[docs] reorder
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README.md
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README.md
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@ -17,8 +17,9 @@ Check out another project we wrote: ***[JobSpy](https://github.com/cullenwatson/
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- **Data Format**: Structures data to resemble MLS listings.
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- **Data Format**: Structures data to resemble MLS listings.
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- **Export Flexibility**: Options to save as either CSV or Excel.
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- **Export Flexibility**: Options to save as either CSV or Excel.
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- **Usage Modes**:
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- **Usage Modes**:
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- **CLI**: For users who prefer command-line operations.
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- **Python**: For those who'd like to integrate scraping into their Python scripts.
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- **Python**: For those who'd like to integrate scraping into their Python scripts.
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- **CLI**: For users who prefer command-line operations.
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[Video Guide for HomeHarvest](https://youtu.be/JnV7eR2Ve2o) - _updated for release v0.2.7_
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[Video Guide for HomeHarvest](https://youtu.be/JnV7eR2Ve2o) - _updated for release v0.2.7_
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@ -33,6 +34,30 @@ pip install homeharvest
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## Usage
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## Usage
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### Python
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```py
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from homeharvest import scrape_property
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from datetime import datetime
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# Generate filename based on current timestamp
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current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"HomeHarvest_{current_timestamp}.csv"
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properties = scrape_property(
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location="San Diego, CA",
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listing_type="sold", # or (for_sale, for_rent)
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property_younger_than=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
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# pending_or_contingent=True # use on for_sale listings to find pending / contingent listings
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# mls_only=True, # only fetch MLS listings
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)
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print(f"Number of properties: {len(properties)}")
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# Export to csv
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properties.to_csv(filename, index=False)
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print(properties.head())
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```
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### CLI
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### CLI
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```
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```
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@ -61,29 +86,6 @@ options:
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> homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
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> homeharvest "San Francisco, CA" -l for_rent -o excel -f HomeHarvest
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```
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```
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### Python
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```py
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from homeharvest import scrape_property
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from datetime import datetime
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# Generate filename based on current timestamp
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current_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"HomeHarvest_{current_timestamp}.csv"
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properties = scrape_property(
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location="San Diego, CA",
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listing_type="sold", # or (for_sale, for_rent)
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property_younger_than=30, # sold in last 30 days - listed in last x days if (for_sale, for_rent)
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# pending_or_contingent=True # use on for_sale listings to find pending / contingent listings
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# mls_only=True, # only fetch MLS listings
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)
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print(f"Number of properties: {len(properties)}")
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# Export to csv
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properties.to_csv(filename, index=False)
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print(properties.head())
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```
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## Output
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## Output
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```plaintext
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```plaintext
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