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README.md
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README.md
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<img src="https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/d1a2bf8b-09f5-4c57-b33a-0ada8a34f12d" width="400">
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<img src="https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/d1a2bf8b-09f5-4c57-b33a-0ada8a34f12d" width="400">
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**HomeHarvest** is a simple, yet comprehensive, real estate scraping library that extracts and formats data in the style of MLS listings.
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**HomeHarvest** is a real estate scraping library that extracts and formats data in the style of MLS listings.
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**Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
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**Not technical?** Try out the web scraping tool on our site at [tryhomeharvest.com](https://tryhomeharvest.com).
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@ -13,8 +13,6 @@
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- **Export Flexibility**: Options to save as either CSV or Excel.
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- **Export Flexibility**: Options to save as either CSV or Excel.
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- **Usage Modes**:
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- **Usage Modes**:
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- **Python**: For those who'd like to integrate scraping into their Python scripts.
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- **Python**: For those who'd like to integrate scraping into their Python scripts.
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- **CLI**: For users who prefer command-line operations.
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[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
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[Video Guide for HomeHarvest](https://youtu.be/J1qgNPgmSLI) - _updated for release v0.3.4_
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@ -46,9 +44,9 @@ properties = scrape_property(
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# date_from="2023-05-01", # alternative to past_days
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# date_from="2023-05-01", # alternative to past_days
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# date_to="2023-05-28",
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# date_to="2023-05-28",
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# foreclosure=True
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# mls_only=True, # only fetch MLS listings
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# mls_only=True, # only fetch MLS listings
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# proxy="http://user:pass@host:port" # use a proxy to change your IP address
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)
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)
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print(f"Number of properties: {len(properties)}")
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print(f"Number of properties: {len(properties)}")
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@ -57,7 +55,6 @@ properties.to_csv(filename, index=False)
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print(properties.head())
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print(properties.head())
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```
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```
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## Output
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## Output
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```plaintext
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```plaintext
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>>> properties.head()
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>>> properties.head()
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@ -94,37 +91,9 @@ Optional
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│
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│
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├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
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├── mls_only (True/False): If set, fetches only MLS listings (mainly applicable to 'sold' listings)
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│
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│
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├── foreclosure (True/False): If set, fetches only foreclosures
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│
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└── proxy (string): In format 'http://user:pass@host:port'
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└── proxy (string): In format 'http://user:pass@host:port'
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```
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### CLI
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```
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usage: homeharvest [-l {for_sale,for_rent,sold}] [-o {excel,csv}] [-f FILENAME] [-p PROXY] [-d DAYS] [-r RADIUS] [-m] [-c] location
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Home Harvest Property Scraper
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positional arguments:
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location Location to scrape (e.g., San Francisco, CA)
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options:
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-l {for_sale,for_rent,sold,pending}, --listing_type {for_sale,for_rent,sold,pending}
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Listing type to scrape
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-o {excel,csv}, --output {excel,csv}
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Output format
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-f FILENAME, --filename FILENAME
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Name of the output file (without extension)
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-p PROXY, --proxy PROXY
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Proxy to use for scraping
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-d DAYS, --days DAYS Sold/listed in last _ days filter.
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-r RADIUS, --radius RADIUS
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Get comparable properties within _ (e.g., 0.0) miles. Only applicable for individual addresses.
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-m, --mls_only If set, fetches only MLS listings.
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```
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```bash
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homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
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```
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```
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### Property Schema
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### Property Schema
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@ -176,20 +145,3 @@ The following exceptions may be raised when using HomeHarvest:
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- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
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- `InvalidListingType` - valid options: `for_sale`, `for_rent`, `sold`
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- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
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- `InvalidDate` - date_from or date_to is not in the format YYYY-MM-DD
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## Frequently Asked Questions
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---
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**Q: Encountering issues with your searches?**
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**A:** Try to broaden the parameters you're using. If problems persist, [submit an issue](https://github.com/ZacharyHampton/HomeHarvest/issues).
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---
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**Q: Received a Forbidden 403 response code?**
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**A:** This indicates that you have been blocked by Realtor.com for sending too many requests. We recommend:
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- Waiting a few seconds between requests.
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- Trying a VPN or using a proxy as a parameter to scrape_property() to change your IP address.
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---
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@ -15,6 +15,7 @@ def scrape_property(
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proxy: str = None,
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proxy: str = None,
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date_from: str = None,
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date_from: str = None,
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date_to: str = None,
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date_to: str = None,
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foreclosure: bool = None,
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) -> pd.DataFrame:
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) -> pd.DataFrame:
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"""
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"""
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Scrape properties from Realtor.com based on a given location and listing type.
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Scrape properties from Realtor.com based on a given location and listing type.
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@ -38,6 +39,7 @@ def scrape_property(
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last_x_days=past_days,
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last_x_days=past_days,
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date_from=date_from,
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date_from=date_from,
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date_to=date_to,
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date_to=date_to,
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foreclosure=foreclosure,
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)
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)
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site = RealtorScraper(scraper_input)
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site = RealtorScraper(scraper_input)
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@ -13,6 +13,7 @@ class ScraperInput:
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last_x_days: int | None = None
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last_x_days: int | None = None
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date_from: str | None = None
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date_from: str | None = None
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date_to: str | None = None
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date_to: str | None = None
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foreclosure: bool | None = None
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class Scraper:
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class Scraper:
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self.mls_only = scraper_input.mls_only
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self.mls_only = scraper_input.mls_only
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self.date_from = scraper_input.date_from
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self.date_from = scraper_input.date_from
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self.date_to = scraper_input.date_to
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self.date_to = scraper_input.date_to
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self.foreclosure = scraper_input.foreclosure
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def search(self) -> list[Property]:
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def search(self) -> list[Property]:
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...
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...
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)
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)
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listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
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listing_type = ListingType.FOR_SALE if self.listing_type == ListingType.PENDING else self.listing_type
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is_foreclosure = ""
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if 'foreclosure' in variables and variables['foreclosure'] == True:
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is_foreclosure = "foreclosure: true"
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if 'foreclosure' in variables and variables['foreclosure'] == False:
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is_foreclosure = "foreclosure: false"
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if search_type == "comps": #: comps search, came from an address
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if search_type == "comps": #: comps search, came from an address
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query = """query Property_search(
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query = """query Property_search(
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) {
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) {
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home_search(
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home_search(
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query: {
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query: {
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%s
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nearby: {
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nearby: {
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coordinates: $coordinates
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coordinates: $coordinates
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radius: $radius
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radius: $radius
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limit: 200
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limit: 200
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offset: $offset
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offset: $offset
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) %s""" % (
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) %s""" % (
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is_foreclosure,
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listing_type.value.lower(),
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listing_type.value.lower(),
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date_param,
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date_param,
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pending_or_contingent_param,
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pending_or_contingent_param,
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) {
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) {
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home_search(
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home_search(
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query: {
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query: {
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%s
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city: $city
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city: $city
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county: $county
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county: $county
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postal_code: $postal_code
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postal_code: $postal_code
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limit: 200
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limit: 200
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offset: $offset
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offset: $offset
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) %s""" % (
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) %s""" % (
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is_foreclosure,
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listing_type.value.lower(),
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listing_type.value.lower(),
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date_param,
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date_param,
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pending_or_contingent_param,
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pending_or_contingent_param,
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"postal_code": location_info.get("postal_code"),
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"postal_code": location_info.get("postal_code"),
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}
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}
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if self.foreclosure:
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search_variables['foreclosure'] = self.foreclosure
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result = self.general_search(search_variables, search_type=search_type)
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result = self.general_search(search_variables, search_type=search_type)
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total = result["total"]
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total = result["total"]
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homes = result["properties"]
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homes = result["properties"]
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[tool.poetry]
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[tool.poetry]
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name = "homeharvest"
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name = "homeharvest"
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version = "0.3.12"
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version = "0.3.12"
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description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
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description = "Real estate scraping library"
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authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/Bunsly/HomeHarvest"
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homepage = "https://github.com/Bunsly/HomeHarvest"
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readme = "README.md"
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readme = "README.md"
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python = ">=3.10,<3.13"
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python = ">=3.10,<3.13"
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requests = "^2.31.0"
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requests = "^2.31.0"
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pandas = "^2.1.1"
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pandas = "^2.1.1"
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openpyxl = "^3.1.2"
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[tool.poetry.group.dev.dependencies]
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[tool.poetry.group.dev.dependencies]
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if len(bad_results) == 0:
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if len(bad_results) == 0:
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assert True
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assert True
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def test_realtor_foreclosed():
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foreclosed = scrape_property(
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location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=True
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)
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not_foreclosed = scrape_property(
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location="Dallas, TX", listing_type="for_sale", past_days=100, foreclosure=False
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)
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assert len(foreclosed) != len(not_foreclosed)
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