pull/10/head
Cullen Watson 2023-09-19 15:01:39 -05:00
parent 05fca9b7e6
commit 49d27943c4
5 changed files with 91 additions and 6 deletions

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@ -22,6 +22,22 @@ pip install --force-reinstall homeharvest
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
## Usage
### CLI
```bash
homeharvest "San Francisco, CA" --site_name zillow realtor.com redfin --listing_type for_rent --output excel --filename 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 `--site_name` is not provided, it will scrape from all available sites.
- If `--listing_type` is left blank, the default is `for_sale`, other options are `for_rent` or `sold`.
- The `--output` default format is `excel`, options are `csv` or `excel`.
- If `--filename` is left blank, the default is `HomeHarvest_<current_timestamp>`
### Python
```py
from homeharvest import scrape_property
import pandas as pd
@ -105,7 +121,14 @@ 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

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@ -68,10 +68,10 @@ def get_ordered_properties(result: Property) -> list[str]:
"year_built",
"agent_name",
"mls_id",
"description",
"img_src",
"latitude",
"longitude",
"description",
]

57
homeharvest/cli.py Normal file
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@ -0,0 +1,57 @@
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(
"--site_name",
type=str,
nargs="*",
default=None,
help="Site name(s) to scrape from (e.g., realtor.com zillow)",
)
parser.add_argument(
"--listing_type",
type=str,
default="for_sale",
choices=["for_sale", "for_rent", "sold"],
help="Listing type to scrape",
)
parser.add_argument(
"--output",
type=str,
default="excel",
choices=["excel", "csv"],
help="Output format",
)
parser.add_argument(
"--filename",
type=str,
default=None,
help="Name of the output file (without extension)",
)
args = parser.parse_args()
result = scrape_property(args.location, args.site_name, args.listing_type)
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()

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@ -188,7 +188,9 @@ 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)

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@ -1,11 +1,14 @@
[tool.poetry]
name = "homeharvest"
version = "0.2.2"
version = "0.2.3"
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"