Business Directory Contact Extractor

You are an expert Python developer specializing in ethical web scraping and data engineering.

Write a complete, production-ready web scraper that collects publicly listed business contact information from a specified directory site and outputs a structured lead sheet. The scraper must:

**Input**
- Target URL: {{directory-url}}
- Output format: {{output-format}}

**Data to Extract**
For each business listing, collect:
- Business name
- Category / industry
- Physical address
- Phone number
- Email address (only if publicly displayed on the listing page)
- Website URL

**Compliance Requirements**
The script MUST:
1. Check and respect the site's robots.txt before scraping
2. Skip any content behind authentication / login walls
3. Only collect publicly published business contact details (no personal data, no scraping of employee profiles or internal pages)
4. Include reasonable rate limiting (minimum 1-second delay between requests)
5. Set a descriptive User-Agent header identifying the scraper
6. Handle HTTP errors gracefully and log skipped pages

**Output**
1. A single Python script using `requests`, `beautifulsoup4`, and `pandas` (or specify if another stack is required)
2. Implement deduplication logic keyed on (business_name + address) to remove duplicate entries
3. Export the final dataset to the specified format with columns: business_name, category, address, phone, email, website, scraped_date
4. Include a CLI interface that accepts the target URL as an argument

**Legal Notice to Include**
Add a prominent comment block at the top of the script stating:
```
# OPERATOR'S LEGAL OBLIGATIONS:
# - Verify this scraping complies with the target site's Terms of Service
# - Ensure compliance with applicable data protection laws (GDPR, CCPA, etc.)
# - Obtain necessary consents before using collected data for marketing
# - Maintain records of data sources and processing purposes
# - Provide opt-out mechanisms if using data for outreach
# The operator assumes full legal responsibility for use of this script.
```

**Code Quality**
- Include error handling for network failures, missing elements, and malformed data
- Log progress and any skipped listings with reasons
- Make the scraping logic modular (separate functions for fetching, parsing, deduplication)
- Add inline comments explaining the extraction logic
- Include a requirements.txt listing all dependencies

Provide the complete script, ready to run.