[enh] date_to and date_from
parent
c597a78191
commit
4edad901c5
68
README.md
68
README.md
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@ -46,7 +46,11 @@ filename = f"HomeHarvest_{current_timestamp}.csv"
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properties = scrape_property(
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properties = scrape_property(
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location="San Diego, CA",
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location="San Diego, CA",
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listing_type="sold", # or (for_sale, for_rent, pending)
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listing_type="sold", # or (for_sale, for_rent, pending)
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past_days=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
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past_days=30, # sold in last 30 days - listed in last 30 days if (for_sale, for_rent)
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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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# 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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# 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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@ -57,34 +61,6 @@ 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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### 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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## Output
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## Output
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```plaintext
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```plaintext
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@ -115,11 +91,45 @@ Optional
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├── 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).
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├── 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).
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│ Example: 30 (fetches properties listed/sold in the last 30 days)
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│ Example: 30 (fetches properties listed/sold in the last 30 days)
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│
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│
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├── date_range (string tuple): Start and end dates to filter properties listed or sold, both dates are required.
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} (use this to get properties in chunks as there's a 10k result limit)
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│ Format for both must be "YYYY-MM-DD".
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│ Example: ("2023-05-01", "2023-05-15") (fetches properties listed/sold between these dates)
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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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└── 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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```
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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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### Property Schema
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### Property Schema
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```plaintext
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```plaintext
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Property
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Property
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@ -1,10 +1,9 @@
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import warnings
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import warnings
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import pandas as pd
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import pandas as pd
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from .core.scrapers import ScraperInput
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from .core.scrapers import ScraperInput
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from .utils import process_result, ordered_properties, validate_input
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from .utils import process_result, ordered_properties, validate_input, validate_dates
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from .core.scrapers.realtor import RealtorScraper
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from .core.scrapers.realtor import RealtorScraper
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from .core.scrapers.models import ListingType
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from .core.scrapers.models import ListingType
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from .exceptions import InvalidListingType, NoResultsFound
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def scrape_property(
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def scrape_property(
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@ -14,6 +13,8 @@ def scrape_property(
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mls_only: bool = False,
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mls_only: bool = False,
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past_days: int = None,
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past_days: int = None,
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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_to: str = 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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@ -22,9 +23,11 @@ def scrape_property(
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:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
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:param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
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:param mls_only: If set, fetches only listings with MLS IDs.
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:param mls_only: If set, fetches only listings with MLS IDs.
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:param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
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:param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
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:param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
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:param proxy: Proxy to use for scraping
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:param proxy: Proxy to use for scraping
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"""
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"""
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validate_input(listing_type)
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validate_input(listing_type)
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validate_dates(date_from, date_to)
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scraper_input = ScraperInput(
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scraper_input = ScraperInput(
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location=location,
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location=location,
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@ -33,6 +36,8 @@ def scrape_property(
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radius=radius,
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radius=radius,
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mls_only=mls_only,
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mls_only=mls_only,
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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_to=date_to,
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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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@ -40,7 +45,7 @@ def scrape_property(
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properties_dfs = [process_result(result) for result in results]
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properties_dfs = [process_result(result) for result in results]
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if not properties_dfs:
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if not properties_dfs:
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raise NoResultsFound("no results found for the query")
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return pd.DataFrame()
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with warnings.catch_warnings():
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", category=FutureWarning)
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warnings.simplefilter("ignore", category=FutureWarning)
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@ -11,6 +11,8 @@ class ScraperInput:
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mls_only: bool | None = None
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mls_only: bool | None = None
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proxy: str | None = None
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proxy: str | None = None
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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_to: str | None = None
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class Scraper:
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class Scraper:
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self.radius = scraper_input.radius
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self.radius = scraper_input.radius
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self.last_x_days = scraper_input.last_x_days
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self.last_x_days = scraper_input.last_x_days
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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_to = scraper_input.date_to
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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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@ -9,7 +9,6 @@ from typing import Dict, Union, Optional
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from .. import Scraper
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from .. import Scraper
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from ....exceptions import NoResultsFound
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from ..models import Property, Address, ListingType, Description
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from ..models import Property, Address, ListingType, Description
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@ -38,7 +37,7 @@ class RealtorScraper(Scraper):
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result = response_json["autocomplete"]
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result = response_json["autocomplete"]
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if not result:
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if not result:
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raise NoResultsFound("No results found for location: " + self.location)
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return None
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return result[0]
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return result[0]
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@ -336,15 +335,17 @@ class RealtorScraper(Scraper):
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}
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}
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}"""
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}"""
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date_param = (
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date_param = ""
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'sold_date: { min: "$today-%sD" }' % self.last_x_days
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if self.listing_type == ListingType.SOLD:
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if self.listing_type == ListingType.SOLD and self.last_x_days
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if self.date_from and self.date_to:
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else (
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date_param = f'sold_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
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'list_date: { min: "$today-%sD" }' % self.last_x_days
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elif self.last_x_days:
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if self.last_x_days
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date_param = f'sold_date: {{ min: "$today-{self.last_x_days}D" }}'
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else ""
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else:
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)
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if self.date_from and self.date_to:
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)
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date_param = f'list_date: {{ min: "{self.date_from}", max: "{self.date_to}" }}'
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elif self.last_x_days:
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date_param = f'list_date: {{ min: "$today-{self.last_x_days}D" }}'
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sort_param = (
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sort_param = (
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"sort: [{ field: sold_date, direction: desc }]"
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"sort: [{ field: sold_date, direction: desc }]"
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@ -509,6 +510,9 @@ class RealtorScraper(Scraper):
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def search(self):
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def search(self):
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location_info = self.handle_location()
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location_info = self.handle_location()
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if not location_info:
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return []
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location_type = location_info["area_type"]
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location_type = location_info["area_type"]
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search_variables = {
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search_variables = {
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class InvalidListingType(Exception):
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class InvalidListingType(Exception):
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"""Raised when a provided listing type is does not exist."""
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"""Raised when a provided listing type is does not exist."""
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class InvalidDate(Exception):
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class NoResultsFound(Exception):
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"""Raised when only one of date_from or date_to is provided or not in the correct format. ex: 2023-10-23 """
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"""Raised when no results are found for the given location"""
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from .core.scrapers.models import Property, ListingType
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import pandas as pd
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import pandas as pd
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from .exceptions import InvalidListingType
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from datetime import datetime
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from .core.scrapers.models import Property, ListingType
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from .exceptions import InvalidListingType, InvalidDate
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ordered_properties = [
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ordered_properties = [
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"property_url",
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"property_url",
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raise InvalidListingType(
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raise InvalidListingType(
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f"Provided listing type, '{listing_type}', does not exist."
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f"Provided listing type, '{listing_type}', does not exist."
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)
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)
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def validate_dates(date_from: str | None, date_to: str | None) -> None:
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if (date_from is not None and date_to is None) or (date_from is None and date_to is not None):
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raise InvalidDate("Both date_from and date_to must be provided.")
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if date_from and date_to:
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try:
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date_from_obj = datetime.strptime(date_from, "%Y-%m-%d")
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date_to_obj = datetime.strptime(date_to, "%Y-%m-%d")
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if date_to_obj < date_from_obj:
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raise InvalidDate("date_to must be after date_from.")
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except ValueError as e:
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raise InvalidDate(f"Invalid date format or range")
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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 = "0.3.7"
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version = "0.3.8"
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description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
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description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
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authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
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authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
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homepage = "https://github.com/Bunsly/HomeHarvest"
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homepage = "https://github.com/Bunsly/HomeHarvest"
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from homeharvest import scrape_property
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from homeharvest import scrape_property
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from homeharvest.exceptions import (
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from homeharvest.exceptions import (
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InvalidListingType,
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InvalidListingType,
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NoResultsFound,
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)
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)
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@ -85,6 +84,20 @@ def test_realtor_last_x_days_sold():
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) and len(days_result_30) != len(days_result_10)
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) and len(days_result_30) != len(days_result_10)
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def test_realtor_date_range_sold():
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days_result_30 = scrape_property(
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location="Dallas, TX", listing_type="sold", date_from="2023-05-01", date_to="2023-05-28"
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)
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days_result_60 = scrape_property(
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location="Dallas, TX", listing_type="sold", date_from="2023-04-01", date_to="2023-06-10"
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)
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assert all(
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[result is not None for result in [days_result_30, days_result_60]]
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) and len(days_result_30) < len(days_result_60)
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def test_realtor_single_property():
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def test_realtor_single_property():
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results = [
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results = [
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scrape_property(
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scrape_property(
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@ -117,15 +130,12 @@ def test_realtor():
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assert all([result is not None for result in results])
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assert all([result is not None for result in results])
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bad_results = []
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try:
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def test_realtor_bad_address():
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bad_results += [
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bad_results = scrape_property(
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scrape_property(
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location="abceefg ju098ot498hh9",
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location="abceefg ju098ot498hh9",
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listing_type="for_sale",
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listing_type="for_sale",
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)
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)
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if len(bad_results) == 0:
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]
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except (InvalidListingType, NoResultsFound):
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assert True
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assert True
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assert all([result is None for result in bad_results])
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