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# Troostwijk Auctions Scraper
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A robust web scraper for extracting auction lot data from Troostwijk Auctions, featuring intelligent caching, rate limiting, and Cloudflare bypass capabilities.
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## Features - 1
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- **Playwright-based scraping** - Bypasses Cloudflare protection
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- **SQLite caching** - Caches every page to avoid redundant requests
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- **Rate limiting** - Strictly enforces 0.5 seconds between requests
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- **Multi-format output** - Exports data in both JSON and CSV formats
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- **Progress saving** - Automatically saves progress every 10 lots
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- **Test mode** - Debug extraction patterns on cached pages
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## Requirements
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- Python 3.8+
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- Playwright (with Chromium browser)
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## Installation
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1. **Clone or download this project**
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2. **Install dependencies:**
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```bash
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pip install -r requirements.txt
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```
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3. **Install Playwright browsers:**
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```bash
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playwright install chromium
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```
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## Configuration
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Edit the configuration variables in `main.py`:
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```python
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BASE_URL = "https://www.troostwijkauctions.com"
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CACHE_DB = "/mnt/okcomputer/output/cache.db" # Path to cache database
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OUTPUT_DIR = "/mnt/okcomputer/output" # Output directory
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RATE_LIMIT_SECONDS = 0.5 # Delay between requests
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MAX_PAGES = 50 # Number of listing pages to crawl
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```
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**Note:** Update the paths to match your system (especially on Windows, use paths like `C:\\output\\cache.db`).
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## Usage
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### Basic Scraping
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Run the scraper to collect auction lot data:
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```bash
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python main.py
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```
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This will:
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1. Crawl listing pages to collect lot URLs
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2. Scrape each individual lot page
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3. Save results in both JSON and CSV formats
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4. Cache all pages to avoid re-fetching
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### Test Mode
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Test extraction patterns on a specific cached URL:
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```bash
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# Test with default URL
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python main.py --test
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# Test with specific URL
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python main.py --test "https://www.troostwijkauctions.com/a/lot-url-here"
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```
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This is useful for debugging extraction patterns and verifying data is being extracted correctly.
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## Output Files
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The scraper generates the following files:
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### During Execution
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- `troostwijk_lots_partial_YYYYMMDD_HHMMSS.json` - Progress checkpoints (every 10 lots)
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### Final Output
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- `troostwijk_lots_final_YYYYMMDD_HHMMSS.json` - Complete data in JSON format
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- `troostwijk_lots_final_YYYYMMDD_HHMMSS.csv` - Complete data in CSV format
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### Cache
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- `cache.db` - SQLite database with cached page content (persistent across runs)
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## Data Extracted
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For each auction lot, the scraper extracts:
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- **URL** - Direct link to the lot
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- **Lot ID** - Unique identifier (e.g., A7-35847)
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- **Title** - Lot title/description
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- **Current Bid** - Current bid amount
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- **Bid Count** - Number of bids placed
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- **End Date** - Auction end time
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- **Location** - Physical location of the item
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- **Description** - Detailed description
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- **Category** - Auction category
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- **Images** - Up to 5 product images
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- **Scraped At** - Timestamp of data collection
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## How It Works
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### Phase 1: Collect Lot URLs
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The scraper iterates through auction listing pages (`/auctions?page=N`) and collects all lot URLs.
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### Phase 2: Scrape Individual Lots
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Each lot page is visited and data is extracted from the embedded JSON data (`__NEXT_DATA__`). The site is built with Next.js and includes all auction/lot data in a JSON structure, making extraction reliable and fast.
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### Caching Strategy
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- Every successfully fetched page is cached in SQLite
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- Cache is checked before making any request
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- Cache entries older than 7 days are automatically cleaned
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- Failed requests (500 errors) are also cached to avoid retrying
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### Rate Limiting
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- Enforces exactly 0.5 seconds between ALL requests
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- Applies to both listing pages and individual lot pages
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- Prevents server overload and potential IP blocking
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## Troubleshooting
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### Issue: "Huidig bod" / "Locatie" instead of actual values
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**✓ FIXED!** The site uses Next.js with all data embedded in `__NEXT_DATA__` JSON. The scraper now automatically extracts data from JSON first, falling back to HTML pattern matching only if needed.
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The scraper correctly extracts:
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- **Title** from `auction.name`
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- **Location** from `viewingDays` or `collectionDays`
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- **Images** from `auction.image.url`
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- **End date** from `minEndDate`
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- **Lot ID** from `auction.displayId`
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To verify extraction is working:
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```bash
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python main.py --test "https://www.troostwijkauctions.com/a/your-auction-url"
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```
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**Note:** Some URLs point to auction pages (collections of lots) rather than individual lots. Individual lots within auctions may have bid information, while auction pages show the collection details.
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### Issue: No lots found
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- Check if the website structure has changed
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- Verify `BASE_URL` is correct
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- Try clearing the cache database
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### Issue: Cloudflare blocking
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- Playwright should bypass this automatically
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- If issues persist, try adjusting user agent or headers in `crawl_auctions()`
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### Issue: Slow scraping
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- This is intentional due to rate limiting (0.5s between requests)
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- Adjust `RATE_LIMIT_SECONDS` if needed (not recommended below 0.5s)
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- First run will be slower; subsequent runs use cache
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## Project Structure
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```
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troost-scraper/
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├── main.py # Main scraper script
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├── requirements.txt # Python dependencies
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├── README.md # This file
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└── output/ # Generated output files (created automatically)
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├── cache.db # SQLite cache
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├── *.json # JSON output files
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└── *.csv # CSV output files
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```
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## Development
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### Adding New Extraction Fields
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1. Add extraction method in `TroostwijkScraper` class:
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```python
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def _extract_new_field(self, content: str) -> str:
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pattern = r'your-regex-pattern'
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match = re.search(pattern, content)
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return match.group(1) if match else ""
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```
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2. Add field to `_parse_lot_page()`:
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```python
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data = {
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# ... existing fields ...
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'new_field': self._extract_new_field(content),
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}
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```
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3. Add field to CSV export in `save_final_results()`:
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```python
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fieldnames = ['url', 'lot_id', ..., 'new_field', ...]
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```
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### Testing Extraction Patterns
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Use test mode to verify patterns work correctly:
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```bash
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python main.py --test "https://www.troostwijkauctions.com/a/your-test-url"
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```
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## License
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This scraper is for educational and research purposes. Please respect Troostwijk Auctions' terms of service and robots.txt when using this tool.
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## Notes
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- **Be respectful:** The rate limiting is intentionally conservative
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- **Check legality:** Ensure web scraping is permitted in your jurisdiction
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- **Monitor changes:** Website structure may change over time, requiring pattern updates
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- **Cache management:** Old cache entries are auto-cleaned after 7 days
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