We extract commercial truck listings, dealer inventory, auction results, and technical specifications from Truck Paper. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Truck Listings objects from truckpaper.com. All fields typed and schema-versioned.
"listing_id": "24981357", "title": "2024 FREIGHTLINER CASCADIA 126", "manufacturer": "Freightliner", "year": 2024, "price": 145000.0, "currency": "USD", "mileage": "450,210 mi", "engine_make": "Detroit", "horsepower": 400, "location": "Omaha, Nebraska"
| # | listing_id | title | category | manufacturer | model | year |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Auction Results objects from truckpaper.com. All fields typed and schema-versioned.
"auction_id": "98214", "lot_number": "412A", "machine_title": "2019 PETERBILT 389", "auctioneer": "AuctionTime", "auction_date": "2026-03-14", "final_bid": 89500.0, "currency": "USD", "condition": "Used", "hours_used": "12,400"
| # | auction_id | lot_number | machine_title | auctioneer | auction_date | location |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Dealer Profiles objects from truckpaper.com. All fields typed and schema-versioned.
"dealer_id": "D-8421", "dealer_name": "Midwest Truck Sales", "location_city": "Des Moines", "location_state": "IA", "active_inventory_count": 142, "brands_carried": "['Kenworth', 'Peterbilt']", "dealer_type": "Independent", "rating": 4.7
| # | dealer_id | dealer_name | location_city | location_state | phone_number | website_url |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Technical Specifications objects from truckpaper.com. All fields typed and schema-versioned.
"vin": "1FUJGLCZ6MLXXXXXX", "engine_model": "DD15", "displacement": "14.8L", "fuel_type": "Diesel", "rear_axle_weight": "40,000 lb", "wheelbase": "240 in", "cab_type": "Sleeper", "sleeper_size": "72 in"
| # | listing_id | vin | engine_model | displacement | fuel_type | rear_axle_weight |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Market Pricing objects from truckpaper.com. All fields typed and schema-versioned.
"listing_id": "24981357", "current_price": 145000.0, "original_price": 149000.0, "days_on_market": 42, "price_drops": 1, "financing_available": true, "scrape_timestamp": "2026-05-12T09:14:00Z"
| # | listing_id | current_price | original_price | days_on_market | price_drops | shipping_cost |
|---|---|---|---|---|---|---|
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Our Truck Paper scraper parses complex vehicle specifications, normalises dealer inventory data, and extracts historical auction pricing while bypassing strict bot protection mechanisms.
Extract engine make, horsepower, transmission type, suspension, axle weights, and wheelbase dimensions for every listing.
Capture dealer asking prices, price drops, and historical auction final bids from AuctionTime integrations.
Aggregate active stock across specific dealer profiles to monitor competitor inventory levels and brand focus.
Extract visible VINs and serial numbers to cross-reference equipment history and validate manufacturing years.
Capture high-resolution image URLs, inspection reports, and video links associated with specific equipment lots.
Standardise dealer locations, equipment staging areas, and auction sites into structured city and state fields.
Navigate complex sub-categories from Heavy Duty Sleeper Trucks to Flatbed Trailers and Vocational Equipment.
Evade Sandhills Global bot protection using residential proxies and TLS fingerprint spoofing.
Identify new listings, sold inventory, and price modifications without re-downloading the entire static catalogue.
Brief in. Clean data out.
Provide categories, dealer IDs, or search parameters. We map the required fields and configure the extraction schema.
We deploy Scrapy and Playwright clusters, configure proxy rotation, and implement Cloudflare bypass strategies.
We test the pipeline for null rates, validate field data types, and ensure complete pagination coverage.
Data is exported as JSON, CSV, or Parquet and pushed to your target warehouse or S3 bucket on a defined schedule.
Truck Paper relies on heavy bot mitigation and complex categorical structures. We handle the infrastructure so you receive clean data.
Truck Paper employs aggressive Cloudflare protection to block automated traffic. We use residential proxies and Playwright to generate valid TLS fingerprints and solve JavaScript challenges automatically.
Dealers input specifications inconsistently. We apply post-processing rules to normalise horsepower, mileage, hours used, and engine makes into clean, queryable formats.
Broad category searches often cap results at 1,000 listings. We programmatically segment searches by year, location, and manufacturer to extract the complete catalogue without hitting truncation limits.
Crucial data points like dealer phone numbers and detailed inspection reports are loaded asynchronously. Our Playwright integration ensures all dynamic content is fully rendered before extraction.
A day cab truck has different specifications than a reefer trailer. Our schema adapts dynamically based on the equipment category, ensuring relevant fields are captured without schema breakage.
Finance and leasing companies use historical and active pricing data to calculate residual values for commercial assets.
Dealerships ingest pricing data to optimise their own asking prices based on regional supply and demand.
OEMs monitor dealer inventory levels to track competitor market share and identify regional sales trends.
Underwriters use specification data and market values to assess risk and price insurance premiums for commercial fleets.
Buyers compare historical auction results against retail asking prices to identify undervalued equipment lots.
Logistics companies track the availability of specific truck models to forecast capacity and procurement costs.
"Commercial equipment pricing is highly fragmented. Truck Paper holds the most comprehensive inventory data, but requires sophisticated pipelines to extract it reliably."
Building a reliable scraper for Truck Paper requires bypassing enterprise-grade bot protection, handling complex JavaScript rendering, and standardising highly variable dealer inputs. DataFlirt manages these infrastructure challenges entirely. We deliver clean, normalised fleet data directly to your warehouse so your analysts can focus on market modeling.
Everything supported by our truckpaper.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy manages request concurrency and routing, while Playwright handles JavaScript execution for complex dealer pages.
We route requests through ISP-grade residential proxies to mimic legitimate user traffic and prevent IP bans.
Apache Airflow schedules daily extraction runs, monitors job health, and triggers alerts for schema anomalies.
Data delivered to where your team already works — no new tooling required.
About truckpaper.com scraping, legality, and pipeline operations.
Ask us directly →Yes. We can configure pipelines to target specific states, cities, or postal codes to build regional inventory datasets.
Our schema accepts null values for optional fields while enforcing strict types for core data points like price and year. We flag listings with missing critical data.
Yes. We maintain historical records for every listing ID. Subsequent runs log price drops, days on market, and final removal dates.
Our infrastructure is compatible with Machinery Trader, TractorHouse, and other Sandhills properties. We can build unified pipelines across these domains.
We support daily, weekly, or custom intervals. High-frequency updates are possible for specific sub-categories or targeted dealer lists.
We extract the direct URLs for all images in a listing gallery. We can also configure the pipeline to download and store the image files in your S3 bucket.
20-minute scoping call. Pilot dataset within the week. Production within two. From specific dealer monitoring to full category extraction, we build and manage the entire infrastructure. Contact us to define your schema.
