[enh] date_to and date_from

homeharvest/__init__.py

@@ -1,10 +1,9 @@
 import warnings
 import pandas as pd
 from .core.scrapers import ScraperInput
-from .utils import process_result, ordered_properties, validate_input
+from .utils import process_result, ordered_properties, validate_input, validate_dates
 from .core.scrapers.realtor import RealtorScraper
 from .core.scrapers.models import ListingType
-from .exceptions import InvalidListingType, NoResultsFound
 
 
 def scrape_property(
@@ -14,6 +13,8 @@ def scrape_property(
     mls_only: bool = False,
     past_days: int = None,
     proxy: str = None,
+    date_from: str = None,
+    date_to: str = None,
 ) -> pd.DataFrame:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
@@ -22,9 +23,11 @@ def scrape_property(
     :param radius: Get properties within _ (e.g. 1.0) miles. Only applicable for individual addresses.
     :param mls_only: If set, fetches only listings with MLS IDs.
     :param past_days: Get properties sold or listed (dependent on your listing_type) in the last _ days.
+    :param date_from, date_to: Get properties sold or listed (dependent on your listing_type) between these dates. format: 2021-01-28
     :param proxy: Proxy to use for scraping
     """
     validate_input(listing_type)
+    validate_dates(date_from, date_to)
 
     scraper_input = ScraperInput(
         location=location,
@@ -33,6 +36,8 @@ def scrape_property(
         radius=radius,
         mls_only=mls_only,
         last_x_days=past_days,
+        date_from=date_from,
+        date_to=date_to,
     )
 
     site = RealtorScraper(scraper_input)
@@ -40,7 +45,7 @@ def scrape_property(
 
     properties_dfs = [process_result(result) for result in results]
     if not properties_dfs:
-        raise NoResultsFound("no results found for the query")
+        return pd.DataFrame()
 
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", category=FutureWarning)