- realtor.com default

README.md

@@ -29,6 +29,21 @@ pip install homeharvest
 
 ## Usage
 
+### Python 
+
+```py
+from homeharvest import scrape_property
+import pandas as pd
+
+properties: pd.DataFrame = scrape_property(
+    location="85281",
+    listing_type="for_rent" # for_sale / sold
+)
+
+#: Note, to export to CSV or Excel, use properties.to_csv() or properties.to_excel().
+print(properties)
+```
+
 ### CLI 
 
 ```bash
@@ -44,21 +59,6 @@ By default:
 - If `-f` or `--filename` is left blank, the default is `HomeHarvest_<current_timestamp>`.
 - If `-p` or `--proxy` is not provided, the scraper uses the local IP.
 - Use `-k` or `--keep_duplicates` to keep duplicate properties based on address. If not provided, duplicates will be removed.
-### Python 
-
-```py
-from homeharvest import scrape_property
-import pandas as pd
-
-properties: pd.DataFrame = scrape_property(
-    site_name=["zillow", "realtor.com", "redfin"],
-    location="85281",
-    listing_type="for_rent" # for_sale / sold
-)
-
-#: Note, to export to CSV or Excel, use properties.to_csv() or properties.to_excel().
-print(properties)
-```
 
 ## Output
 ```py

homeharvest/__init__.py

@@ -132,7 +132,7 @@ def _scrape_single_site(location: str, site_name: str, listing_type: str, proxy:
 
 def scrape_property(
     location: str,
-    site_name: Union[str, list[str]] = None,
+    site_name: Union[str, list[str]] = "realtor.com",
     listing_type: str = "for_sale",
     proxy: str = None,
     keep_duplicates: bool = False
@@ -140,12 +140,14 @@ def scrape_property(
     """
     Scrape property from various sites from a given location and listing type.
 
-    :returns: pd.DataFrame
+    :param keep_duplicates:
+    :param proxy:
     :param location: US Location (e.g. 'San Francisco, CA', 'Cook County, IL', '85281', '2530 Al Lipscomb Way')
     :param site_name: Site name or list of site names (e.g. ['realtor.com', 'zillow'], 'redfin')
     :param listing_type: Listing type (e.g. 'for_sale', 'for_rent', 'sold')
-    :return: pd.DataFrame containing properties
+    :returns: pd.DataFrame containing properties
     """
+
     if site_name is None:
         site_name = list(_scrapers.keys())