|
|
||||||
default="for_sale",
|
|
||||||
choices=["for_sale", "for_rent", "sold", "pending"],
|
|
||||||
help="Listing type to scrape",
|
|
||||||
)
|
|
||||||
|
|
||||||
parser.add_argument(
|
|
||||||
"-o",
|
|
||||||
"--output",
|
|
||||||
type=str,
|
|
||||||
default="excel",
|
|
||||||
choices=["excel", "csv"],
|
|
||||||
help="Output format",
|
|
||||||
)
|
|
||||||
|
|
||||||
parser.add_argument(
|
|
||||||
"-f",
|
|
||||||
"--filename",
|
|
||||||
type=str,
|
|
||||||
default=None,
|
|
||||||
help="Name of the output file (without extension)",
|
|
||||||
)
|
|
||||||
|
|
||||||
parser.add_argument("-p", "--proxy", type=str, default=None, help="Proxy to use for scraping")
|
|
||||||
parser.add_argument(
|
|
||||||
"-d",
|
|
||||||
"--days",
|
|
||||||
type=int,
|
|
||||||
default=None,
|
|
||||||
help="Sold/listed in last _ days filter.",
|
|
||||||
)
|
|
||||||
|
|
||||||
parser.add_argument(
|
|
||||||
"-r",
|
|
||||||
"--radius",
|
|
||||||
type=float,
|
|
||||||
default=None,
|
|
||||||
help="Get comparable properties within _ (eg. 0.0) miles. Only applicable for individual addresses.",
|
|
||||||
)
|
|
||||||
parser.add_argument(
|
|
||||||
"-m",
|
|
||||||
"--mls_only",
|
|
||||||
action="store_true",
|
|
||||||
help="If set, fetches only MLS listings.",
|
|
||||||
)
|
|
||||||
|
|
||||||
args = parser.parse_args()
|
|
||||||
|
|
||||||
result = scrape_property(
|
|
||||||
args.location,
|
|
||||||
args.listing_type,
|
|
||||||
radius=args.radius,
|
|
||||||
proxy=args.proxy,
|
|
||||||
mls_only=args.mls_only,
|
|
||||||
past_days=args.days,
|
|
||||||
)
|
|
||||||
|
|
||||||
if not args.filename:
|
|
||||||
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
|
|
||||||
args.filename = f"HomeHarvest_{timestamp}"
|
|
||||||
|
|
||||||
if args.output == "excel":
|
|
||||||
output_filename = f"{args.filename}.xlsx"
|
|
||||||
result.to_excel(output_filename, index=False)
|
|
||||||
print(f"Excel file saved as {output_filename}")
|
|
||||||
elif args.output == "csv":
|
|
||||||
output_filename = f"{args.filename}.csv"
|
|
||||||
result.to_csv(output_filename, index=False)
|
|
||||||
print(f"CSV file saved as {output_filename}")
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
main()
|
|
||||||
|
|
@ -1,128 +1,37 @@
|
||||||
from __future__ import annotations
|
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass
|
||||||
from typing import Union
|
|
||||||
|
|
||||||
import requests
|
import requests
|
||||||
from requests.adapters import HTTPAdapter
|
from .models import Property, ListingType, SiteName
|
||||||
from urllib3.util.retry import Retry
|
|
||||||
import uuid
|
|
||||||
from ...exceptions import AuthenticationError
|
|
||||||
from .models import Property, ListingType, SiteName, SearchPropertyType, ReturnType
|
|
||||||
import json
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
class ScraperInput:
|
class ScraperInput:
|
||||||
location: str
|
location: str
|
||||||
listing_type: ListingType
|
listing_type: ListingType
|
||||||
property_type: list[SearchPropertyType] | None = None
|
site_name: str
|
||||||
radius: float | None = None
|
proxy_url: str | 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 = False
|
|
||||||
extra_property_data: bool | None = True
|
|
||||||
exclude_pending: bool | None = False
|
|
||||||
limit: int = 10000
|
|
||||||
return_type: ReturnType = ReturnType.pandas
|
|
||||||
|
|
||||||
|
|
||||||
class Scraper:
|
class Scraper:
|
||||||
session = None
|
def __init__(self, scraper_input: ScraperInput):
|
||||||
|
|
||||||
def __init__(
|
|
||||||
self,
|
|
||||||
scraper_input: ScraperInput,
|
|
||||||
):
|
|
||||||
self.location = scraper_input.location
|
self.location = scraper_input.location
|
||||||
self.listing_type = scraper_input.listing_type
|
self.listing_type = scraper_input.listing_type
|
||||||
self.property_type = scraper_input.property_type
|
|
||||||
|
|
||||||
if not self.session:
|
|
||||||
Scraper.session = requests.Session()
|
|
||||||
retries = Retry(
|
|
||||||
total=3, backoff_factor=4, status_forcelist=[429, 403], allowed_methods=frozenset(["GET", "POST"])
|
|
||||||
)
|
|
||||||
|
|
||||||
adapter = HTTPAdapter(max_retries=retries)
|
|
||||||
Scraper.session.mount("http://", adapter)
|
|
||||||
Scraper.session.mount("https://", adapter)
|
|
||||||
Scraper.session.headers.update(
|
|
||||||
{
|
|
||||||
"accept": "application/json, text/javascript",
|
|
||||||
"accept-language": "en-US,en;q=0.9",
|
|
||||||
"cache-control": "no-cache",
|
|
||||||
"content-type": "application/json",
|
|
||||||
"origin": "https://www.realtor.com",
|
|
||||||
"pragma": "no-cache",
|
|
||||||
"priority": "u=1, i",
|
|
||||||
"rdc-ab-tests": "commute_travel_time_variation:v1",
|
|
||||||
"sec-ch-ua": '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
|
|
||||||
"sec-ch-ua-mobile": "?0",
|
|
||||||
"sec-ch-ua-platform": '"Windows"',
|
|
||||||
"sec-fetch-dest": "empty",
|
|
||||||
"sec-fetch-mode": "cors",
|
|
||||||
"sec-fetch-site": "same-origin",
|
|
||||||
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36",
|
|
||||||
}
|
|
||||||
)
|
|
||||||
|
|
||||||
if scraper_input.proxy:
|
|
||||||
proxy_url = scraper_input.proxy
|
|
||||||
proxies = {"http": proxy_url, "https": proxy_url}
|
|
||||||
self.session.proxies.update(proxies)
|
|
||||||
|
|
||||||
|
self.session = requests.Session()
|
||||||
self.listing_type = scraper_input.listing_type
|
self.listing_type = scraper_input.listing_type
|
||||||
self.radius = scraper_input.radius
|
self.site_name = scraper_input.site_name
|
||||||
self.last_x_days = scraper_input.last_x_days
|
|
||||||
self.mls_only = scraper_input.mls_only
|
|
||||||
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
|
|
||||||
self.return_type = scraper_input.return_type
|
|
||||||
|
|
||||||
def search(self) -> list[Union[Property | dict]]: ...
|
if scraper_input.proxy_url:
|
||||||
|
self.session.proxies = {
|
||||||
|
"http": scraper_input.proxy_url,
|
||||||
|
"https": scraper_input.proxy_url,
|
||||||
|
}
|
||||||
|
|
||||||
|
def search(self) -> list[Property]:
|
||||||
|
...
|
||||||
|
|
||||||
@staticmethod
|
@staticmethod
|
||||||
def _parse_home(home) -> Property: ...
|
def _parse_home(home) -> Property:
|
||||||
|
...
|
||||||
|
|
||||||
def handle_location(self): ...
|
def handle_location(self):
|
||||||
|
...
|
||||||
@staticmethod
|
|
||||||
def get_access_token():
|
|
||||||
device_id = str(uuid.uuid4()).upper()
|
|
||||||
|
|
||||||
response = requests.post(
|
|
||||||
"https://graph.realtor.com/auth/token",
|
|
||||||
headers={
|
|
||||||
"Host": "graph.realtor.com",
|
|
||||||
"Accept": "*/*",
|
|
||||||
"Content-Type": "Application/json",
|
|
||||||
"X-Client-ID": "rdc_mobile_native,iphone",
|
|
||||||
"X-Visitor-ID": device_id,
|
|
||||||
"X-Client-Version": "24.21.23.679885",
|
|
||||||
"Accept-Language": "en-US,en;q=0.9",
|
|
||||||
"User-Agent": "Realtor.com/24.21.23.679885 CFNetwork/1494.0.7 Darwin/23.4.0",
|
|
||||||
},
|
|
||||||
data=json.dumps(
|
|
||||||
{
|
|
||||||
"grant_type": "device_mobile",
|
|
||||||
"device_id": device_id,
|
|
||||||
"client_app_id": "rdc_mobile_native,24.21.23.679885,iphone",
|
|
||||||
}
|
|
||||||
),
|
|
||||||
)
|
|
||||||
|
|
||||||
data = response.json()
|
|
||||||
|
|
||||||
if not (access_token := data.get("access_token")):
|
|
||||||
raise AuthenticationError(
|
|
||||||
"Failed to get access token, use a proxy/vpn or wait a moment and try again.", response=response
|
|
||||||
)
|
|
||||||
|
|
||||||
return access_token
|
|
||||||
|
|
|
||||||
|
|
@ -1,13 +1,5 @@
|
||||||
from __future__ import annotations
|
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass
|
||||||
from enum import Enum
|
from enum import Enum
|
||||||
from typing import Optional
|
|
||||||
|
|
||||||
|
|
||||||
class ReturnType(Enum):
|
|
||||||
pydantic = "pydantic"
|
|
||||||
pandas = "pandas"
|
|
||||||
raw = "raw"
|
|
||||||
|
|
||||||
|
|
||||||
class SiteName(Enum):
|
class SiteName(Enum):
|
||||||
|
|
@ -15,180 +7,78 @@ class SiteName(Enum):
|
||||||
REDFIN = "redfin"
|
REDFIN = "redfin"
|
||||||
REALTOR = "realtor.com"
|
REALTOR = "realtor.com"
|
||||||
|
|
||||||
@classmethod
|
|
||||||
def get_by_value(cls, value):
|
|
||||||
for item in cls:
|
|
||||||
if item.value == value:
|
|
||||||
return item
|
|
||||||
raise ValueError(f"{value} not found in {cls}")
|
|
||||||
|
|
||||||
|
|
||||||
class SearchPropertyType(Enum):
|
|
||||||
SINGLE_FAMILY = "single_family"
|
|
||||||
APARTMENT = "apartment"
|
|
||||||
CONDOS = "condos"
|
|
||||||
CONDO_TOWNHOME_ROWHOME_COOP = "condo_townhome_rowhome_coop"
|
|
||||||
CONDO_TOWNHOME = "condo_townhome"
|
|
||||||
TOWNHOMES = "townhomes"
|
|
||||||
DUPLEX_TRIPLEX = "duplex_triplex"
|
|
||||||
FARM = "farm"
|
|
||||||
LAND = "land"
|
|
||||||
MULTI_FAMILY = "multi_family"
|
|
||||||
MOBILE = "mobile"
|
|
||||||
|
|
||||||
|
|
||||||
class ListingType(Enum):
|
class ListingType(Enum):
|
||||||
FOR_SALE = "FOR_SALE"
|
FOR_SALE = "for_sale"
|
||||||
FOR_RENT = "FOR_RENT"
|
FOR_RENT = "for_rent"
|
||||||
PENDING = "PENDING"
|
SOLD = "sold"
|
||||||
SOLD = "SOLD"
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Agent:
|
|
||||||
name: str | None = None
|
|
||||||
phone: str | None = None
|
|
||||||
|
|
||||||
|
|
||||||
class PropertyType(Enum):
|
class PropertyType(Enum):
|
||||||
APARTMENT = "APARTMENT"
|
HOUSE = "HOUSE"
|
||||||
BUILDING = "BUILDING"
|
|
||||||
COMMERCIAL = "COMMERCIAL"
|
|
||||||
GOVERNMENT = "GOVERNMENT"
|
|
||||||
INDUSTRIAL = "INDUSTRIAL"
|
|
||||||
CONDO_TOWNHOME = "CONDO_TOWNHOME"
|
|
||||||
CONDO_TOWNHOME_ROWHOME_COOP = "CONDO_TOWNHOME_ROWHOME_COOP"
|
|
||||||
CONDO = "CONDO"
|
CONDO = "CONDO"
|
||||||
CONDOP = "CONDOP"
|
TOWNHOUSE = "TOWNHOUSE"
|
||||||
CONDOS = "CONDOS"
|
|
||||||
COOP = "COOP"
|
|
||||||
DUPLEX_TRIPLEX = "DUPLEX_TRIPLEX"
|
|
||||||
FARM = "FARM"
|
|
||||||
INVESTMENT = "INVESTMENT"
|
|
||||||
LAND = "LAND"
|
|
||||||
MOBILE = "MOBILE"
|
|
||||||
MULTI_FAMILY = "MULTI_FAMILY"
|
|
||||||
RENTAL = "RENTAL"
|
|
||||||
SINGLE_FAMILY = "SINGLE_FAMILY"
|
SINGLE_FAMILY = "SINGLE_FAMILY"
|
||||||
TOWNHOMES = "TOWNHOMES"
|
MULTI_FAMILY = "MULTI_FAMILY"
|
||||||
|
MANUFACTURED = "MANUFACTURED"
|
||||||
|
APARTMENT = "APARTMENT"
|
||||||
|
LAND = "LAND"
|
||||||
OTHER = "OTHER"
|
OTHER = "OTHER"
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_int_code(cls, code):
|
||||||
|
mapping = {
|
||||||
|
1: cls.HOUSE,
|
||||||
|
2: cls.CONDO,
|
||||||
|
3: cls.TOWNHOUSE,
|
||||||
|
4: cls.MULTI_FAMILY,
|
||||||
|
5: cls.LAND,
|
||||||
|
6: cls.OTHER,
|
||||||
|
8: cls.SINGLE_FAMILY,
|
||||||
|
13: cls.SINGLE_FAMILY,
|
||||||
|
}
|
||||||
|
|
||||||
|
return mapping.get(code, cls.OTHER)
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
class Address:
|
class Address:
|
||||||
full_line: str | None = None
|
address_one: str
|
||||||
street: str | None = None
|
city: str
|
||||||
unit: str | None = None
|
state: str
|
||||||
city: str | None = None
|
zip_code: str
|
||||||
state: str | None = None
|
|
||||||
zip: str | None = None
|
address_two: str | None = None
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass()
|
||||||
|
class Realty:
|
||||||
|
site_name: str
|
||||||
|
address: Address
|
||||||
|
url: str
|
||||||
|
listing_type: ListingType | None = None
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
class Description:
|
class Property(Realty):
|
||||||
primary_photo: str | None = None
|
price: int | None = None
|
||||||
alt_photos: list[str] | None = None
|
|
||||||
style: PropertyType | None = None
|
|
||||||
beds: int | None = None
|
beds: int | None = None
|
||||||
baths_full: int | None = None
|
baths: float | None = None
|
||||||
baths_half: int | None = None
|
|
||||||
sqft: int | None = None
|
|
||||||
lot_sqft: int | None = None
|
|
||||||
sold_price: int | None = None
|
|
||||||
year_built: int | None = None
|
|
||||||
garage: float | None = None
|
|
||||||
stories: int | None = None
|
stories: int | None = None
|
||||||
text: str | None = None
|
year_built: int | None = None
|
||||||
|
square_feet: int | None = None
|
||||||
|
price_per_square_foot: int | 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 Entity:
|
|
||||||
name: str
|
|
||||||
uuid: str | None = None
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Agent(Entity):
|
|
||||||
mls_set: str | None = None
|
|
||||||
nrds_id: str | None = None
|
|
||||||
phones: list[dict] | AgentPhone | None = None
|
|
||||||
email: str | None = None
|
|
||||||
href: str | None = None
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Office(Entity):
|
|
||||||
mls_set: str | None = None
|
|
||||||
email: str | None = None
|
|
||||||
href: str | None = None
|
|
||||||
phones: list[dict] | AgentPhone | None = None
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Broker(Entity):
|
|
||||||
pass
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Builder(Entity):
|
|
||||||
pass
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Advertisers:
|
|
||||||
agent: Agent | None = None
|
|
||||||
broker: Broker | None = None
|
|
||||||
builder: Builder | None = None
|
|
||||||
office: Office | None = None
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class Property:
|
|
||||||
property_url: str
|
|
||||||
|
|
||||||
property_id: str
|
|
||||||
#: allows_cats: bool
|
|
||||||
#: allows_dogs: bool
|
|
||||||
|
|
||||||
listing_id: str | None = None
|
|
||||||
|
|
||||||
mls: str | None = None
|
|
||||||
mls_id: str | None = None
|
mls_id: str | None = None
|
||||||
status: str | None = None
|
|
||||||
address: Address | None = None
|
|
||||||
|
|
||||||
list_price: int | None = None
|
agent_name: str | None = None
|
||||||
list_price_min: int | None = None
|
property_type: PropertyType | None = None
|
||||||
list_price_max: int | None = None
|
lot_size: int | None = None
|
||||||
|
description: str | None = None
|
||||||
|
|
||||||
list_date: str | None = None
|
|
||||||
pending_date: str | None = None
|
|
||||||
last_sold_date: str | None = None
|
|
||||||
prc_sqft: int | None = None
|
|
||||||
new_construction: bool | None = None
|
|
||||||
hoa_fee: int | None = None
|
|
||||||
days_on_mls: int | None = None
|
|
||||||
description: Description | None = None
|
|
||||||
tags: list[str] | None = None
|
|
||||||
details: list[dict] | None = None
|
|
||||||
|
|
||||||
latitude: float | None = None
|
@dataclass
|
||||||
longitude: float | None = None
|
class Building(Realty):
|
||||||
neighborhoods: Optional[str] = None
|
num_units: int | None = None
|
||||||
county: Optional[str] = None
|
min_unit_price: int | None = None
|
||||||
fips_code: Optional[str] = None
|
max_unit_price: int | None = None
|
||||||
nearby_schools: list[str] = None
|
avg_unit_price: int | None = None
|
||||||
assessed_value: int | None = None
|
|
||||||
estimated_value: int | None = None
|
|
||||||
tax: int | None = None
|
|
||||||
tax_history: list[dict] | None = None
|
|
||||||
|
|
||||||
advertisers: Advertisers | None = None
|
|
||||||
|
|
|
||||||
|
|
@ -1,668 +1,268 @@
|
||||||
"""
|
|
||||||
homeharvest.realtor.__init__
|
|
||||||
~~~~~~~~~~~~
|
|
||||||
|
|
||||||
This module implements the scraper for realtor.com
|
|
||||||
"""
|
|
||||||
|
|
||||||
from __future__ import annotations
|
|
||||||
|
|
||||||
import json
|
import json
|
||||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
from ..models import Property, Address
|
||||||
from datetime import datetime
|
|
||||||
from json import JSONDecodeError
|
|
||||||
from typing import Dict, Union, Optional
|
|
||||||
|
|
||||||
from tenacity import (
|
|
||||||
retry,
|
|
||||||
retry_if_exception_type,
|
|
||||||
wait_exponential,
|
|
||||||
stop_after_attempt,
|
|
||||||
)
|
|
||||||
|
|
||||||
from .. import Scraper
|
from .. import Scraper
|
||||||
from ..models import (
|
from typing import Any, Generator
|
||||||
Property,
|
from ....exceptions import NoResultsFound
|
||||||
Address,
|
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||||
ListingType,
|
|
||||||
Description,
|
|
||||||
PropertyType,
|
|
||||||
Agent,
|
|
||||||
Broker,
|
|
||||||
Builder,
|
|
||||||
Advertisers,
|
|
||||||
Office,
|
|
||||||
ReturnType
|
|
||||||
)
|
|
||||||
from .queries import GENERAL_RESULTS_QUERY, SEARCH_HOMES_DATA, HOMES_DATA, HOME_FRAGMENT
|
|
||||||
|
|
||||||
|
|
||||||
class RealtorScraper(Scraper):
|
class RealtorScraper(Scraper):
|
||||||
SEARCH_GQL_URL = "https://www.realtor.com/api/v1/rdc_search_srp?client_id=rdc-search-new-communities&schema=vesta"
|
|
||||||
PROPERTY_URL = "https://www.realtor.com/realestateandhomes-detail/"
|
|
||||||
PROPERTY_GQL = "https://graph.realtor.com/graphql"
|
|
||||||
ADDRESS_AUTOCOMPLETE_URL = "https://parser-external.geo.moveaws.com/suggest"
|
|
||||||
NUM_PROPERTY_WORKERS = 20
|
|
||||||
DEFAULT_PAGE_SIZE = 200
|
|
||||||
|
|
||||||
def __init__(self, scraper_input):
|
def __init__(self, scraper_input):
|
||||||
super().__init__(scraper_input)
|
super().__init__(scraper_input)
|
||||||
|
self.search_url = "https://www.realtor.com/api/v1/rdc_search_srp?client_id=rdc-search-new-communities&schema=vesta"
|
||||||
|
|
||||||
def handle_location(self):
|
def handle_location(self):
|
||||||
|
headers = {
|
||||||
|
"authority": "parser-external.geo.moveaws.com",
|
||||||
|
"accept": "*/*",
|
||||||
|
"accept-language": "en-US,en;q=0.9",
|
||||||
|
"origin": "https://www.realtor.com",
|
||||||
|
"referer": "https://www.realtor.com/",
|
||||||
|
"sec-ch-ua": '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||||
|
"sec-ch-ua-mobile": "?0",
|
||||||
|
"sec-ch-ua-platform": '"Windows"',
|
||||||
|
"sec-fetch-dest": "empty",
|
||||||
|
"sec-fetch-mode": "cors",
|
||||||
|
"sec-fetch-site": "cross-site",
|
||||||
|
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36",
|
||||||
|
}
|
||||||
|
|
||||||
params = {
|
params = {
|
||||||
"input": self.location,
|
"input": self.location,
|
||||||
"client_id": self.listing_type.value.lower().replace("_", "-"),
|
"client_id": self.listing_type.value.replace('_', '-'),
|
||||||
"limit": "1",
|
"limit": "1",
|
||||||
"area_types": "city,state,county,postal_code,address,street,neighborhood,school,school_district,university,park",
|
"area_types": "city,state,county,postal_code,address,street,neighborhood,school,school_district,university,park",
|
||||||
}
|
}
|
||||||
|
|
||||||
response = self.session.get(
|
response = self.session.get(
|
||||||
self.ADDRESS_AUTOCOMPLETE_URL,
|
"https://parser-external.geo.moveaws.com/suggest",
|
||||||
params=params,
|
params=params,
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
response_json = response.json()
|
response_json = response.json()
|
||||||
|
|
||||||
result = response_json["autocomplete"]
|
result = response_json["autocomplete"]
|
||||||
|
|
||||||
if not result:
|
if result is None:
|
||||||
return None
|
raise NoResultsFound("No results found for location: " + self.location)
|
||||||
|
|
||||||
return result[0]
|
return result[0]
|
||||||
|
|
||||||
def get_latest_listing_id(self, property_id: str) -> str | None:
|
def handle_address(self, property_id: str) -> list[Property]:
|
||||||
query = """query Property($property_id: ID!) {
|
query = """query Property($property_id: ID!) {
|
||||||
property(id: $property_id) {
|
property(id: $property_id) {
|
||||||
listings {
|
property_id
|
||||||
listing_id
|
details {
|
||||||
primary
|
date_updated
|
||||||
|
garage
|
||||||
|
permalink
|
||||||
|
year_built
|
||||||
|
stories
|
||||||
|
}
|
||||||
|
address {
|
||||||
|
address_validation_code
|
||||||
|
city
|
||||||
|
country
|
||||||
|
county
|
||||||
|
line
|
||||||
|
postal_code
|
||||||
|
state_code
|
||||||
|
street_direction
|
||||||
|
street_name
|
||||||
|
street_number
|
||||||
|
street_suffix
|
||||||
|
street_post_direction
|
||||||
|
unit_value
|
||||||
|
unit
|
||||||
|
unit_descriptor
|
||||||
|
zip
|
||||||
|
}
|
||||||
|
basic {
|
||||||
|
baths
|
||||||
|
beds
|
||||||
|
price
|
||||||
|
sqft
|
||||||
|
lot_sqft
|
||||||
|
type
|
||||||
|
sold_price
|
||||||
|
}
|
||||||
|
public_record {
|
||||||
|
lot_size
|
||||||
|
sqft
|
||||||
|
stories
|
||||||
|
units
|
||||||
|
year_built
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
|
||||||
"""
|
|
||||||
|
|
||||||
variables = {"property_id": property_id}
|
|
||||||
payload = {
|
|
||||||
"query": query,
|
|
||||||
"variables": variables,
|
|
||||||
}
|
|
||||||
|
|
||||||
response = self.session.post(self.SEARCH_GQL_URL, json=payload)
|
|
||||||
response_json = response.json()
|
|
||||||
|
|
||||||
property_info = response_json["data"]["property"]
|
|
||||||
if property_info["listings"] is None:
|
|
||||||
return None
|
|
||||||
|
|
||||||
primary_listing = next(
|
|
||||||
(listing for listing in property_info["listings"] if listing["primary"]),
|
|
||||||
None,
|
|
||||||
)
|
|
||||||
if primary_listing:
|
|
||||||
return primary_listing["listing_id"]
|
|
||||||
else:
|
|
||||||
return property_info["listings"][0]["listing_id"]
|
|
||||||
|
|
||||||
def handle_home(self, property_id: str) -> list[Property]:
|
|
||||||
query = (
|
|
||||||
"""query Home($property_id: ID!) {
|
|
||||||
home(property_id: $property_id) %s
|
|
||||||
}"""
|
}"""
|
||||||
% HOMES_DATA
|
|
||||||
)
|
|
||||||
|
|
||||||
variables = {"property_id": property_id}
|
variables = {
|
||||||
payload = {
|
'property_id': property_id
|
||||||
"query": query,
|
|
||||||
"variables": variables,
|
|
||||||
}
|
}
|
||||||
|
|
||||||
response = self.session.post(self.SEARCH_GQL_URL, json=payload)
|
payload = {
|
||||||
|
'query': query,
|
||||||
|
'variables': variables,
|
||||||
|
}
|
||||||
|
|
||||||
|
response = self.session.post(self.search_url, json=payload)
|
||||||
response_json = response.json()
|
response_json = response.json()
|
||||||
|
|
||||||
property_info = response_json["data"]["home"]
|
property_info = response_json['data']['property']
|
||||||
|
|
||||||
return [self.process_property(property_info)]
|
return [Property(
|
||||||
|
site_name=self.site_name,
|
||||||
@staticmethod
|
address=Address(
|
||||||
def process_advertisers(advertisers: list[dict] | None) -> Advertisers | None:
|
address_one=property_info['address']['line'],
|
||||||
if not advertisers:
|
city=property_info['address']['city'],
|
||||||
return None
|
state=property_info['address']['state_code'],
|
||||||
|
zip_code=property_info['address']['postal_code'],
|
||||||
def _parse_fulfillment_id(fulfillment_id: str | None) -> str | None:
|
|
||||||
return fulfillment_id if fulfillment_id and fulfillment_id != "0" else None
|
|
||||||
|
|
||||||
processed_advertisers = Advertisers()
|
|
||||||
|
|
||||||
for advertiser in advertisers:
|
|
||||||
advertiser_type = advertiser.get("type")
|
|
||||||
if advertiser_type == "seller": #: agent
|
|
||||||
processed_advertisers.agent = Agent(
|
|
||||||
uuid=_parse_fulfillment_id(advertiser.get("fulfillment_id")),
|
|
||||||
nrds_id=advertiser.get("nrds_id"),
|
|
||||||
mls_set=advertiser.get("mls_set"),
|
|
||||||
name=advertiser.get("name"),
|
|
||||||
email=advertiser.get("email"),
|
|
||||||
phones=advertiser.get("phones"),
|
|
||||||
)
|
|
||||||
|
|
||||||
if advertiser.get("broker") and advertiser["broker"].get("name"): #: has a broker
|
|
||||||
processed_advertisers.broker = Broker(
|
|
||||||
uuid=_parse_fulfillment_id(advertiser["broker"].get("fulfillment_id")),
|
|
||||||
name=advertiser["broker"].get("name"),
|
|
||||||
)
|
|
||||||
|
|
||||||
if advertiser.get("office"): #: has an office
|
|
||||||
processed_advertisers.office = Office(
|
|
||||||
uuid=_parse_fulfillment_id(advertiser["office"].get("fulfillment_id")),
|
|
||||||
mls_set=advertiser["office"].get("mls_set"),
|
|
||||||
name=advertiser["office"].get("name"),
|
|
||||||
email=advertiser["office"].get("email"),
|
|
||||||
phones=advertiser["office"].get("phones"),
|
|
||||||
)
|
|
||||||
|
|
||||||
if advertiser_type == "community": #: could be builder
|
|
||||||
if advertiser.get("builder"):
|
|
||||||
processed_advertisers.builder = Builder(
|
|
||||||
uuid=_parse_fulfillment_id(advertiser["builder"].get("fulfillment_id")),
|
|
||||||
name=advertiser["builder"].get("name"),
|
|
||||||
)
|
|
||||||
|
|
||||||
return processed_advertisers
|
|
||||||
|
|
||||||
def process_property(self, result: dict) -> Property | None:
|
|
||||||
mls = result["source"].get("id") if "source" in result and isinstance(result["source"], dict) else None
|
|
||||||
|
|
||||||
if not mls and self.mls_only:
|
|
||||||
return
|
|
||||||
|
|
||||||
able_to_get_lat_long = (
|
|
||||||
result
|
|
||||||
and result.get("location")
|
|
||||||
and result["location"].get("address")
|
|
||||||
and result["location"]["address"].get("coordinate")
|
|
||||||
)
|
|
||||||
|
|
||||||
is_pending = result["flags"].get("is_pending")
|
|
||||||
is_contingent = result["flags"].get("is_contingent")
|
|
||||||
|
|
||||||
if (is_pending or is_contingent) and (self.exclude_pending and self.listing_type != ListingType.PENDING):
|
|
||||||
return
|
|
||||||
|
|
||||||
property_id = result["property_id"]
|
|
||||||
prop_details = self.process_extra_property_details(result) if self.extra_property_data else {}
|
|
||||||
|
|
||||||
property_estimates_root = result.get("current_estimates") or result.get("estimates", {}).get("currentValues")
|
|
||||||
estimated_value = self.get_key(property_estimates_root, [0, "estimate"])
|
|
||||||
|
|
||||||
advertisers = self.process_advertisers(result.get("advertisers"))
|
|
||||||
|
|
||||||
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=result["href"],
|
url="https://www.realtor.com/realestateandhomes-detail/" + property_info['details']['permalink'],
|
||||||
property_id=property_id,
|
beds=property_info['basic']['beds'],
|
||||||
listing_id=result.get("listing_id"),
|
baths=property_info['basic']['baths'],
|
||||||
status=("PENDING" if is_pending else "CONTINGENT" if is_contingent else result["status"].upper()),
|
stories=property_info['details']['stories'],
|
||||||
list_price=result["list_price"],
|
year_built=property_info['details']['year_built'],
|
||||||
list_price_min=result["list_price_min"],
|
square_feet=property_info['basic']['sqft'],
|
||||||
list_price_max=result["list_price_max"],
|
price_per_square_foot=property_info['basic']['price'] / property_info['basic']['sqft']
|
||||||
list_date=(result["list_date"].split("T")[0] if result.get("list_date") else None),
|
if property_info['basic']['sqft'] is not None and
|
||||||
prc_sqft=result.get("price_per_sqft"),
|
property_info['basic']['price'] is not None
|
||||||
last_sold_date=result.get("last_sold_date"),
|
else None,
|
||||||
new_construction=result["flags"].get("is_new_construction") is True,
|
price=property_info['basic']['price'],
|
||||||
hoa_fee=(result["hoa"]["fee"] if result.get("hoa") and isinstance(result["hoa"], dict) else None),
|
mls_id=property_id,
|
||||||
latitude=(result["location"]["address"]["coordinate"].get("lat") if able_to_get_lat_long else None),
|
listing_type=self.listing_type,
|
||||||
longitude=(result["location"]["address"]["coordinate"].get("lon") if able_to_get_lat_long else None),
|
lot_size=property_info['public_record']['lot_size'] if property_info['public_record'] is not None 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),
|
|
||||||
nearby_schools=prop_details.get("schools"),
|
|
||||||
assessed_value=prop_details.get("assessed_value"),
|
|
||||||
estimated_value=estimated_value if estimated_value else None,
|
|
||||||
advertisers=advertisers,
|
|
||||||
tax=prop_details.get("tax"),
|
|
||||||
tax_history=prop_details.get("tax_history"),
|
|
||||||
)
|
|
||||||
return realty_property
|
|
||||||
|
|
||||||
def general_search(self, variables: dict, search_type: str) -> Dict[str, Union[int, Union[list[Property], list[dict]]]]:
|
def handle_area(self, variables: dict, return_total: bool = False) -> list[Property] | int:
|
||||||
"""
|
query = """query Home_search(
|
||||||
Handles a location area & returns a list of properties
|
$city: String,
|
||||||
"""
|
$county: [String],
|
||||||
|
$state_code: String,
|
||||||
date_param = ""
|
$postal_code: String
|
||||||
if self.listing_type == ListingType.SOLD:
|
$offset: Int,
|
||||||
if self.date_from and self.date_to:
|
) {
|
||||||
date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
|
home_search(
|
||||||
elif self.last_x_days:
|
query: {
|
||||||
date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
|
city: $city
|
||||||
else:
|
county: $county
|
||||||
if self.date_from and self.date_to:
|
postal_code: $postal_code
|
||||||
date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
|
state_code: $state_code
|
||||||
elif self.last_x_days:
|
status: %s
|
||||||
date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
|
|
||||||
|
|
||||||
property_type_param = ""
|
|
||||||
if self.property_type:
|
|
||||||
property_types = [pt.value for pt in self.property_type]
|
|
||||||
property_type_param = f"type: {json.dumps(property_types)}"
|
|
||||||
|
|
||||||
sort_param = (
|
|
||||||
"sort: [{ field: sold_date, direction: desc }]"
|
|
||||||
if self.listing_type == ListingType.SOLD
|
|
||||||
else "" #: "sort: [{ field: list_date, direction: desc }]" #: prioritize normal fractal sort from realtor
|
|
||||||
)
|
|
||||||
|
|
||||||
pending_or_contingent_param = (
|
|
||||||
"or_filters: { contingent: true, pending: true }" if self.listing_type == ListingType.PENDING else ""
|
|
||||||
)
|
|
||||||
|
|
||||||
listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
|
|
||||||
is_foreclosure = ""
|
|
||||||
|
|
||||||
if variables.get("foreclosure") is True:
|
|
||||||
is_foreclosure = "foreclosure: true"
|
|
||||||
elif variables.get("foreclosure") is False:
|
|
||||||
is_foreclosure = "foreclosure: false"
|
|
||||||
|
|
||||||
if search_type == "comps": #: comps search, came from an address
|
|
||||||
query = """query Property_search(
|
|
||||||
$coordinates: [Float]!
|
|
||||||
$radius: String!
|
|
||||||
$offset: Int!,
|
|
||||||
) {
|
|
||||||
home_search(
|
|
||||||
query: {
|
|
||||||
%s
|
|
||||||
nearby: {
|
|
||||||
coordinates: $coordinates
|
|
||||||
radius: $radius
|
|
||||||
}
|
}
|
||||||
status: %s
|
limit: 200
|
||||||
%s
|
offset: $offset
|
||||||
%s
|
|
||||||
%s
|
|
||||||
}
|
|
||||||
%s
|
|
||||||
limit: 200
|
|
||||||
offset: $offset
|
|
||||||
) %s
|
|
||||||
}""" % (
|
|
||||||
is_foreclosure,
|
|
||||||
listing_type.value.lower(),
|
|
||||||
date_param,
|
|
||||||
property_type_param,
|
|
||||||
pending_or_contingent_param,
|
|
||||||
sort_param,
|
|
||||||
GENERAL_RESULTS_QUERY,
|
|
||||||
)
|
|
||||||
elif search_type == "area": #: general search, came from a general location
|
|
||||||
query = """query Home_search(
|
|
||||||
$location: String!,
|
|
||||||
$offset: Int,
|
|
||||||
) {
|
) {
|
||||||
home_search(
|
count
|
||||||
query: {
|
total
|
||||||
%s
|
results {
|
||||||
search_location: {location: $location}
|
property_id
|
||||||
status: %s
|
description {
|
||||||
unique: true
|
baths
|
||||||
%s
|
beds
|
||||||
%s
|
lot_sqft
|
||||||
%s
|
sqft
|
||||||
|
text
|
||||||
|
sold_price
|
||||||
|
stories
|
||||||
|
year_built
|
||||||
|
garage
|
||||||
|
unit_number
|
||||||
|
floor_number
|
||||||
}
|
}
|
||||||
bucket: { sort: "fractal_v1.1.3_fr" }
|
location {
|
||||||
%s
|
address {
|
||||||
limit: 200
|
city
|
||||||
offset: $offset
|
country
|
||||||
) %s
|
line
|
||||||
}""" % (
|
postal_code
|
||||||
is_foreclosure,
|
state_code
|
||||||
listing_type.value.lower(),
|
state
|
||||||
date_param,
|
street_direction
|
||||||
property_type_param,
|
street_name
|
||||||
pending_or_contingent_param,
|
street_number
|
||||||
sort_param,
|
street_post_direction
|
||||||
GENERAL_RESULTS_QUERY,
|
street_suffix
|
||||||
)
|
unit
|
||||||
else: #: general search, came from an address
|
}
|
||||||
query = (
|
}
|
||||||
"""query Property_search(
|
list_price
|
||||||
$property_id: [ID]!
|
price_per_sqft
|
||||||
$offset: Int!,
|
source {
|
||||||
) {
|
id
|
||||||
home_search(
|
}
|
||||||
query: {
|
}
|
||||||
property_id: $property_id
|
|
||||||
}
|
}
|
||||||
limit: 1
|
}""" % self.listing_type.value
|
||||||
offset: $offset
|
|
||||||
) %s
|
|
||||||
}"""
|
|
||||||
% GENERAL_RESULTS_QUERY
|
|
||||||
)
|
|
||||||
|
|
||||||
payload = {
|
payload = {
|
||||||
"query": query,
|
'query': query,
|
||||||
"variables": variables,
|
'variables': variables,
|
||||||
}
|
}
|
||||||
|
|
||||||
response = self.session.post(self.SEARCH_GQL_URL, json=payload)
|
response = self.session.post(self.search_url, json=payload)
|
||||||
response_json = response.json()
|
response_json = response.json()
|
||||||
search_key = "home_search" if "home_search" in query else "property_search"
|
|
||||||
|
|
||||||
properties: list[Union[Property, dict]] = []
|
if return_total:
|
||||||
|
return response_json['data']['home_search']['total']
|
||||||
|
|
||||||
if (
|
properties: list[Property] = []
|
||||||
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": []}
|
|
||||||
|
|
||||||
properties_list = response_json["data"][search_key]["results"]
|
for result in response_json['data']['home_search']['results']:
|
||||||
total_properties = response_json["data"][search_key]["total"]
|
realty_property = Property(
|
||||||
offset = variables.get("offset", 0)
|
address=Address(
|
||||||
|
address_one=result['location']['address']['line'],
|
||||||
|
city=result['location']['address']['city'],
|
||||||
|
state=result['location']['address']['state_code'],
|
||||||
|
zip_code=result['location']['address']['postal_code'],
|
||||||
|
address_two=result['location']['address']['unit'],
|
||||||
|
),
|
||||||
|
site_name=self.site_name,
|
||||||
|
url="https://www.realtor.com/realestateandhomes-detail/" + result['property_id'],
|
||||||
|
beds=result['description']['beds'],
|
||||||
|
baths=result['description']['baths'],
|
||||||
|
stories=result['description']['stories'],
|
||||||
|
year_built=result['description']['year_built'],
|
||||||
|
square_feet=result['description']['sqft'],
|
||||||
|
price_per_square_foot=result['price_per_sqft'],
|
||||||
|
price=result['list_price'],
|
||||||
|
mls_id=result['property_id'],
|
||||||
|
listing_type=self.listing_type,
|
||||||
|
lot_size=result['description']['lot_sqft'],
|
||||||
|
)
|
||||||
|
|
||||||
#: limit the number of properties to be processed
|
properties.append(realty_property)
|
||||||
#: example, if your offset is 200, and your limit is 250, return 50
|
|
||||||
properties_list: list[dict] = properties_list[: self.limit - offset]
|
|
||||||
|
|
||||||
if self.extra_property_data:
|
return properties
|
||||||
property_ids = [data["property_id"] for data in properties_list]
|
|
||||||
extra_property_details = self.get_bulk_prop_details(property_ids) or {}
|
|
||||||
|
|
||||||
for result in properties_list:
|
|
||||||
result.update(extra_property_details.get(result["property_id"], {}))
|
|
||||||
|
|
||||||
if self.return_type != ReturnType.raw:
|
|
||||||
with ThreadPoolExecutor(max_workers=self.NUM_PROPERTY_WORKERS) as executor:
|
|
||||||
futures = [executor.submit(self.process_property, result) for result in properties_list]
|
|
||||||
|
|
||||||
for future in as_completed(futures):
|
|
||||||
result = future.result()
|
|
||||||
if result:
|
|
||||||
properties.append(result)
|
|
||||||
else:
|
|
||||||
properties = properties_list
|
|
||||||
|
|
||||||
return {
|
|
||||||
"total": total_properties,
|
|
||||||
"properties": properties,
|
|
||||||
}
|
|
||||||
|
|
||||||
def search(self):
|
def search(self):
|
||||||
location_info = self.handle_location()
|
location_info = self.handle_location()
|
||||||
if not location_info:
|
|
||||||
return []
|
|
||||||
|
|
||||||
location_type = location_info["area_type"]
|
location_type = location_info["area_type"]
|
||||||
|
|
||||||
|
if location_type == 'address':
|
||||||
|
property_id = location_info['mpr_id']
|
||||||
|
return self.handle_address(property_id)
|
||||||
|
|
||||||
|
offset = 0
|
||||||
search_variables = {
|
search_variables = {
|
||||||
"offset": 0,
|
'city': location_info.get('city'),
|
||||||
|
'county': location_info.get('county'),
|
||||||
|
'state_code': location_info.get('state_code'),
|
||||||
|
'postal_code': location_info.get('postal_code'),
|
||||||
|
'offset': offset,
|
||||||
}
|
}
|
||||||
|
|
||||||
search_type = (
|
total = self.handle_area(search_variables, return_total=True)
|
||||||
"comps"
|
|
||||||
if self.radius and location_type == "address"
|
|
||||||
else "address" if location_type == "address" and not self.radius else "area"
|
|
||||||
)
|
|
||||||
if location_type == "address":
|
|
||||||
if not self.radius: #: single address search, non comps
|
|
||||||
property_id = location_info["mpr_id"]
|
|
||||||
return self.handle_home(property_id)
|
|
||||||
|
|
||||||
else: #: general search, comps (radius)
|
homes = []
|
||||||
if not location_info.get("centroid"):
|
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||||
return []
|
|
||||||
|
|
||||||
coordinates = list(location_info["centroid"].values())
|
|
||||||
search_variables |= {
|
|
||||||
"coordinates": coordinates,
|
|
||||||
"radius": "{}mi".format(self.radius),
|
|
||||||
}
|
|
||||||
|
|
||||||
elif location_type == "postal_code":
|
|
||||||
search_variables |= {
|
|
||||||
"postal_code": location_info.get("postal_code"),
|
|
||||||
}
|
|
||||||
|
|
||||||
else: #: general search, location
|
|
||||||
search_variables |= {
|
|
||||||
"location": self.location,
|
|
||||||
}
|
|
||||||
|
|
||||||
if self.foreclosure:
|
|
||||||
search_variables["foreclosure"] = self.foreclosure
|
|
||||||
|
|
||||||
result = self.general_search(search_variables, search_type=search_type)
|
|
||||||
total = result["total"]
|
|
||||||
homes = result["properties"]
|
|
||||||
|
|
||||||
with ThreadPoolExecutor() as executor:
|
|
||||||
futures = [
|
futures = [
|
||||||
executor.submit(
|
executor.submit(
|
||||||
self.general_search,
|
self.handle_area, variables=search_variables | {'offset': i}, return_total=False
|
||||||
variables=search_variables | {"offset": i},
|
) for i in range(0, total, 200)
|
||||||
search_type=search_type,
|
|
||||||
)
|
|
||||||
for i in range(
|
|
||||||
self.DEFAULT_PAGE_SIZE,
|
|
||||||
min(total, self.limit),
|
|
||||||
self.DEFAULT_PAGE_SIZE,
|
|
||||||
)
|
|
||||||
]
|
]
|
||||||
|
|
||||||
for future in as_completed(futures):
|
for future in as_completed(futures):
|
||||||
homes.extend(future.result()["properties"])
|
homes.extend(future.result())
|
||||||
|
|
||||||
return homes
|
return homes
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def get_key(data: dict, keys: list):
|
|
||||||
try:
|
|
||||||
value = data
|
|
||||||
for key in keys:
|
|
||||||
value = value[key]
|
|
||||||
|
|
||||||
return value or {}
|
|
||||||
except (KeyError, TypeError, IndexError):
|
|
||||||
return {}
|
|
||||||
|
|
||||||
def process_extra_property_details(self, result: dict) -> dict:
|
|
||||||
schools = self.get_key(result, ["nearbySchools", "schools"])
|
|
||||||
assessed_value = self.get_key(result, ["taxHistory", 0, "assessment", "total"])
|
|
||||||
tax_history = self.get_key(result, ["taxHistory"])
|
|
||||||
|
|
||||||
schools = [school["district"]["name"] for school in schools if school["district"].get("name")]
|
|
||||||
|
|
||||||
# Process tax history
|
|
||||||
latest_tax = None
|
|
||||||
processed_tax_history = None
|
|
||||||
if tax_history and isinstance(tax_history, list):
|
|
||||||
tax_history = sorted(tax_history, key=lambda x: x.get("year", 0), reverse=True)
|
|
||||||
|
|
||||||
if tax_history and "tax" in tax_history[0]:
|
|
||||||
latest_tax = tax_history[0]["tax"]
|
|
||||||
|
|
||||||
processed_tax_history = []
|
|
||||||
for entry in tax_history:
|
|
||||||
if "year" in entry and "tax" in entry:
|
|
||||||
processed_entry = {
|
|
||||||
"year": entry["year"],
|
|
||||||
"tax": entry["tax"],
|
|
||||||
}
|
|
||||||
if "assessment" in entry and isinstance(entry["assessment"], dict):
|
|
||||||
processed_entry["assessment"] = {
|
|
||||||
"building": entry["assessment"].get("building"),
|
|
||||||
"land": entry["assessment"].get("land"),
|
|
||||||
"total": entry["assessment"].get("total"),
|
|
||||||
}
|
|
||||||
processed_tax_history.append(processed_entry)
|
|
||||||
|
|
||||||
return {
|
|
||||||
"schools": schools if schools else None,
|
|
||||||
"assessed_value": assessed_value if assessed_value else None,
|
|
||||||
"tax": latest_tax,
|
|
||||||
"tax_history": processed_tax_history,
|
|
||||||
}
|
|
||||||
|
|
||||||
@retry(
|
|
||||||
retry=retry_if_exception_type(JSONDecodeError),
|
|
||||||
wait=wait_exponential(min=4, max=10),
|
|
||||||
stop=stop_after_attempt(3),
|
|
||||||
)
|
|
||||||
def get_bulk_prop_details(self, property_ids: list[str]) -> dict:
|
|
||||||
"""
|
|
||||||
Fetch extra property details for multiple properties in a single GraphQL query.
|
|
||||||
Returns a map of property_id to its details.
|
|
||||||
"""
|
|
||||||
if not self.extra_property_data or not property_ids:
|
|
||||||
return {}
|
|
||||||
|
|
||||||
property_ids = list(set(property_ids))
|
|
||||||
|
|
||||||
# Construct the bulk query
|
|
||||||
fragments = "\n".join(
|
|
||||||
f'home_{property_id}: home(property_id: {property_id}) {{ ...HomeData }}'
|
|
||||||
for property_id in property_ids
|
|
||||||
)
|
|
||||||
query = f"""{HOME_FRAGMENT}
|
|
||||||
|
|
||||||
query GetHomes {{
|
|
||||||
{fragments}
|
|
||||||
}}"""
|
|
||||||
|
|
||||||
response = self.session.post(self.SEARCH_GQL_URL, json={"query": query})
|
|
||||||
data = response.json()
|
|
||||||
|
|
||||||
if "data" not in data:
|
|
||||||
return {}
|
|
||||||
|
|
||||||
properties = data["data"]
|
|
||||||
return {data.replace('home_', ''): properties[data] for data in properties if properties[data]}
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def _parse_neighborhoods(result: dict) -> Optional[str]:
|
|
||||||
neighborhoods_list = []
|
|
||||||
neighborhoods = result["location"].get("neighborhoods", [])
|
|
||||||
|
|
||||||
if neighborhoods:
|
|
||||||
for neighborhood in neighborhoods:
|
|
||||||
name = neighborhood.get("name")
|
|
||||||
if name:
|
|
||||||
neighborhoods_list.append(name)
|
|
||||||
|
|
||||||
return ", ".join(neighborhoods_list) if neighborhoods_list else None
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def handle_none_safely(address_part):
|
|
||||||
if address_part is None:
|
|
||||||
return ""
|
|
||||||
|
|
||||||
return address_part
|
|
||||||
|
|
||||||
@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(
|
|
||||||
part
|
|
||||||
for part in [
|
|
||||||
address.get("street_number"),
|
|
||||||
address.get("street_direction"),
|
|
||||||
address.get("street_name"),
|
|
||||||
address.get("street_suffix"),
|
|
||||||
]
|
|
||||||
if part is not None
|
|
||||||
).strip(),
|
|
||||||
unit=address["unit"],
|
|
||||||
city=address["city"],
|
|
||||||
state=address["state_code"],
|
|
||||||
zip=address["postal_code"],
|
|
||||||
)
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
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):
|
|
||||||
description_data = {}
|
|
||||||
|
|
||||||
style = description_data.get("type", "")
|
|
||||||
if style is not None:
|
|
||||||
style = style.upper()
|
|
||||||
|
|
||||||
primary_photo = ""
|
|
||||||
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.__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=(
|
|
||||||
result.get("last_sold_price") or 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
|
|
||||||
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
|
|
||||||
|
|
||||||
@staticmethod
|
|
||||||
def process_alt_photos(photos_info: list[dict]) -> list[str] | None:
|
|
||||||
if not photos_info:
|
|
||||||
return None
|
|
||||||
|
|
||||||
return [
|
|
||||||
photo_info["href"].replace("s.jpg", "od-w480_h360_x2.webp?w=1080&q=75")
|
|
||||||
for photo_info in photos_info
|
|
||||||
if photo_info.get("href")
|
|
||||||
]
|
|
||||||
|
|
|
||||||
|
|
@ -1,242 +0,0 @@
|
||||||
_SEARCH_HOMES_DATA_BASE = """{
|
|
||||||
pending_date
|
|
||||||
listing_id
|
|
||||||
property_id
|
|
||||||
href
|
|
||||||
list_date
|
|
||||||
status
|
|
||||||
last_sold_price
|
|
||||||
last_sold_date
|
|
||||||
list_price
|
|
||||||
list_price_max
|
|
||||||
list_price_min
|
|
||||||
price_per_sqft
|
|
||||||
tags
|
|
||||||
details {
|
|
||||||
category
|
|
||||||
text
|
|
||||||
parent_category
|
|
||||||
}
|
|
||||||
pet_policy {
|
|
||||||
cats
|
|
||||||
dogs
|
|
||||||
dogs_small
|
|
||||||
dogs_large
|
|
||||||
__typename
|
|
||||||
}
|
|
||||||
units {
|
|
||||||
availability {
|
|
||||||
date
|
|
||||||
__typename
|
|
||||||
}
|
|
||||||
description {
|
|
||||||
baths_consolidated
|
|
||||||
baths
|
|
||||||
beds
|
|
||||||
sqft
|
|
||||||
__typename
|
|
||||||
}
|
|
||||||
list_price
|
|
||||||
__typename
|
|
||||||
}
|
|
||||||
flags {
|
|
||||||
is_contingent
|
|
||||||
is_pending
|
|
||||||
is_new_construction
|
|
||||||
}
|
|
||||||
description {
|
|
||||||
type
|
|
||||||
sqft
|
|
||||||
beds
|
|
||||||
baths_full
|
|
||||||
baths_half
|
|
||||||
lot_sqft
|
|
||||||
year_built
|
|
||||||
garage
|
|
||||||
type
|
|
||||||
name
|
|
||||||
stories
|
|
||||||
text
|
|
||||||
}
|
|
||||||
source {
|
|
||||||
id
|
|
||||||
listing_id
|
|
||||||
}
|
|
||||||
hoa {
|
|
||||||
fee
|
|
||||||
}
|
|
||||||
location {
|
|
||||||
address {
|
|
||||||
street_direction
|
|
||||||
street_number
|
|
||||||
street_name
|
|
||||||
street_suffix
|
|
||||||
line
|
|
||||||
unit
|
|
||||||
city
|
|
||||||
state_code
|
|
||||||
postal_code
|
|
||||||
coordinate {
|
|
||||||
lon
|
|
||||||
lat
|
|
||||||
}
|
|
||||||
}
|
|
||||||
county {
|
|
||||||
name
|
|
||||||
fips_code
|
|
||||||
}
|
|
||||||
neighborhoods {
|
|
||||||
name
|
|
||||||
}
|
|
||||||
}
|
|
||||||
tax_record {
|
|
||||||
public_record_id
|
|
||||||
}
|
|
||||||
primary_photo(https: true) {
|
|
||||||
href
|
|
||||||
}
|
|
||||||
photos(https: true) {
|
|
||||||
href
|
|
||||||
tags {
|
|
||||||
label
|
|
||||||
}
|
|
||||||
}
|
|
||||||
advertisers {
|
|
||||||
email
|
|
||||||
broker {
|
|
||||||
name
|
|
||||||
fulfillment_id
|
|
||||||
}
|
|
||||||
type
|
|
||||||
name
|
|
||||||
fulfillment_id
|
|
||||||
builder {
|
|
||||||
name
|
|
||||||
fulfillment_id
|
|
||||||
}
|
|
||||||
phones {
|
|
||||||
ext
|
|
||||||
primary
|
|
||||||
type
|
|
||||||
number
|
|
||||||
}
|
|
||||||
office {
|
|
||||||
name
|
|
||||||
email
|
|
||||||
fulfillment_id
|
|
||||||
href
|
|
||||||
phones {
|
|
||||||
number
|
|
||||||
type
|
|
||||||
primary
|
|
||||||
ext
|
|
||||||
}
|
|
||||||
mls_set
|
|
||||||
}
|
|
||||||
corporation {
|
|
||||||
specialties
|
|
||||||
name
|
|
||||||
bio
|
|
||||||
href
|
|
||||||
fulfillment_id
|
|
||||||
}
|
|
||||||
mls_set
|
|
||||||
nrds_id
|
|
||||||
rental_corporation {
|
|
||||||
fulfillment_id
|
|
||||||
}
|
|
||||||
rental_management {
|
|
||||||
name
|
|
||||||
href
|
|
||||||
fulfillment_id
|
|
||||||
}
|
|
||||||
}
|
|
||||||
"""
|
|
||||||
|
|
||||||
|
|
||||||
HOME_FRAGMENT = """
|
|
||||||
fragment HomeData on Home {
|
|
||||||
property_id
|
|
||||||
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 } }
|
|
||||||
monthly_fees {
|
|
||||||
description
|
|
||||||
display_amount
|
|
||||||
}
|
|
||||||
one_time_fees {
|
|
||||||
description
|
|
||||||
display_amount
|
|
||||||
}
|
|
||||||
parking {
|
|
||||||
unassigned_space_rent
|
|
||||||
assigned_spaces_available
|
|
||||||
description
|
|
||||||
assigned_space_rent
|
|
||||||
}
|
|
||||||
terms {
|
|
||||||
text
|
|
||||||
category
|
|
||||||
}
|
|
||||||
}
|
|
||||||
"""
|
|
||||||
|
|
||||||
HOMES_DATA = """%s
|
|
||||||
nearbySchools: nearby_schools(radius: 5.0, limit_per_level: 3) {
|
|
||||||
__typename schools { district { __typename id name } }
|
|
||||||
}
|
|
||||||
monthly_fees {
|
|
||||||
description
|
|
||||||
display_amount
|
|
||||||
}
|
|
||||||
one_time_fees {
|
|
||||||
description
|
|
||||||
display_amount
|
|
||||||
}
|
|
||||||
parking {
|
|
||||||
unassigned_space_rent
|
|
||||||
assigned_spaces_available
|
|
||||||
description
|
|
||||||
assigned_space_rent
|
|
||||||
}
|
|
||||||
terms {
|
|
||||||
text
|
|
||||||
category
|
|
||||||
}
|
|
||||||
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
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}""" % _SEARCH_HOMES_DATA_BASE
|
|
||||||
|
|
||||||
SEARCH_HOMES_DATA = """%s
|
|
||||||
current_estimates {
|
|
||||||
__typename
|
|
||||||
source {
|
|
||||||
__typename
|
|
||||||
type
|
|
||||||
name
|
|
||||||
}
|
|
||||||
estimate
|
|
||||||
estimateHigh: estimate_high
|
|
||||||
estimateLow: estimate_low
|
|
||||||
date
|
|
||||||
isBestHomeValue: isbest_homevalue
|
|
||||||
}
|
|
||||||
}""" % _SEARCH_HOMES_DATA_BASE
|
|
||||||
|
|
||||||
GENERAL_RESULTS_QUERY = """{
|
|
||||||
count
|
|
||||||
total
|
|
||||||
results %s
|
|
||||||
}""" % SEARCH_HOMES_DATA
|
|
||||||
|
|
@ -0,0 +1,158 @@
|
||||||
|
import json
|
||||||
|
from ..models import Property, Address, PropertyType, Building
|
||||||
|
from .. import Scraper
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
class RedfinScraper(Scraper):
|
||||||
|
def __init__(self, scraper_input):
|
||||||
|
super().__init__(scraper_input)
|
||||||
|
self.listing_type = scraper_input.listing_type
|
||||||
|
|
||||||
|
def _handle_location(self):
|
||||||
|
url = "https://www.redfin.com/stingray/do/location-autocomplete?v=2&al=1&location={}".format(
|
||||||
|
self.location
|
||||||
|
)
|
||||||
|
|
||||||
|
response = self.session.get(url)
|
||||||
|
response_json = json.loads(response.text.replace("{}&&", ""))
|
||||||
|
|
||||||
|
def get_region_type(match_type: str):
|
||||||
|
if match_type == "4":
|
||||||
|
return "2" #: zip
|
||||||
|
elif match_type == "2":
|
||||||
|
return "6" #: city
|
||||||
|
elif match_type == "1":
|
||||||
|
return "address" #: address, needs to be handled differently
|
||||||
|
|
||||||
|
if response_json["payload"]["exactMatch"] is not None:
|
||||||
|
target = response_json["payload"]["exactMatch"]
|
||||||
|
else:
|
||||||
|
target = response_json["payload"]["sections"][0]["rows"][0]
|
||||||
|
|
||||||
|
return target["id"].split("_")[1], get_region_type(target["type"])
|
||||||
|
|
||||||
|
def _parse_home(self, home: dict, single_search: bool = False) -> Property:
|
||||||
|
def get_value(key: str) -> Any | None:
|
||||||
|
if key in home and "value" in home[key]:
|
||||||
|
return home[key]["value"]
|
||||||
|
|
||||||
|
if not single_search:
|
||||||
|
address = Address(
|
||||||
|
address_one=get_value("streetLine"),
|
||||||
|
city=home["city"],
|
||||||
|
state=home["state"],
|
||||||
|
zip_code=home["zip"],
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
address_info = home["streetAddress"]
|
||||||
|
|
||||||
|
address = Address(
|
||||||
|
address_one=address_info["assembledAddress"],
|
||||||
|
city=home["city"],
|
||||||
|
state=home["state"],
|
||||||
|
zip_code=home["zip"],
|
||||||
|
)
|
||||||
|
url = "https://www.redfin.com{}".format(home["url"])
|
||||||
|
property_type = home["propertyType"] if "propertyType" in home else None
|
||||||
|
lot_size_data = home.get("lotSize")
|
||||||
|
if not isinstance(lot_size_data, int):
|
||||||
|
lot_size = (
|
||||||
|
lot_size_data.get("value", None)
|
||||||
|
if isinstance(lot_size_data, dict)
|
||||||
|
else None
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
lot_size = lot_size_data
|
||||||
|
|
||||||
|
return Property(
|
||||||
|
site_name=self.site_name,
|
||||||
|
listing_type=self.listing_type,
|
||||||
|
address=address,
|
||||||
|
url=url,
|
||||||
|
beds=home["beds"] if "beds" in home else None,
|
||||||
|
baths=home["baths"] if "baths" in home else None,
|
||||||
|
stories=home["stories"] if "stories" in home else None,
|
||||||
|
agent_name=get_value("listingAgent"),
|
||||||
|
description=home["listingRemarks"] if "listingRemarks" in home else None,
|
||||||
|
year_built=get_value("yearBuilt")
|
||||||
|
if not single_search
|
||||||
|
else home["yearBuilt"],
|
||||||
|
square_feet=get_value("sqFt"),
|
||||||
|
lot_size=lot_size,
|
||||||
|
property_type=PropertyType.from_int_code(home.get("propertyType")),
|
||||||
|
price_per_square_foot=get_value("pricePerSqFt"),
|
||||||
|
price=get_value("price"),
|
||||||
|
mls_id=get_value("mlsId"),
|
||||||
|
)
|
||||||
|
|
||||||
|
def _parse_building(self, building: dict) -> Building:
|
||||||
|
return Building(
|
||||||
|
address=Address(
|
||||||
|
address_one=" ".join(
|
||||||
|
[
|
||||||
|
building['address']['streetNumber'],
|
||||||
|
building['address']['directionalPrefix'],
|
||||||
|
building['address']['streetName'],
|
||||||
|
building['address']['streetType'],
|
||||||
|
]
|
||||||
|
),
|
||||||
|
city=building['address']['city'],
|
||||||
|
state=building['address']['stateOrProvinceCode'],
|
||||||
|
zip_code=building['address']['postalCode'],
|
||||||
|
address_two=" ".join(
|
||||||
|
[
|
||||||
|
building['address']['unitType'],
|
||||||
|
building['address']['unitValue'],
|
||||||
|
]
|
||||||
|
)
|
||||||
|
),
|
||||||
|
site_name=self.site_name,
|
||||||
|
url="https://www.redfin.com{}".format(building["url"]),
|
||||||
|
listing_type=self.listing_type,
|
||||||
|
num_units=building["numUnitsForSale"],
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def handle_address(self, home_id: str):
|
||||||
|
"""
|
||||||
|
EPs:
|
||||||
|
https://www.redfin.com/stingray/api/home/details/initialInfo?al=1&path=/TX/Austin/70-Rainey-St-78701/unit-1608/home/147337694
|
||||||
|
https://www.redfin.com/stingray/api/home/details/mainHouseInfoPanelInfo?propertyId=147337694&accessLevel=3
|
||||||
|
https://www.redfin.com/stingray/api/home/details/aboveTheFold?propertyId=147337694&accessLevel=3
|
||||||
|
https://www.redfin.com/stingray/api/home/details/belowTheFold?propertyId=147337694&accessLevel=3
|
||||||
|
"""
|
||||||
|
|
||||||
|
url = "https://www.redfin.com/stingray/api/home/details/aboveTheFold?propertyId={}&accessLevel=3".format(
|
||||||
|
home_id
|
||||||
|
)
|
||||||
|
|
||||||
|
response = self.session.get(url)
|
||||||
|
response_json = json.loads(response.text.replace("{}&&", ""))
|
||||||
|
|
||||||
|
parsed_home = self._parse_home(
|
||||||
|
response_json["payload"]["addressSectionInfo"], single_search=True
|
||||||
|
)
|
||||||
|
return [parsed_home]
|
||||||
|
|
||||||
|
def search(self):
|
||||||
|
region_id, region_type = self._handle_location()
|
||||||
|
|
||||||
|
if region_type == "address":
|
||||||
|
home_id = region_id
|
||||||
|
return self.handle_address(home_id)
|
||||||
|
|
||||||
|
url = "https://www.redfin.com/stingray/api/gis?al=1®ion_id={}®ion_type={}".format(
|
||||||
|
region_id, region_type
|
||||||
|
)
|
||||||
|
|
||||||
|
response = self.session.get(url)
|
||||||
|
response_json = json.loads(response.text.replace("{}&&", ""))
|
||||||
|
|
||||||
|
homes = [
|
||||||
|
self._parse_home(home) for home in response_json["payload"]["homes"]
|
||||||
|
] + [
|
||||||
|
self._parse_building(building) for building in response_json["payload"]["buildings"].values()
|
||||||
|
]
|
||||||
|
|
||||||
|
return homes
|
||||||
|
|
@ -0,0 +1,210 @@
|
||||||
|
import re
|
||||||
|
import json
|
||||||
|
from ..models import Property, Address, Building, ListingType, PropertyType
|
||||||
|
from ....exceptions import NoResultsFound, PropertyNotFound
|
||||||
|
from .. import Scraper
|
||||||
|
|
||||||
|
|
||||||
|
class ZillowScraper(Scraper):
|
||||||
|
def __init__(self, scraper_input):
|
||||||
|
super().__init__(scraper_input)
|
||||||
|
self.listing_type = scraper_input.listing_type
|
||||||
|
if self.listing_type == ListingType.FOR_SALE:
|
||||||
|
self.url = f"https://www.zillow.com/homes/for_sale/{self.location}_rb/"
|
||||||
|
elif self.listing_type == ListingType.FOR_RENT:
|
||||||
|
self.url = f"https://www.zillow.com/homes/for_rent/{self.location}_rb/"
|
||||||
|
|
||||||
|
def search(self):
|
||||||
|
resp = self.session.get(self.url, headers=self._get_headers())
|
||||||
|
resp.raise_for_status()
|
||||||
|
content = resp.text
|
||||||
|
|
||||||
|
match = re.search(
|
||||||
|
r'<script id="__NEXT_DATA__" type="application/json">(.*?)</script>',
|
||||||
|
content,
|
||||||
|
re.DOTALL,
|
||||||
|
)
|
||||||
|
if not match:
|
||||||
|
raise NoResultsFound(
|
||||||
|
"No results were found for Zillow with the given Location."
|
||||||
|
)
|
||||||
|
|
||||||
|
json_str = match.group(1)
|
||||||
|
data = json.loads(json_str)
|
||||||
|
|
||||||
|
if "searchPageState" in data["props"]["pageProps"]:
|
||||||
|
houses = data["props"]["pageProps"]["searchPageState"]["cat1"][
|
||||||
|
"searchResults"
|
||||||
|
]["listResults"]
|
||||||
|
return [self._parse_home(house) for house in houses]
|
||||||
|
elif "gdpClientCache" in data["props"]["pageProps"]:
|
||||||
|
gdp_client_cache = json.loads(data["props"]["pageProps"]["gdpClientCache"])
|
||||||
|
main_key = list(gdp_client_cache.keys())[0]
|
||||||
|
|
||||||
|
property_data = gdp_client_cache[main_key]["property"]
|
||||||
|
property = self._get_single_property_page(property_data)
|
||||||
|
|
||||||
|
return [property]
|
||||||
|
raise PropertyNotFound("Specific property data not found in the response.")
|
||||||
|
|
||||||
|
def _parse_home(self, home: dict):
|
||||||
|
"""
|
||||||
|
This method is used when a user enters a generic location & zillow returns more than one property
|
||||||
|
"""
|
||||||
|
url = (
|
||||||
|
f"https://www.zillow.com{home['detailUrl']}"
|
||||||
|
if "zillow.com" not in home["detailUrl"]
|
||||||
|
else home["detailUrl"]
|
||||||
|
)
|
||||||
|
|
||||||
|
if "hdpData" in home and "homeInfo" in home["hdpData"]:
|
||||||
|
price_data = self._extract_price(home)
|
||||||
|
address = self._extract_address(home)
|
||||||
|
agent_name = self._extract_agent_name(home)
|
||||||
|
beds = home["hdpData"]["homeInfo"]["bedrooms"]
|
||||||
|
baths = home["hdpData"]["homeInfo"]["bathrooms"]
|
||||||
|
property_type = home["hdpData"]["homeInfo"].get("homeType")
|
||||||
|
|
||||||
|
return Property(
|
||||||
|
site_name=self.site_name,
|
||||||
|
address=address,
|
||||||
|
agent_name=agent_name,
|
||||||
|
url=url,
|
||||||
|
beds=beds,
|
||||||
|
baths=baths,
|
||||||
|
listing_type=self.listing_type,
|
||||||
|
property_type=PropertyType(property_type),
|
||||||
|
**price_data,
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
keys = ("addressStreet", "addressCity", "addressState", "addressZipcode")
|
||||||
|
address_one, city, state, zip_code = (home[key] for key in keys)
|
||||||
|
address_one, address_two = self._parse_address_two(address_one)
|
||||||
|
address = Address(address_one, city, state, zip_code, address_two)
|
||||||
|
|
||||||
|
building_info = self._extract_building_info(home)
|
||||||
|
return Building(
|
||||||
|
site_name=self.site_name, address=address, url=url, **building_info
|
||||||
|
)
|
||||||
|
|
||||||
|
def _get_single_property_page(self, property_data: dict):
|
||||||
|
"""
|
||||||
|
This method is used when a user enters the exact location & zillow returns just one property
|
||||||
|
"""
|
||||||
|
url = (
|
||||||
|
f"https://www.zillow.com{property_data['hdpUrl']}"
|
||||||
|
if "zillow.com" not in property_data["hdpUrl"]
|
||||||
|
else property_data["hdpUrl"]
|
||||||
|
)
|
||||||
|
address_data = property_data["address"]
|
||||||
|
address_one, address_two = self._parse_address_two(
|
||||||
|
address_data["streetAddress"]
|
||||||
|
)
|
||||||
|
address = Address(
|
||||||
|
address_one=address_one,
|
||||||
|
address_two=address_two,
|
||||||
|
city=address_data["city"],
|
||||||
|
state=address_data["state"],
|
||||||
|
zip_code=address_data["zipcode"],
|
||||||
|
)
|
||||||
|
property_type = property_data.get("homeType", None)
|
||||||
|
|
||||||
|
return Property(
|
||||||
|
site_name=self.site_name,
|
||||||
|
address=address,
|
||||||
|
url=url,
|
||||||
|
beds=property_data.get("bedrooms", None),
|
||||||
|
baths=property_data.get("bathrooms", None),
|
||||||
|
year_built=property_data.get("yearBuilt", None),
|
||||||
|
price=property_data.get("price", None),
|
||||||
|
lot_size=property_data.get("lotSize", None),
|
||||||
|
agent_name=property_data.get("attributionInfo", {}).get("agentName", None),
|
||||||
|
stories=property_data.get("resoFacts", {}).get("stories", None),
|
||||||
|
description=property_data.get("description", None),
|
||||||
|
mls_id=property_data.get("attributionInfo", {}).get("mlsId", None),
|
||||||
|
price_per_square_foot=property_data.get("resoFacts", {}).get(
|
||||||
|
"pricePerSquareFoot", None
|
||||||
|
),
|
||||||
|
square_feet=property_data.get("livingArea", None),
|
||||||
|
property_type=PropertyType(property_type),
|
||||||
|
listing_type=self.listing_type,
|
||||||
|
)
|
||||||
|
|
||||||
|
def _extract_building_info(self, home: dict) -> dict:
|
||||||
|
num_units = len(home["units"])
|
||||||
|
prices = [
|
||||||
|
int(unit["price"].replace("$", "").replace(",", "").split("+")[0])
|
||||||
|
for unit in home["units"]
|
||||||
|
]
|
||||||
|
return {
|
||||||
|
"listing_type": self.listing_type,
|
||||||
|
"num_units": len(home["units"]),
|
||||||
|
"min_unit_price": min(
|
||||||
|
(
|
||||||
|
int(unit["price"].replace("$", "").replace(",", "").split("+")[0])
|
||||||
|
for unit in home["units"]
|
||||||
|
)
|
||||||
|
),
|
||||||
|
"max_unit_price": max(
|
||||||
|
(
|
||||||
|
int(unit["price"].replace("$", "").replace(",", "").split("+")[0])
|
||||||
|
for unit in home["units"]
|
||||||
|
)
|
||||||
|
),
|
||||||
|
"avg_unit_price": sum(prices) // len(prices) if num_units else None,
|
||||||
|
}
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _extract_price(home: dict) -> dict:
|
||||||
|
price = int(home["hdpData"]["homeInfo"]["priceForHDP"])
|
||||||
|
square_feet = home["hdpData"]["homeInfo"].get("livingArea")
|
||||||
|
|
||||||
|
lot_size = home["hdpData"]["homeInfo"].get("lotAreaValue")
|
||||||
|
price_per_square_foot = price // square_feet if square_feet and price else None
|
||||||
|
|
||||||
|
return {
|
||||||
|
k: v
|
||||||
|
for k, v in locals().items()
|
||||||
|
if k in ["price", "square_feet", "lot_size", "price_per_square_foot"]
|
||||||
|
}
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _extract_agent_name(home: dict) -> str | None:
|
||||||
|
broker_str = home.get("brokerName", "")
|
||||||
|
match = re.search(r"Listing by: (.+)", broker_str)
|
||||||
|
return match.group(1) if match else None
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _parse_address_two(address_one: str):
|
||||||
|
apt_match = re.search(r"(APT\s*.+|#[\s\S]+)$", address_one, re.I)
|
||||||
|
address_two = apt_match.group().strip() if apt_match else None
|
||||||
|
address_one = (
|
||||||
|
address_one.replace(address_two, "").strip() if address_two else address_one
|
||||||
|
)
|
||||||
|
return address_one, address_two
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _extract_address(home: dict) -> Address:
|
||||||
|
keys = ("streetAddress", "city", "state", "zipcode")
|
||||||
|
address_one, city, state, zip_code = (
|
||||||
|
home["hdpData"]["homeInfo"][key] for key in keys
|
||||||
|
)
|
||||||
|
address_one, address_two = ZillowScraper._parse_address_two(address_one)
|
||||||
|
return Address(address_one, city, state, zip_code, address_two=address_two)
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def _get_headers():
|
||||||
|
return {
|
||||||
|
"authority": "parser-external.geo.moveaws.com",
|
||||||
|
"accept": "*/*",
|
||||||
|
"accept-language": "en-US,en;q=0.9",
|
||||||
|
"origin": "https://www.zillow.com",
|
||||||
|
"referer": "https://www.zillow.com/",
|
||||||
|
"sec-ch-ua": '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
|
||||||
|
"sec-ch-ua-mobile": "?0",
|
||||||
|
"sec-ch-ua-platform": '"Windows"',
|
||||||
|
"sec-fetch-dest": "empty",
|
||||||
|
"sec-fetch-mode": "cors",
|
||||||
|
"sec-fetch-site": "cross-site",
|
||||||
|
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36",
|
||||||
|
}
|
||||||
|
|
@ -1,14 +1,14 @@
|
||||||
|
class InvalidSite(Exception):
|
||||||
|
"""Raised when a provided site is does not exist."""
|
||||||
|
|
||||||
|
|
||||||
class InvalidListingType(Exception):
|
class InvalidListingType(Exception):
|
||||||
"""Raised when a provided listing type is does not exist."""
|
"""Raised when a provided listing type is does not exist."""
|
||||||
|
|
||||||
|
|
||||||
class InvalidDate(Exception):
|
class NoResultsFound(Exception):
|
||||||
"""Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23"""
|
"""Raised when no results are found for the given location"""
|
||||||
|
|
||||||
|
|
||||||
class AuthenticationError(Exception):
|
class PropertyNotFound(Exception):
|
||||||
"""Raised when there is an issue with the authentication process."""
|
"""Raised when no property is found for the given address"""
|
||||||
def __init__(self, *args, response):
|
|
||||||
super().__init__(*args)
|
|
||||||
|
|
||||||
self.response = response
|
|
||||||
|
|
|
||||||
|
|
@ -1,166 +0,0 @@
|
||||||
from __future__ import annotations
|
|
||||||
import pandas as pd
|
|
||||||
from datetime import datetime
|
|
||||||
from .core.scrapers.models import Property, ListingType, Advertisers
|
|
||||||
from .exceptions import InvalidListingType, InvalidDate
|
|
||||||
|
|
||||||
ordered_properties = [
|
|
||||||
"property_url",
|
|
||||||
"property_id",
|
|
||||||
"listing_id",
|
|
||||||
"mls",
|
|
||||||
"mls_id",
|
|
||||||
"status",
|
|
||||||
"text",
|
|
||||||
"style",
|
|
||||||
"full_street_line",
|
|
||||||
"street",
|
|
||||||
"unit",
|
|
||||||
"city",
|
|
||||||
"state",
|
|
||||||
"zip_code",
|
|
||||||
"beds",
|
|
||||||
"full_baths",
|
|
||||||
"half_baths",
|
|
||||||
"sqft",
|
|
||||||
"year_built",
|
|
||||||
"days_on_mls",
|
|
||||||
"list_price",
|
|
||||||
"list_price_min",
|
|
||||||
"list_price_max",
|
|
||||||
"list_date",
|
|
||||||
"sold_price",
|
|
||||||
"last_sold_date",
|
|
||||||
"assessed_value",
|
|
||||||
"estimated_value",
|
|
||||||
"tax",
|
|
||||||
"tax_history",
|
|
||||||
"new_construction",
|
|
||||||
"lot_sqft",
|
|
||||||
"price_per_sqft",
|
|
||||||
"latitude",
|
|
||||||
"longitude",
|
|
||||||
"neighborhoods",
|
|
||||||
"county",
|
|
||||||
"fips_code",
|
|
||||||
"stories",
|
|
||||||
"hoa_fee",
|
|
||||||
"parking_garage",
|
|
||||||
"agent_id",
|
|
||||||
"agent_name",
|
|
||||||
"agent_email",
|
|
||||||
"agent_phones",
|
|
||||||
"agent_mls_set",
|
|
||||||
"agent_nrds_id",
|
|
||||||
"broker_id",
|
|
||||||
"broker_name",
|
|
||||||
"builder_id",
|
|
||||||
"builder_name",
|
|
||||||
"office_id",
|
|
||||||
"office_mls_set",
|
|
||||||
"office_name",
|
|
||||||
"office_email",
|
|
||||||
"office_phones",
|
|
||||||
"nearby_schools",
|
|
||||||
"primary_photo",
|
|
||||||
"alt_photos",
|
|
||||||
]
|
|
||||||
|
|
||||||
|
|
||||||
def process_result(result: Property) -> pd.DataFrame:
|
|
||||||
prop_data = {prop: None for prop in ordered_properties}
|
|
||||||
prop_data.update(result.__dict__)
|
|
||||||
|
|
||||||
if "address" in prop_data:
|
|
||||||
address_data = prop_data["address"]
|
|
||||||
prop_data["full_street_line"] = address_data.full_line
|
|
||||||
prop_data["street"] = address_data.street
|
|
||||||
prop_data["unit"] = address_data.unit
|
|
||||||
prop_data["city"] = address_data.city
|
|
||||||
prop_data["state"] = address_data.state
|
|
||||||
prop_data["zip_code"] = address_data.zip
|
|
||||||
|
|
||||||
if "advertisers" in prop_data and prop_data.get("advertisers"):
|
|
||||||
advertiser_data: Advertisers | None = prop_data["advertisers"]
|
|
||||||
if advertiser_data.agent:
|
|
||||||
agent_data = advertiser_data.agent
|
|
||||||
prop_data["agent_id"] = agent_data.uuid
|
|
||||||
prop_data["agent_name"] = agent_data.name
|
|
||||||
prop_data["agent_email"] = agent_data.email
|
|
||||||
prop_data["agent_phones"] = agent_data.phones
|
|
||||||
prop_data["agent_mls_set"] = agent_data.mls_set
|
|
||||||
prop_data["agent_nrds_id"] = agent_data.nrds_id
|
|
||||||
|
|
||||||
if advertiser_data.broker:
|
|
||||||
broker_data = advertiser_data.broker
|
|
||||||
prop_data["broker_id"] = broker_data.uuid
|
|
||||||
prop_data["broker_name"] = broker_data.name
|
|
||||||
|
|
||||||
if advertiser_data.builder:
|
|
||||||
builder_data = advertiser_data.builder
|
|
||||||
prop_data["builder_id"] = builder_data.uuid
|
|
||||||
prop_data["builder_name"] = builder_data.name
|
|
||||||
|
|
||||||
if advertiser_data.office:
|
|
||||||
office_data = advertiser_data.office
|
|
||||||
prop_data["office_id"] = office_data.uuid
|
|
||||||
prop_data["office_name"] = office_data.name
|
|
||||||
prop_data["office_email"] = office_data.email
|
|
||||||
prop_data["office_phones"] = office_data.phones
|
|
||||||
prop_data["office_mls_set"] = office_data.mls_set
|
|
||||||
|
|
||||||
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
|
|
||||||
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)
|
|
||||||
|
|
||||||
return properties_df[ordered_properties]
|
|
||||||
|
|
||||||
|
|
||||||
def validate_input(listing_type: str) -> None:
|
|
||||||
if listing_type.upper() not in ListingType.__members__:
|
|
||||||
raise InvalidListingType(f"Provided listing type, '{listing_type}', does not exist.")
|
|
||||||
|
|
||||||
|
|
||||||
def validate_dates(date_from: str | None, date_to: str | None) -> 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:
|
|
||||||
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:
|
|
||||||
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.")
|
|
||||||
|
|
@ -1,15 +1,4 @@
|
||||||
# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
|
# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "annotated-types"
|
|
||||||
version = "0.7.0"
|
|
||||||
description = "Reusable constraint types to use with typing.Annotated"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
|
|
||||||
{file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "certifi"
|
name = "certifi"
|
||||||
|
|
@ -22,114 +11,88 @@ files = [
|
||||||
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "cfgv"
|
|
||||||
version = "3.4.0"
|
|
||||||
description = "Validate configuration and produce human readable error messages."
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
|
|
||||||
{file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "charset-normalizer"
|
name = "charset-normalizer"
|
||||||
version = "3.3.0"
|
version = "3.2.0"
|
||||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||||
optional = false
|
optional = false
|
||||||
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|
||||||
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|
||||||
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|
||||||
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|
||||||
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|
||||||
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|
||||||
{file = "charset_normalizer-3.3.0-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:c2af80fb58f0f24b3f3adcb9148e6203fa67dd3f61c4af146ecad033024dde43"},
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|
||||||
{file = "charset_normalizer-3.3.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:153e7b6e724761741e0974fc4dcd406d35ba70b92bfe3fedcb497226c93b9da7"},
|
|
||||||
{file = "charset_normalizer-3.3.0-cp39-cp39-win32.whl", hash = "sha256:d47ecf253780c90ee181d4d871cd655a789da937454045b17b5798da9393901a"},
|
|
||||||
{file = "charset_normalizer-3.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:d97d85fa63f315a8bdaba2af9a6a686e0eceab77b3089af45133252618e70884"},
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|
||||||
{file = "charset_normalizer-3.3.0-py3-none-any.whl", hash = "sha256:e46cd37076971c1040fc8c41273a8b3e2c624ce4f2be3f5dfcb7a430c1d3acc2"},
|
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
|
|
@ -143,17 +106,6 @@ files = [
|
||||||
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
|
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "distlib"
|
|
||||||
version = "0.3.8"
|
|
||||||
description = "Distribution utilities"
|
|
||||||
optional = false
|
|
||||||
python-versions = "*"
|
|
||||||
files = [
|
|
||||||
{file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"},
|
|
||||||
{file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "exceptiongroup"
|
name = "exceptiongroup"
|
||||||
version = "1.1.3"
|
version = "1.1.3"
|
||||||
|
|
@ -168,36 +120,6 @@ files = [
|
||||||
[package.extras]
|
[package.extras]
|
||||||
test = ["pytest (>=6)"]
|
test = ["pytest (>=6)"]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "filelock"
|
|
||||||
version = "3.13.4"
|
|
||||||
description = "A platform independent file lock."
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "filelock-3.13.4-py3-none-any.whl", hash = "sha256:404e5e9253aa60ad457cae1be07c0f0ca90a63931200a47d9b6a6af84fd7b45f"},
|
|
||||||
{file = "filelock-3.13.4.tar.gz", hash = "sha256:d13f466618bfde72bd2c18255e269f72542c6e70e7bac83a0232d6b1cc5c8cf4"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
|
|
||||||
testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
|
|
||||||
typing = ["typing-extensions (>=4.8)"]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "identify"
|
|
||||||
version = "2.5.35"
|
|
||||||
description = "File identification library for Python"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "identify-2.5.35-py2.py3-none-any.whl", hash = "sha256:c4de0081837b211594f8e877a6b4fad7ca32bbfc1a9307fdd61c28bfe923f13e"},
|
|
||||||
{file = "identify-2.5.35.tar.gz", hash = "sha256:10a7ca245cfcd756a554a7288159f72ff105ad233c7c4b9c6f0f4d108f5f6791"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
license = ["ukkonen"]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "idna"
|
name = "idna"
|
||||||
version = "3.4"
|
version = "3.4"
|
||||||
|
|
@ -221,19 +143,39 @@ files = [
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "nodeenv"
|
name = "numpy"
|
||||||
version = "1.8.0"
|
version = "1.25.2"
|
||||||
description = "Node.js virtual environment builder"
|
description = "Fundamental package for array computing in Python"
|
||||||
optional = false
|
optional = false
|
||||||
python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
|
python-versions = ">=3.9"
|
||||||
files = [
|
files = [
|
||||||
{file = "nodeenv-1.8.0-py2.py3-none-any.whl", hash = "sha256:df865724bb3c3adc86b3876fa209771517b0cfe596beff01a92700e0e8be4cec"},
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||||||
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||||||
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|
||||||
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|
||||||
|
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|
||||||
|
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|
||||||
|
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|
||||||
|
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||||||
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||||||
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||||||
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{file = "numpy-1.25.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:60e7f0f7f6d0eee8364b9a6304c2845b9c491ac706048c7e8cf47b83123b8dbf"},
|
||||||
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|
||||||
|
{file = "numpy-1.25.2-cp311-cp311-win32.whl", hash = "sha256:5883c06bb92f2e6c8181df7b39971a5fb436288db58b5a1c3967702d4278691d"},
|
||||||
|
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||||||
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|
||||||
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{file = "numpy-1.25.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:eb942bfb6f84df5ce05dbf4b46673ffed0d3da59f13635ea9b926af3deb76926"},
|
||||||
|
{file = "numpy-1.25.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3e0746410e73384e70d286f93abf2520035250aad8c5714240b0492a7302fdca"},
|
||||||
|
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|
||||||
|
{file = "numpy-1.25.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:8b77775f4b7df768967a7c8b3567e309f617dd5e99aeb886fa14dc1a0791141f"},
|
||||||
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{file = "numpy-1.25.2-cp39-cp39-win32.whl", hash = "sha256:2792d23d62ec51e50ce4d4b7d73de8f67a2fd3ea710dcbc8563a51a03fb07b01"},
|
||||||
|
{file = "numpy-1.25.2-cp39-cp39-win_amd64.whl", hash = "sha256:76b4115d42a7dfc5d485d358728cdd8719be33cc5ec6ec08632a5d6fca2ed380"},
|
||||||
|
{file = "numpy-1.25.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1a1329e26f46230bf77b02cc19e900db9b52f398d6722ca853349a782d4cff55"},
|
||||||
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{file = "numpy-1.25.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c3abc71e8b6edba80a01a52e66d83c5d14433cbcd26a40c329ec7ed09f37901"},
|
||||||
|
{file = "numpy-1.25.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:1b9735c27cea5d995496f46a8b1cd7b408b3f34b6d50459d9ac8fe3a20cc17bf"},
|
||||||
|
{file = "numpy-1.25.2.tar.gz", hash = "sha256:fd608e19c8d7c55021dffd43bfe5492fab8cc105cc8986f813f8c3c048b38760"},
|
||||||
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|
]
|
||||||
|
|
||||||
[package.dependencies]
|
|
||||||
setuptools = "*"
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "numpy"
|
name = "numpy"
|
||||||
version = "1.26.0"
|
version = "1.26.0"
|
||||||
|
|
@ -277,54 +219,47 @@ files = [
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
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|
name = "packaging"
|
||||||
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|
version = "23.1"
|
||||||
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|
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|
||||||
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|
optional = false
|
||||||
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|
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|
||||||
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|
||||||
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|
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|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pandas"
|
name = "pandas"
|
||||||
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|
version = "2.1.0"
|
||||||
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|
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|
||||||
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|
optional = false
|
||||||
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|
python-versions = ">=3.9"
|
||||||
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{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]
|
[package.dependencies]
|
||||||
numpy = [
|
numpy = [
|
||||||
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
|
{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"
|
python-dateutil = ">=2.8.2"
|
||||||
pytz = ">=2020.1"
|
pytz = ">=2020.1"
|
||||||
|
|
@ -354,21 +289,6 @@ sql-other = ["SQLAlchemy (>=1.4.36)"]
|
||||||
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
|
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
|
||||||
xml = ["lxml (>=4.8.0)"]
|
xml = ["lxml (>=4.8.0)"]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "platformdirs"
|
|
||||||
version = "4.2.0"
|
|
||||||
description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "platformdirs-4.2.0-py3-none-any.whl", hash = "sha256:0614df2a2f37e1a662acbd8e2b25b92ccf8632929bc6d43467e17fe89c75e068"},
|
|
||||||
{file = "platformdirs-4.2.0.tar.gz", hash = "sha256:ef0cc731df711022c174543cb70a9b5bd22e5a9337c8624ef2c2ceb8ddad8768"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
|
|
||||||
test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pluggy"
|
name = "pluggy"
|
||||||
version = "1.3.0"
|
version = "1.3.0"
|
||||||
|
|
@ -384,134 +304,6 @@ files = [
|
||||||
dev = ["pre-commit", "tox"]
|
dev = ["pre-commit", "tox"]
|
||||||
testing = ["pytest", "pytest-benchmark"]
|
testing = ["pytest", "pytest-benchmark"]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pre-commit"
|
|
||||||
version = "3.7.0"
|
|
||||||
description = "A framework for managing and maintaining multi-language pre-commit hooks."
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.9"
|
|
||||||
files = [
|
|
||||||
{file = "pre_commit-3.7.0-py2.py3-none-any.whl", hash = "sha256:5eae9e10c2b5ac51577c3452ec0a490455c45a0533f7960f993a0d01e59decab"},
|
|
||||||
{file = "pre_commit-3.7.0.tar.gz", hash = "sha256:e209d61b8acdcf742404408531f0c37d49d2c734fd7cff2d6076083d191cb060"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.dependencies]
|
|
||||||
cfgv = ">=2.0.0"
|
|
||||||
identify = ">=1.0.0"
|
|
||||||
nodeenv = ">=0.11.1"
|
|
||||||
pyyaml = ">=5.1"
|
|
||||||
virtualenv = ">=20.10.0"
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pydantic"
|
|
||||||
version = "2.7.4"
|
|
||||||
description = "Data validation using Python type hints"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "pydantic-2.7.4-py3-none-any.whl", hash = "sha256:ee8538d41ccb9c0a9ad3e0e5f07bf15ed8015b481ced539a1759d8cc89ae90d0"},
|
|
||||||
{file = "pydantic-2.7.4.tar.gz", hash = "sha256:0c84efd9548d545f63ac0060c1e4d39bb9b14db8b3c0652338aecc07b5adec52"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.dependencies]
|
|
||||||
annotated-types = ">=0.4.0"
|
|
||||||
pydantic-core = "2.18.4"
|
|
||||||
typing-extensions = ">=4.6.1"
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
email = ["email-validator (>=2.0.0)"]
|
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pydantic-core"
|
|
||||||
version = "2.18.4"
|
|
||||||
description = "Core functionality for Pydantic validation and serialization"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
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|
||||||
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|
||||||
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|
||||||
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|
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|
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|
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|
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|
||||||
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|
||||||
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|
|
||||||
{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]]
|
[[package]]
|
||||||
name = "pytest"
|
name = "pytest"
|
||||||
version = "7.4.2"
|
version = "7.4.2"
|
||||||
|
|
@ -559,66 +351,6 @@ files = [
|
||||||
{file = "pytz-2023.3.post1.tar.gz", hash = "sha256:7b4fddbeb94a1eba4b557da24f19fdf9db575192544270a9101d8509f9f43d7b"},
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|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "pyyaml"
|
|
||||||
version = "6.0.1"
|
|
||||||
description = "YAML parser and emitter for Python"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.6"
|
|
||||||
files = [
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|
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||||||
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||||||
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|
||||||
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|
||||||
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|
||||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
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|
||||||
{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
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|
||||||
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|
||||||
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|
||||||
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|
|
||||||
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|
|
||||||
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|
|
||||||
]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "requests"
|
name = "requests"
|
||||||
version = "2.31.0"
|
version = "2.31.0"
|
||||||
|
|
@ -640,22 +372,6 @@ urllib3 = ">=1.21.1,<3"
|
||||||
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
||||||
use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
|
use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "setuptools"
|
|
||||||
version = "69.5.1"
|
|
||||||
description = "Easily download, build, install, upgrade, and uninstall Python packages"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
|
|
||||||
{file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
|
|
||||||
testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
|
|
||||||
testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "six"
|
name = "six"
|
||||||
version = "1.16.0"
|
version = "1.16.0"
|
||||||
|
|
@ -667,21 +383,6 @@ files = [
|
||||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||||
]
|
]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "tenacity"
|
|
||||||
version = "9.0.0"
|
|
||||||
description = "Retry code until it succeeds"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.8"
|
|
||||||
files = [
|
|
||||||
{file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"},
|
|
||||||
{file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
doc = ["reno", "sphinx"]
|
|
||||||
test = ["pytest", "tornado (>=4.5)", "typeguard"]
|
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "tomli"
|
name = "tomli"
|
||||||
version = "2.0.1"
|
version = "2.0.1"
|
||||||
|
|
@ -693,17 +394,6 @@ files = [
|
||||||
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
|
{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]]
|
[[package]]
|
||||||
name = "tzdata"
|
name = "tzdata"
|
||||||
version = "2023.3"
|
version = "2023.3"
|
||||||
|
|
@ -717,13 +407,13 @@ files = [
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "urllib3"
|
name = "urllib3"
|
||||||
version = "2.0.6"
|
version = "2.0.4"
|
||||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||||
optional = false
|
optional = false
|
||||||
python-versions = ">=3.7"
|
python-versions = ">=3.7"
|
||||||
files = [
|
files = [
|
||||||
{file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"},
|
{file = "urllib3-2.0.4-py3-none-any.whl", hash = "sha256:de7df1803967d2c2a98e4b11bb7d6bd9210474c46e8a0401514e3a42a75ebde4"},
|
||||||
{file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"},
|
{file = "urllib3-2.0.4.tar.gz", hash = "sha256:8d22f86aae8ef5e410d4f539fde9ce6b2113a001bb4d189e0aed70642d602b11"},
|
||||||
]
|
]
|
||||||
|
|
||||||
[package.extras]
|
[package.extras]
|
||||||
|
|
@ -732,27 +422,7 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
|
||||||
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
|
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||||
zstd = ["zstandard (>=0.18.0)"]
|
zstd = ["zstandard (>=0.18.0)"]
|
||||||
|
|
||||||
[[package]]
|
|
||||||
name = "virtualenv"
|
|
||||||
version = "20.25.1"
|
|
||||||
description = "Virtual Python Environment builder"
|
|
||||||
optional = false
|
|
||||||
python-versions = ">=3.7"
|
|
||||||
files = [
|
|
||||||
{file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
|
|
||||||
{file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
|
|
||||||
]
|
|
||||||
|
|
||||||
[package.dependencies]
|
|
||||||
distlib = ">=0.3.7,<1"
|
|
||||||
filelock = ">=3.12.2,<4"
|
|
||||||
platformdirs = ">=3.9.1,<5"
|
|
||||||
|
|
||||||
[package.extras]
|
|
||||||
docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
|
|
||||||
test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
|
|
||||||
|
|
||||||
[metadata]
|
[metadata]
|
||||||
lock-version = "2.0"
|
lock-version = "2.0"
|
||||||
python-versions = ">=3.9,<3.13"
|
python-versions = "^3.10"
|
||||||
content-hash = "cefc11b1bf5ad99d628f6d08f6f03003522cc1b6e48b519230d99d716a5c165c"
|
content-hash = "eede625d6d45085e143b0af246cb2ce00cff8579c667be3b63387c8594a5570d"
|
||||||
|
|
|
||||||
|
|
@ -1,25 +1,19 @@
|
||||||
[tool.poetry]
|
[tool.poetry]
|
||||||
name = "homeharvest"
|
name = "homeharvest"
|
||||||
version = "0.4.7"
|
version = "0.1.3"
|
||||||
description = "Real estate scraping library"
|
description = "Real estate scraping library"
|
||||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
|
||||||
homepage = "https://github.com/Bunsly/HomeHarvest"
|
homepage = "https://github.com/ZacharyHampton/HomeHarvest"
|
||||||
readme = "README.md"
|
readme = "README.md"
|
||||||
|
|
||||||
[tool.poetry.scripts]
|
|
||||||
homeharvest = "homeharvest.cli:main"
|
|
||||||
|
|
||||||
[tool.poetry.dependencies]
|
[tool.poetry.dependencies]
|
||||||
python = ">=3.9,<3.13"
|
python = "^3.10"
|
||||||
requests = "^2.31.0"
|
requests = "^2.31.0"
|
||||||
pandas = "^2.1.1"
|
pandas = "^2.1.0"
|
||||||
pydantic = "^2.7.4"
|
|
||||||
tenacity = "^9.0.0"
|
|
||||||
|
|
||||||
|
|
||||||
[tool.poetry.group.dev.dependencies]
|
[tool.poetry.group.dev.dependencies]
|
||||||
pytest = "^7.4.2"
|
pytest = "^7.4.2"
|
||||||
pre-commit = "^3.7.0"
|
|
||||||
|
|
||||||
[build-system]
|
[build-system]
|
||||||
requires = ["poetry-core"]
|
requires = ["poetry-core"]
|
||||||
|
|
|
||||||
|
|
@ -1,302 +1,12 @@
|
||||||
from homeharvest import scrape_property, Property
|
from homeharvest import scrape_property
|
||||||
import pandas as pd
|
|
||||||
|
|
||||||
|
|
||||||
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", 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)
|
|
||||||
|
|
||||||
|
|
||||||
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,
|
|
||||||
past_days=180,
|
|
||||||
listing_type="sold",
|
|
||||||
)
|
|
||||||
|
|
||||||
assert result is not None and len(result) > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_last_x_days_sold():
|
|
||||||
days_result_30 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=30)
|
|
||||||
|
|
||||||
days_result_10 = scrape_property(location="Dallas, TX", listing_type="sold", past_days=10)
|
|
||||||
|
|
||||||
assert all([result is not None for result in [days_result_30, days_result_10]]) and len(days_result_30) != len(
|
|
||||||
days_result_10
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_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(
|
|
||||||
location="15509 N 172nd Dr, Surprise, AZ 85388",
|
|
||||||
listing_type="for_sale",
|
|
||||||
),
|
|
||||||
scrape_property(
|
|
||||||
location="2530 Al Lipscomb Way",
|
|
||||||
listing_type="for_sale",
|
|
||||||
),
|
|
||||||
]
|
|
||||||
|
|
||||||
assert all([result is not None for result in results])
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor():
|
def test_realtor():
|
||||||
results = [
|
results = [
|
||||||
scrape_property(
|
scrape_property(location="2530 Al Lipscomb Way", site_name="realtor.com"),
|
||||||
location="2530 Al Lipscomb Way",
|
scrape_property(location="Phoenix, AZ", site_name="realtor.com"), #: does not support "city, state, USA" format
|
||||||
listing_type="for_sale",
|
scrape_property(location="Dallas, TX", site_name="realtor.com"), #: does not support "city, state, USA" format
|
||||||
),
|
scrape_property(location="85281", site_name="realtor.com"),
|
||||||
scrape_property(
|
|
||||||
location="Phoenix, AZ", listing_type="for_rent", limit=1000
|
|
||||||
), #: does not support "city, state, USA" format
|
|
||||||
scrape_property(
|
|
||||||
location="Dallas, TX", listing_type="sold", limit=1000
|
|
||||||
), #: does not support "city, state, USA" format
|
|
||||||
scrape_property(location="85281"),
|
|
||||||
]
|
]
|
||||||
|
|
||||||
assert all([result is not None for result in results])
|
assert all([result is not None for result in results])
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_city():
|
|
||||||
results = scrape_property(location="Atlanta, GA", listing_type="for_sale", limit=1000)
|
|
||||||
|
|
||||||
assert results is not None and len(results) > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_land():
|
|
||||||
results = scrape_property(location="Atlanta, GA", listing_type="for_sale", property_type=["land"], limit=1000)
|
|
||||||
|
|
||||||
assert results is not None and len(results) > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_bad_address():
|
|
||||||
bad_results = scrape_property(
|
|
||||||
location="abceefg ju098ot498hh9",
|
|
||||||
listing_type="for_sale",
|
|
||||||
)
|
|
||||||
|
|
||||||
if len(bad_results) == 0:
|
|
||||||
assert True
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_foreclosed():
|
|
||||||
foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=True)
|
|
||||||
|
|
||||||
not_foreclosed = scrape_property(location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=False)
|
|
||||||
|
|
||||||
assert len(foreclosed) != len(not_foreclosed)
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_agent():
|
|
||||||
scraped = scrape_property(location="Detroit, MI", listing_type="for_sale", limit=1000, extra_property_data=False)
|
|
||||||
assert scraped["agent_name"].nunique() > 1
|
|
||||||
|
|
||||||
|
|
||||||
def test_realtor_without_extra_details():
|
|
||||||
results = [
|
|
||||||
scrape_property(
|
|
||||||
location="00741",
|
|
||||||
listing_type="sold",
|
|
||||||
limit=10,
|
|
||||||
extra_property_data=False,
|
|
||||||
),
|
|
||||||
scrape_property(
|
|
||||||
location="00741",
|
|
||||||
listing_type="sold",
|
|
||||||
limit=10,
|
|
||||||
extra_property_data=True,
|
|
||||||
),
|
|
||||||
]
|
|
||||||
|
|
||||||
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,
|
|
||||||
limit=1000,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert results is not None and len(results) > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_primary_image_error():
|
|
||||||
results = scrape_property(
|
|
||||||
location="Spokane, PA",
|
|
||||||
listing_type="for_rent", # or (for_sale, for_rent, pending)
|
|
||||||
past_days=360,
|
|
||||||
radius=3,
|
|
||||||
extra_property_data=False,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert results is not None and len(results) > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_limit():
|
|
||||||
over_limit = 876
|
|
||||||
extra_params = {"limit": over_limit}
|
|
||||||
|
|
||||||
over_results = scrape_property(
|
|
||||||
location="Waddell, AZ",
|
|
||||||
listing_type="for_sale",
|
|
||||||
**extra_params,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert over_results is not None and len(over_results) <= over_limit
|
|
||||||
|
|
||||||
under_limit = 1
|
|
||||||
under_results = scrape_property(
|
|
||||||
location="Waddell, AZ",
|
|
||||||
listing_type="for_sale",
|
|
||||||
limit=under_limit,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert under_results is not None and len(under_results) == under_limit
|
|
||||||
|
|
||||||
|
|
||||||
def test_apartment_list_price():
|
|
||||||
results = scrape_property(
|
|
||||||
location="Spokane, WA",
|
|
||||||
listing_type="for_rent", # or (for_sale, for_rent, pending)
|
|
||||||
extra_property_data=False,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert results is not None
|
|
||||||
|
|
||||||
results = results[results["style"] == "APARTMENT"]
|
|
||||||
|
|
||||||
#: get percentage of results with atleast 1 of any column not none, list_price, list_price_min, list_price_max
|
|
||||||
assert (
|
|
||||||
len(results[results[["list_price", "list_price_min", "list_price_max"]].notnull().any(axis=1)]) / len(results)
|
|
||||||
> 0.5
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
def test_builder_exists():
|
|
||||||
listing = scrape_property(
|
|
||||||
location="18149 W Poston Dr, Surprise, AZ 85387",
|
|
||||||
extra_property_data=False,
|
|
||||||
)
|
|
||||||
|
|
||||||
assert listing is not None
|
|
||||||
assert listing["builder_name"].nunique() > 0
|
|
||||||
|
|
||||||
|
|
||||||
def test_phone_number_matching():
|
|
||||||
searches = [
|
|
||||||
scrape_property(
|
|
||||||
location="Phoenix, AZ",
|
|
||||||
listing_type="for_sale",
|
|
||||||
limit=100,
|
|
||||||
),
|
|
||||||
scrape_property(
|
|
||||||
location="Phoenix, AZ",
|
|
||||||
listing_type="for_sale",
|
|
||||||
limit=100,
|
|
||||||
),
|
|
||||||
]
|
|
||||||
|
|
||||||
assert all([search is not None for search in searches])
|
|
||||||
|
|
||||||
#: random row
|
|
||||||
row = searches[0][searches[0]["agent_phones"].notnull()].sample()
|
|
||||||
|
|
||||||
#: find matching row
|
|
||||||
matching_row = searches[1].loc[searches[1]["property_url"] == row["property_url"].values[0]]
|
|
||||||
|
|
||||||
#: assert phone numbers are the same
|
|
||||||
assert row["agent_phones"].values[0] == matching_row["agent_phones"].values[0]
|
|
||||||
|
|
||||||
|
|
||||||
def test_return_type():
|
|
||||||
results = {
|
|
||||||
"pandas": scrape_property(location="Surprise, AZ", listing_type="for_rent", limit=100),
|
|
||||||
"pydantic": scrape_property(location="Surprise, AZ", listing_type="for_rent", limit=100, return_type="pydantic"),
|
|
||||||
"raw": scrape_property(location="Surprise, AZ", listing_type="for_rent", limit=100, return_type="raw"),
|
|
||||||
}
|
|
||||||
|
|
||||||
assert isinstance(results["pandas"], pd.DataFrame)
|
|
||||||
assert isinstance(results["pydantic"][0], Property)
|
|
||||||
assert isinstance(results["raw"][0], dict)
|
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,12 @@
|
||||||
|
from homeharvest import scrape_property
|
||||||
|
|
||||||
|
|
||||||
|
def test_redfin():
|
||||||
|
results = [
|
||||||
|
scrape_property(location="2530 Al Lipscomb Way", site_name="redfin"),
|
||||||
|
scrape_property(location="Phoenix, AZ, USA", site_name="redfin"),
|
||||||
|
scrape_property(location="Dallas, TX, USA", site_name="redfin"),
|
||||||
|
scrape_property(location="85281", site_name="redfin"),
|
||||||
|
]
|
||||||
|
|
||||||
|
assert all([result is not None for result in results])
|
||||||
|
|
@ -0,0 +1,12 @@
|
||||||
|
from homeharvest import scrape_property
|
||||||
|
|
||||||
|
|
||||||
|
def test_zillow():
|
||||||
|
results = [
|
||||||
|
scrape_property(location="2530 Al Lipscomb Way", site_name="zillow"),
|
||||||
|
scrape_property(location="Phoenix, AZ, USA", site_name="zillow"),
|
||||||
|
scrape_property(location="Dallas, TX, USA", site_name="zillow"),
|
||||||
|
scrape_property(location="85281", site_name="zillow"),
|
||||||
|
]
|
||||||
|
|
||||||
|
assert all([result is not None for result in results])
|
||||||
Loading…
Reference in New Issue