Merge pull request #128 from Alexandre-Shofstall/fix/python39-compat

Fix syntax of __init__ line 24

README.md

@@ -8,8 +8,6 @@
 - **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_
-
 ![homeharvest](https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/b3d5d727-e67b-4a9f-85d8-1e65fd18620a)
 
 ## Installation

homeharvest/__init__.py

@@ -4,13 +4,13 @@ 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.models import ListingType, SearchPropertyType, ReturnType, Property
-
+from typing import Union, Optional, List
 
 def scrape_property(
     location: str,
     listing_type: str = "for_sale",
     return_type: str = "pandas",
-    property_type: list[str] | None = None,
+    property_type: Optional[List[str]] = None,
     radius: float = None,
     mls_only: bool = False,
     past_days: int = None,
@@ -21,7 +21,7 @@ def scrape_property(
     extra_property_data: bool = True,
     exclude_pending: bool = False,
     limit: int = 10000
-) -> pd.DataFrame | list[dict] | list[Property]:
+) -> Union[pd.DataFrame, list[dict], list[Property]]:
     """
     Scrape properties from Realtor.com based on a given location and listing type.
     :param location: Location to search (e.g. "Dallas, TX", "85281", "2530 Al Lipscomb Way")

homeharvest/core/scrapers/realtor/__init__.py

@@ -121,7 +121,10 @@ class RealtorScraper(Scraper):
 
         property_info = response_json["data"]["home"]
 
-        return [self.process_property(property_info)]
+        if self.return_type != ReturnType.raw:
+            return [self.process_property(property_info)]
+        else:
+            return [property_info]
 
     @staticmethod
     def process_advertisers(advertisers: list[dict] | None) -> Advertisers | None:

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.4.8"
+version = "0.4.11"
 description = "Real estate scraping library"
 authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
 homepage = "https://github.com/Bunsly/HomeHarvest"

tests/test_realtor.py

@@ -292,11 +292,14 @@ def test_phone_number_matching():
 
 def test_return_type():
     results = {
-        "pandas": scrape_property(location="Surprise, AZ", listing_type="for_rent", limit=100),
+        "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"),
+        "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"),
+        "raw": [
+            scrape_property(location="Surprise, AZ", listing_type="for_rent", limit=100, return_type="raw"),
+            scrape_property(location="66642", listing_type="for_rent", limit=100, return_type="raw"),
+        ],
     }
 
-    assert isinstance(results["pandas"], pd.DataFrame)
+    assert all(isinstance(result, pd.DataFrame) for result in results["pandas"])
-    assert isinstance(results["pydantic"][0], Property)
+    assert all(isinstance(result[0], Property) for result in results["pydantic"])
-    assert isinstance(results["raw"][0], dict)
+    assert all(isinstance(result[0], dict) for result in results["raw"])