chore: update version number

fix: proxy add to session correctly

.gitignore

@@ -3,4 +3,5 @@
 **/__pycache__/
 **/.pytest_cache/
 *.pyc
-/.ipynb_checkpoints/
+/.ipynb_checkpoints/
+*.csv

HomeHarvest_Demo.ipynb

@@ -55,7 +55,7 @@
     "    location=\"2530 Al Lipscomb Way\",\n",
     "    site_name=\"zillow\",\n",
     "    listing_type=\"for_sale\"\n",
-    "),"
+    ")"
    ]
   },
   {

README.md

@@ -9,17 +9,36 @@
 
 - Scrapes properties from **Zillow**, **Realtor.com** & **Redfin** simultaneously
 - Aggregates the properties in a Pandas DataFrame
-  
+
+[Video Guide for HomeHarvest](https://www.youtube.com/watch?v=HCoHoiJdWQY)
+
 ![homeharvest](https://github.com/ZacharyHampton/HomeHarvest/assets/78247585/b3d5d727-e67b-4a9f-85d8-1e65fd18620a)
 
 ## Installation
 
 ```bash
-pip install --upgrade homeharvest
+pip install homeharvest
 ```
   _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_ 
-  
+
 ## Usage
+
+### CLI 
+
+```bash
+homeharvest "San Francisco, CA" -s zillow realtor.com redfin -l for_rent -o excel -f HomeHarvest
+```
+
+This will scrape properties from the specified sites for the given location and listing type, and save the results to an Excel file named `HomeHarvest.xlsx`.
+
+By default:
+- If `-s` or `--site_name` is not provided, it will scrape from all available sites.
+- If `-l` or `--listing_type` is left blank, the default is `for_sale`. Other options are `for_rent` or `sold`.
+- The `-o` or `--output` default format is `excel`. Options are `csv` or `excel`.
+- 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.
+### Python 
+
 ```py
 from homeharvest import scrape_property
 import pandas as pd
@@ -33,16 +52,17 @@ properties: pd.DataFrame = scrape_property(
 #: Note, to export to CSV or Excel, use properties.to_csv() or properties.to_excel().
 print(properties)
 ```
+
 ## Output
 ```py
 >>> properties.head()
-                           street   city  ... mls_id description
-0                 420 N  Scottsdale Rd  Tempe  ...    NaN         NaN
-1                1255 E  University Dr  Tempe  ...    NaN         NaN
-2              1979 E  Rio Salado Pkwy  Tempe  ...    NaN         NaN
-3                      548 S Wilson St  Tempe  ...   None        None
-4  945 E  Playa Del Norte Dr Unit 4027  Tempe  ...    NaN         NaN
-[5 rows x 23 columns]
+                                        property_url site_name listing_type  apt_min_price  apt_max_price   ...  
+0  https://www.redfin.com/AZ/Tempe/1003-W-Washing...    redfin     for_rent         1666.0         2750.0   ... 
+1  https://www.redfin.com/AZ/Tempe/VELA-at-Town-L...    redfin     for_rent         1665.0         3763.0   ...  
+2  https://www.redfin.com/AZ/Tempe/Camden-Tempe/a...    redfin     for_rent         1939.0         3109.0   ...  
+3  https://www.redfin.com/AZ/Tempe/Emerson-Park/a...    redfin     for_rent         1185.0         1817.0   ... 
+4  https://www.redfin.com/AZ/Tempe/Rio-Paradiso-A...    redfin     for_rent         1470.0         2235.0   ...   
+[5 rows x 41 columns]
 ```
 
 ### Parameters for `scrape_properties()`
@@ -52,6 +72,7 @@ Required
 └── listing_type (enum): for_rent, for_sale, sold
 Optional
 ├── site_name (List[enum], default=all three sites): zillow, realtor.com, redfin
+├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
 ```
 
 ### Property Schema
@@ -102,7 +123,14 @@ Property
 │   └── bldg_min_area (int)
 
 └── Apartment Details (for property type: apartment):
-    └── apt_min_price (int)
+    ├── apt_min_beds: int
+    ├── apt_max_beds: int
+    ├── apt_min_baths: float
+    ├── apt_max_baths: float
+    ├── apt_min_price: int
+    ├── apt_max_price: int
+    ├── apt_min_sqft: int
+    ├── apt_max_sqft: int
 ```
 ## Supported Countries for Property Scraping
 

homeharvest/__init__.py

@@ -18,7 +18,7 @@ _scrapers = {
 }
 
 
-def validate_input(site_name: str, listing_type: str) -> None:
+def _validate_input(site_name: str, listing_type: str) -> None:
     if site_name.lower() not in _scrapers:
         raise InvalidSite(f"Provided site, '{site_name}', does not exist.")
 
@@ -28,7 +28,7 @@ def validate_input(site_name: str, listing_type: str) -> None:
         )
 
 
-def get_ordered_properties(result: Property) -> list[str]:
+def _get_ordered_properties(result: Property) -> list[str]:
     return [
         "property_url",
         "site_name",
@@ -38,6 +38,13 @@ def get_ordered_properties(result: Property) -> list[str]:
         "currency",
         "price",
         "apt_min_price",
+        "apt_max_price",
+        "apt_min_sqft",
+        "apt_max_sqft",
+        "apt_min_beds",
+        "apt_max_beds",
+        "apt_min_baths",
+        "apt_max_baths",
         "tax_assessed_value",
         "square_feet",
         "price_per_sqft",
@@ -61,14 +68,14 @@ def get_ordered_properties(result: Property) -> list[str]:
         "year_built",
         "agent_name",
         "mls_id",
-        "description",
         "img_src",
         "latitude",
         "longitude",
+        "description",
     ]
 
 
-def process_result(result: Property) -> pd.DataFrame:
+def _process_result(result: Property) -> pd.DataFrame:
     prop_data = result.__dict__
 
     prop_data["site_name"] = prop_data["site_name"].value
@@ -89,29 +96,30 @@ def process_result(result: Property) -> pd.DataFrame:
         del prop_data["address"]
 
     properties_df = pd.DataFrame([prop_data])
-    properties_df = properties_df[get_ordered_properties(result)]
+    properties_df = properties_df[_get_ordered_properties(result)]
 
     return properties_df
 
 
 def _scrape_single_site(
-    location: str, site_name: str, listing_type: str
+    location: str, site_name: str, listing_type: str, proxy: str = None
 ) -> pd.DataFrame:
     """
     Helper function to scrape a single site.
     """
-    validate_input(site_name, listing_type)
+    _validate_input(site_name, listing_type)
 
     scraper_input = ScraperInput(
         location=location,
         listing_type=ListingType[listing_type.upper()],
         site_name=SiteName.get_by_value(site_name.lower()),
+        proxy=proxy,
     )
 
     site = _scrapers[site_name.lower()](scraper_input)
     results = site.search()
 
-    properties_dfs = [process_result(result) for result in results]
+    properties_dfs = [_process_result(result) for result in results]
     properties_dfs = [
         df.dropna(axis=1, how="all") for df in properties_dfs if not df.empty
     ]
@@ -125,6 +133,7 @@ def scrape_property(
     location: str,
     site_name: Union[str, list[str]] = None,
     listing_type: str = "for_sale",
+    proxy: str = None,
 ) -> pd.DataFrame:
     """
     Scrape property from various sites from a given location and listing type.
@@ -144,13 +153,13 @@ def scrape_property(
     results = []
 
     if len(site_name) == 1:
-        final_df = _scrape_single_site(location, site_name[0], listing_type)
+        final_df = _scrape_single_site(location, site_name[0], listing_type, proxy)
         results.append(final_df)
     else:
         with ThreadPoolExecutor() as executor:
             futures = {
                 executor.submit(
-                    _scrape_single_site, location, s_name, listing_type
+                    _scrape_single_site, location, s_name, listing_type, proxy
                 ): s_name
                 for s_name in site_name
             }

homeharvest/cli.py

@@ -0,0 +1,72 @@
+import argparse
+import datetime
+from homeharvest import scrape_property
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Home Harvest Property Scraper")
+    parser.add_argument(
+        "location", type=str, help="Location to scrape (e.g., San Francisco, CA)"
+    )
+
+    parser.add_argument(
+        "-s",
+        "--site_name",
+        type=str,
+        nargs="*",
+        default=None,
+        help="Site name(s) to scrape from (e.g., realtor, zillow)",
+    )
+
+    parser.add_argument(
+        "-l",
+        "--listing_type",
+        type=str,
+        default="for_sale",
+        choices=["for_sale", "for_rent", "sold"],
+        help="Listing type to scrape",
+    )
+
+    parser.add_argument(
+        "-o",
+        "--output",
+        type=str,
+        default="excel",
+        choices=["excel", "csv"],
+        help="Output format",
+    )
+
+    parser.add_argument(
+        "-f",
+        "--filename",
+        type=str,
+        default=None,
+        help="Name of the output file (without extension)",
+    )
+
+    parser.add_argument(
+        "-p", "--proxy", type=str, default=None, help="Proxy to use for scraping"
+    )
+
+    args = parser.parse_args()
+
+    result = scrape_property(
+        args.location, args.site_name, args.listing_type, proxy=args.proxy
+    )
+
+    if not args.filename:
+        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+        args.filename = f"HomeHarvest_{timestamp}"
+
+    if args.output == "excel":
+        output_filename = f"{args.filename}.xlsx"
+        result.to_excel(output_filename, index=False)
+        print(f"Excel file saved as {output_filename}")
+    elif args.output == "csv":
+        output_filename = f"{args.filename}.csv"
+        result.to_csv(output_filename, index=False)
+        print(f"CSV file saved as {output_filename}")
+
+
+if __name__ == "__main__":
+    main()

homeharvest/core/scrapers/__init__.py

@@ -8,7 +8,7 @@ class ScraperInput:
     location: str
     listing_type: ListingType
     site_name: SiteName
-    proxy_url: str | None = None
+    proxy: str | None = None
 
 
 class Scraper:
@@ -17,15 +17,16 @@ class Scraper:
         self.listing_type = scraper_input.listing_type
 
         self.session = requests.Session()
+        if scraper_input.proxy:
+            proxy_url = scraper_input.proxy
+            proxies = {
+                "http": proxy_url,
+                "https": proxy_url
+            }
+            self.session.proxies.update(proxies)
         self.listing_type = scraper_input.listing_type
         self.site_name = scraper_input.site_name
 
-        if scraper_input.proxy_url:
-            self.session.proxies = {
-                "http": scraper_input.proxy_url,
-                "https": scraper_input.proxy_url,
-            }
-
     def search(self) -> list[Property]:
         ...
 

homeharvest/core/scrapers/models.py

@@ -102,4 +102,11 @@ class Property:
     bldg_min_area: int | None = None
 
     # apt
+    apt_min_beds: int | None = None
+    apt_max_beds: int | None = None
+    apt_min_baths: float | None = None
+    apt_max_baths: float | None = None
     apt_min_price: int | None = None
+    apt_max_price: int | None = None
+    apt_min_sqft: int | None = None
+    apt_max_sqft: int | None = None

homeharvest/core/scrapers/redfin/__init__.py

@@ -2,7 +2,7 @@ import json
 from typing import Any
 from .. import Scraper
 from ....utils import parse_address_two, parse_unit
-from ..models import Property, Address, PropertyType
+from ..models import Property, Address, PropertyType, ListingType, SiteName
 from ....exceptions import NoResultsFound
 
 
@@ -49,21 +49,21 @@ class RedfinScraper(Scraper):
             unit = parse_unit(get_value("streetLine"))
             address = Address(
                 street_address=street_address,
-                city=home["city"],
-                state=home["state"],
-                zip_code=home["zip"],
+                city=home.get("city"),
+                state=home.get("state"),
+                zip_code=home.get("zip"),
                 unit=unit,
                 country="USA",
             )
         else:
-            address_info = home["streetAddress"]
-            street_address, unit = parse_address_two(address_info["assembledAddress"])
+            address_info = home.get("streetAddress")
+            street_address, unit = parse_address_two(address_info.get("assembledAddress"))
 
             address = Address(
                 street_address=street_address,
-                city=home["city"],
-                state=home["state"],
-                zip_code=home["zip"],
+                city=home.get("city"),
+                state=home.get("state"),
+                zip_code=home.get("zip"),
                 unit=unit,
                 country="USA",
             )
@@ -108,6 +108,64 @@ class RedfinScraper(Scraper):
             else None,
         )
 
+    def _handle_rentals(self, region_id, region_type):
+        url = f"https://www.redfin.com/stingray/api/v1/search/rentals?al=1&isRentals=true&region_id={region_id}&region_type={region_type}&num_homes=100000"
+
+        response = self.session.get(url)
+        response.raise_for_status()
+        homes = response.json()
+
+        properties_list = []
+
+        for home in homes["homes"]:
+            home_data = home["homeData"]
+            rental_data = home["rentalExtension"]
+
+            property_url = f"https://www.redfin.com{home_data.get('url', '')}"
+            address_info = home_data.get("addressInfo", {})
+            centroid = address_info.get("centroid", {}).get("centroid", {})
+            address = Address(
+                street_address=address_info.get("formattedStreetLine", None),
+                city=address_info.get("city", None),
+                state=address_info.get("state", None),
+                zip_code=address_info.get("zip", None),
+                unit=None,
+                country="US" if address_info.get("countryCode", None) == 1 else None,
+            )
+
+            price_range = rental_data.get("rentPriceRange", {"min": None, "max": None})
+            bed_range = rental_data.get("bedRange", {"min": None, "max": None})
+            bath_range = rental_data.get("bathRange", {"min": None, "max": None})
+            sqft_range = rental_data.get("sqftRange", {"min": None, "max": None})
+
+            property_ = Property(
+                property_url=property_url,
+                site_name=SiteName.REDFIN,
+                listing_type=ListingType.FOR_RENT,
+                address=address,
+                apt_min_beds=bed_range.get("min", None),
+                apt_min_baths=bath_range.get("min", None),
+                apt_max_beds=bed_range.get("max", None),
+                apt_max_baths=bath_range.get("max", None),
+                description=rental_data.get("description", None),
+                latitude=centroid.get("latitude", None),
+                longitude=centroid.get("longitude", None),
+                apt_min_price=price_range.get("min", None),
+                apt_max_price=price_range.get("max", None),
+                apt_min_sqft=sqft_range.get("min", None),
+                apt_max_sqft=sqft_range.get("max", None),
+                img_src=home_data.get("staticMapUrl", None),
+                posted_time=rental_data.get("lastUpdated", None),
+                bldg_name=rental_data.get("propertyName", None),
+            )
+
+            properties_list.append(property_)
+
+        if not properties_list:
+            raise NoResultsFound("No rentals found for the given location.")
+
+        return properties_list
+
     def _parse_building(self, building: dict) -> Property:
         street_address = " ".join(
             [
@@ -168,18 +226,19 @@ class RedfinScraper(Scraper):
             home_id = region_id
             return self.handle_address(home_id)
 
-        url = "https://www.redfin.com/stingray/api/gis?al=1&region_id={}&region_type={}".format(
-            region_id, region_type
-        )
-
-        response = self.session.get(url)
-        response_json = json.loads(response.text.replace("{}&&", ""))
-
-        homes = [
-            self._parse_home(home) for home in response_json["payload"]["homes"]
-        ] + [
-            self._parse_building(building)
-            for building in response_json["payload"]["buildings"].values()
-        ]
-
-        return homes
+        if self.listing_type == ListingType.FOR_RENT:
+            return self._handle_rentals(region_id, region_type)
+        else:
+            if self.listing_type == ListingType.FOR_SALE:
+                url = f"https://www.redfin.com/stingray/api/gis?al=1&region_id={region_id}&region_type={region_type}&num_homes=100000"
+            else:
+                url = f"https://www.redfin.com/stingray/api/gis?al=1&region_id={region_id}&region_type={region_type}&sold_within_days=30&num_homes=100000"
+            response = self.session.get(url)
+            response_json = json.loads(response.text.replace("{}&&", ""))
+            homes = [
+                self._parse_home(home) for home in response_json["payload"]["homes"]
+            ] + [
+                self._parse_building(building)
+                for building in response_json["payload"]["buildings"].values()
+            ]
+            return homes

homeharvest/core/scrapers/zillow/__init__.py

@@ -1,6 +1,5 @@
 import re
 import json
-import string
 from .. import Scraper
 from ....utils import parse_address_two, parse_unit
 from ....exceptions import GeoCoordsNotFound, NoResultsFound
@@ -10,9 +9,10 @@ from ..models import Property, Address, ListingType, PropertyType
 class ZillowScraper(Scraper):
     def __init__(self, scraper_input):
         super().__init__(scraper_input)
-        self.listing_type = scraper_input.listing_type
+
         if not self.is_plausible_location(self.location):
             raise NoResultsFound("Invalid location input: {}".format(self.location))
+
         if self.listing_type == ListingType.FOR_SALE:
             self.url = f"https://www.zillow.com/homes/for_sale/{self.location}_rb/"
         elif self.listing_type == ListingType.FOR_RENT:
@@ -20,20 +20,20 @@ class ZillowScraper(Scraper):
         else:
             self.url = f"https://www.zillow.com/homes/recently_sold/{self.location}_rb/"
 
-    @staticmethod
-    def is_plausible_location(location: str) -> bool:
-        blocks = location.split()
-        for block in blocks:
-            if (
-                any(char.isdigit() for char in block)
-                and any(char.isalpha() for char in block)
-                and len(block) > 6
-            ):
-                return False
-        return True
+    def is_plausible_location(self, location: str) -> bool:
+        url = (
+            "https://www.zillowstatic.com/autocomplete/v3/suggestions?q={"
+            "}&abKey=6666272a-4b99-474c-b857-110ec438732b&clientId=homepage-render"
+        ).format(location)
+
+        response = self.session.get(url)
+
+        return response.json()["results"] != []
 
     def search(self):
-        resp = self.session.get(self.url, headers=self._get_headers())
+        resp = self.session.get(
+            self.url, headers=self._get_headers()
+        )
         resp.raise_for_status()
         content = resp.text
 
@@ -130,7 +130,9 @@ class ZillowScraper(Scraper):
             "wants": {"cat1": ["mapResults"]},
             "isDebugRequest": False,
         }
-        resp = self.session.put(url, headers=self._get_headers(), json=payload)
+        resp = self.session.put(
+            url, headers=self._get_headers(), json=payload
+        )
         resp.raise_for_status()
         a = resp.json()
         return self._parse_properties(resp.json())
@@ -189,7 +191,9 @@ class ZillowScraper(Scraper):
                     else None,
                     "img_src": result.get("imgSrc"),
                     "price_per_sqft": int(home_info["price"] // home_info["livingArea"])
-                    if "livingArea" in home_info and "price" in home_info
+                    if "livingArea" in home_info
+                    and home_info["livingArea"] != 0
+                    and "price" in home_info
                     else None,
                 }
                 property_obj = Property(**property_data)

poetry.lock

@@ -106,6 +106,17 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "et-xmlfile"
+version = "1.1.0"
+description = "An implementation of lxml.xmlfile for the standard library"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "et_xmlfile-1.1.0-py3-none-any.whl", hash = "sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada"},
+    {file = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.1.3"
@@ -217,6 +228,20 @@ files = [
     {file = "numpy-1.26.0.tar.gz", hash = "sha256:f93fc78fe8bf15afe2b8d6b6499f1c73953169fad1e9a8dd086cdff3190e7fdf"},
 ]
 
+[[package]]
+name = "openpyxl"
+version = "3.1.2"
+description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "openpyxl-3.1.2-py2.py3-none-any.whl", hash = "sha256:f91456ead12ab3c6c2e9491cf33ba6d08357d802192379bb482f1033ade496f5"},
+    {file = "openpyxl-3.1.2.tar.gz", hash = "sha256:a6f5977418eff3b2d5500d54d9db50c8277a368436f4e4f8ddb1be3422870184"},
+]
+
+[package.dependencies]
+et-xmlfile = "*"
+
 [[package]]
 name = "packaging"
 version = "23.1"
@@ -425,4 +450,4 @@ zstd = ["zstandard (>=0.18.0)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "eede625d6d45085e143b0af246cb2ce00cff8579c667be3b63387c8594a5570d"
+content-hash = "3647d568f5623dd762f19029230626a62e68309fa2ef8be49a36382c19264a5f"

pyproject.toml

@@ -1,15 +1,19 @@
 [tool.poetry]
 name = "homeharvest"
-version = "0.2.1"
+version = "0.2.6"
 description = "Real estate scraping library supporting Zillow, Realtor.com & Redfin."
 authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
 homepage = "https://github.com/ZacharyHampton/HomeHarvest"
 readme = "README.md"
 
+[tool.poetry.scripts]
+homeharvest = "homeharvest.cli:main"
+
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
 pandas = "^2.1.0"
+openpyxl = "^3.1.2"
 
 
 [tool.poetry.group.dev.dependencies]