Auto-Data.net Scraper

Auto-Data.net Scraper reads car technical specifications from auto-data.net and returns one clean row per engine variant. Type a brand such as Audi, or a list of models such as Audi RS3 and Audi TT, and get power, torque, 0-100 km/h, top speed, weight, dimensions, fuel economy, gearbox, brakes and tyres for every generation. Each row also carries the complete spec sheet exactly as auto-data.net publishes it. Export to JSON, CSV or Excel, with no API key and no HTML parsing on your side.

What is Auto-Data.net Scraper?

Auto-Data.net Scraper turns a brand or a model name into the full list of its engine variants on auto-data.net, opens each variant page and saves a structured record in an Apify dataset. The only source it reads is auto-data.net.

Auto-Data.net Scraper supports the following:

• Scrape a whole brand: one entry like Audi expands to every model, generation and engine variant.
• Scrape a model list: Audi TT expands to all TT generations and engine variants. Mix several models in one run.
• One row per variant: power, torque, acceleration, top speed, dimensions, weight, fuel economy, transmission and chassis, normalized to metric units.
• Full spec sheet on every row: the rawSpecs array keeps every label and value of the variant page, in page order, so nothing the site publishes is lost to the flat columns.
• Electric and hybrid variants: system power and torque, gross battery capacity and all-electric range, filled only where auto-data.net publishes them.

What data can I extract with Auto-Data.net Scraper?

Group	Example fields
Performance	0-100 km/h, 0-60 mph, top speed, power-to-weight
Engine	power (hp and kW), torque, displacement, cylinders, valves, compression, fuel type
Transmission	drive wheels, gearbox type, number of gears
Dimensions	length, width, height, wheelbase, kerb weight, drag coefficient
Electric and hybrid	system power and torque, gross battery capacity, all-electric range
Fuel economy	combined consumption, CO2 and its test standard, fuel tank
Chassis	front and rear brakes, suspension, steering

How can I use data scraped from a car reference site?

Build pricing and residual-value models, power a vehicle comparison or a configurator, feed a performance database or an enthusiast site, enrich a dealer or marketplace catalog, or run engineering and market research across a whole brand history. Because the output is one tidy row per variant, it drops straight into a spreadsheet, a database or a BI tool.

How to use Auto-Data.net Scraper

Here's how to use Auto-Data.net Scraper in 5 steps:

1. Create a free Apify account using your email.
2. Open Auto-Data.net Scraper.
3. Pick the Input mode (Brand or Model names list), then choose a brand (for example Audi) or list models (for example Audi RS3). Optionally set a year range or a max items cap.
4. Click the Start button and wait for the data to be extracted.
5. Download your data in JSON, XML, CSV, Excel or HTML.

How much will scraping car data cost you?

Auto-Data.net Scraper uses a pay-per-event pricing model.

• Car specs: from $0.003 to $0.005 per variant depending on your Apify subscription tier, which is $3 to $5 per 1,000 variants. One event is charged for each engine-variant record saved to the dataset, with its full spec sheet.
• Actor Start: the standard Apify event, charged once for every run.
• Error rows are never charged. A row carrying _error: true is returned for visibility and does not trigger the Car specs event.

See the Pricing tab for the current prices.

You can cap the spend of any single run from the Apify Console with ACTOR_MAX_TOTAL_CHARGE_USD, and the maxItems input gives you a hard limit on how many variants are emitted.

⬇️ Input

The input is a JSON object that says which brand or models to scrape, plus optional filters. See the Input tab for the full schema with all fields and defaults.

Auto-Data.net Scraper input examples

Scrape a list of specific models (set inputMode to models):

{
  "inputMode": "models",
  "models": ["Audi RS3", "Audi TT"],
  "yearMin": 2015,
  "maxItems": 200
}

Scrape a whole brand (set inputMode to brand):

{
  "inputMode": "brand",
  "brand": "Audi",
  "maxItems": 500
}

Only the field matching inputMode is used, the other is ignored. Always set inputMode to match how you are targeting cars.

• models entries are always written as Brand Model, for example Audi RS3. A model typed without its brand is ignored.
• yearMin and yearMax (inclusive) filter variants after the generation pages are read, so they narrow the output but do not make a run shorter.
• excludeModels matches exact model names, case-insensitively. Enter either the model (TT) or make and model (Audi TT). Excluding TT does not exclude TTS.
• maxItems defaults to 1000. Through the API you can set it to 0 to remove the record cap, but only on a run that has a timeout, otherwise the input is rejected.

Options that belonged to the multi-source Car Data Scraper (sources, extraSources, sourcePriority, conflictThresholdPct) are still accepted by the API so existing integrations do not break. They are ignored, and the run log carries one warning per key.

Calling the Actor from the API

Use apify-client for Node.js or Python to start a run and read the dataset. Python example:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("mrbridge/auto-data-scraper").call(
    run_input={"inputMode": "models", "models": ["Audi RS3"], "maxItems": 50}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["modification"], item["powerHp"], item["zeroToHundredS"])

⬆️ Output

Auto-Data.net Scraper stores results in a dataset, one record per engine variant. Each row carries flat summary columns for browsing, filtering and spreadsheet export, a set of nested sections that keep the unit of each value, and the complete spec sheet in rawSpecs.

Rows are written as each model completes, not in one block at the end, so a long brand run fills its dataset progressively and a run you stop early keeps everything already produced.

A run that reaches its time budget stops on its own, shortly before the platform timeout, and finishes as a normal successful run with a partial dataset. An OUTPUT record in the key-value store says how the run ended, how many records it delivered and which model was the last one fully completed. It is the thing to share when reporting a problem.

Dataset views

The Output tab offers five views.

View	What it shows
overview	Make, model, generation, modification, years, fuel type, engine size, power, torque, 0-100 km/h, top speed, url
performance	Power and its basis, 0-100 km/h, 0-60 mph and how it was obtained, top speed, power-to-weight, electric range
detailed	All the flat columns listed below except zeroToSixtyMphS, zeroToSixtyMphMethod and powerToWeightHpPerT, which are in performance
fullSpecSheet	Identification columns, url and the rawSpecs array
errors	Error rows only: error, errorMessage, source, url, scrapedAt

Flat columns

• Identity: make, model, generation, modification, yearStart, yearEnd, bodyType, doors, seats, canonicalVariantId, url, autodataId, scrapedAt.
• Engine: fuelType, engineCc, powerHp, powerKw, torqueNm, powerBasis, torqueBasis, cylinders, valves, compression.
• Electric and hybrid: batteryCapacityKwh, electricRangeKm.
• Performance: zeroToHundredS, topSpeedKmh, zeroToSixtyMphS, zeroToSixtyMphMethod, powerToWeightHpPerT.
• Drivetrain: transmission, gears, driveType.
• Dimensions and weight: lengthMm, widthMm, heightMm, wheelbaseMm, curbWeightKg.
• Fuel economy: fuelConsumptionL100, co2GKm, co2Standard.

Values auto-data.net does not publish for a variant are null. Nothing is estimated or read out of the variant name.

On an electric, plug-in hybrid or full hybrid, auto-data.net prints the total output under System power and System torque, separately from the Power row of the combustion engine. powerHp and torqueNm carry the system figure whenever the page prints one. powerBasis and torqueBasis tell you which row was used on every row, and the nested engine section keeps both as published.

Nested sections

performance, engine, transmissionDetail, dimensions, fuelEconomy and chassis hold one entry per field, each with its value, a canonical unit where it applies and source, which is always autodata.

The rawSpecs array

rawSpecs is the full spec sheet of the variant page: an array of { "label": ..., "value": ... } entries in page order, with repeated labels kept. Entries with no value are omitted, and so are the entries auto-data.net replaces with Log in to see. for visitors who are not signed in. Error rows have no rawSpecs.

Because rawSpecs is an array, a CSV export flattens it into numbered columns (rawSpecs/0/label, rawSpecs/0/value, and so on), which makes a wide and hard-to-read file. Prefer JSON when you need the full spec sheet. For CSV or Excel, use the flat columns or the overview, performance and detailed views.

Sample output

A real row from an Audi RS3 run, shortened for this page: the nested sections engine, transmissionDetail, dimensions, fuelEconomy and chassis are left out, and rawSpecs shows its first 4 entries out of 68.

{
  "make": "Audi",
  "model": "RS3",
  "generation": "RS3 Sportback (8Y, facelift 2024)",
  "modification": "2.5 TFSI (400 Hp) quattro S tronic",
  "yearStart": 2024,
  "yearEnd": null,
  "bodyType": "Hatchback",
  "doors": 5,
  "seats": 5,
  "canonicalVariantId": "audi-rs3-hatchback-2.5l-400hp-2024",
  "url": "https://www.auto-data.net/en/audi-rs3-sportback-8y-facelift-2024-2.5-tfsi-400hp-quattro-s-tronic-52529",
  "autodataId": "52529",
  "fuelType": "Petrol (Gasoline)",
  "engineCc": 2480,
  "powerHp": 400,
  "powerKw": null,
  "torqueNm": 500,
  "powerBasis": "engine",
  "torqueBasis": "engine",
  "batteryCapacityKwh": null,
  "electricRangeKm": null,
  "cylinders": 5,
  "valves": 4,
  "compression": "10:1",
  "zeroToHundredS": 3.8,
  "topSpeedKmh": 250,
  "zeroToSixtyMphS": 3.6,
  "zeroToSixtyMphMethod": "calculated",
  "powerToWeightHpPerT": 255.6,
  "transmission": "automatic transmission S tronic",
  "gears": 7,
  "driveType": "All wheel drive (4x4)",
  "lengthMm": 4381,
  "widthMm": 1851,
  "heightMm": 1430,
  "wheelbaseMm": 2631,
  "curbWeightKg": 1565,
  "fuelConsumptionL100": 9.3,
  "co2GKm": 211,
  "co2Standard": "WLTP",
  "scrapedAt": "2026-10-19T20:55:57.576Z",
  "performance": {
    "accel_0_100_kmh": { "value": 3.8, "unit": "s", "source": "autodata" },
    "accel_0_60_mph": { "value": 3.6, "unit": "s", "source": "autodata", "measurementKind": "calculated" },
    "top_speed_kmh": { "value": 250, "unit": "km/h", "source": "autodata" },
    "power_to_weight_hp_per_t": { "value": 255.6, "unit": "hp/t", "source": "autodata" }
  },
  "rawSpecs": [
    { "label": "Brand", "value": "Audi" },
    { "label": "Model", "value": "RS3" },
    { "label": "Generation", "value": "RS3 Sportback (8Y, facelift 2024)" },
    { "label": "Modification (Engine)", "value": "2.5 TFSI (400 Hp) quattro S tronic" }
  ]
}

Differences from Car Data Scraper

Auto-Data.net Scraper keeps the same name, type and value for every column it shares with Car Data Scraper, so a pipeline built on the multi-source Actor reads these rows without change. The differences:

• Removed (they only exist when several sources are merged): sources, conflicts, dedupeConfidence, sourcesDetail, flags, quarterMileS, peakG. The alternatives entries of the nested fields are gone for the same reason.
• Added: url (the auto-data.net page of the variant), autodataId (its identifier, as text) and rawSpecs (the full spec sheet).

For programmatic access in Python, Node.js or PHP, see the Apify API reference.

Known limitations

• One source. Every figure is reported as auto-data.net publishes it. Values are normalized to metric units, but regional and market differences are not reconciled.
• No market or region field. auto-data.net describes each variant by generation and chassis code (for example 8V or 8Y), not by sales market.
• Coverage depends on the site. A model or generation page that cannot be read comes back as an error row (not charged), and the rest of the run carries on.
• Run time follows the number of variants. A whole-brand pull can walk hundreds of variants and take several minutes. Use Max items to bound a run.
• Use autodataId as the row key. autodataId and url are unique per variant. canonicalVariantId groups variants that share make, model, body, engine size, power and start year, so variants that differ only by gearbox, drive or fuel share one id. Use it to group rows, not to deduplicate them.
• Ranges keep their lower figure. When auto-data.net prints a range, such as "9-9.5 l/100 km" or "520-534 km", fuelConsumptionL100, co2GKm and electricRangeKm hold the first figure, the lower one. The full range stays in rawSpecs.
• powerKw is always empty. auto-data.net prints power in horsepower, the Actor reads no kilowatt row and never converts powerHp, so the column stays empty. Use powerHp.
• Battery capacity is the gross figure. batteryCapacityKwh reads the gross capacity. A page that prints only the net (usable) capacity, as some Tesla pages do, leaves it empty, and the net figure stays in rawSpecs.
• An empty zeroToSixtyMphMethod means the page carries no calculation note. The column says calculated when auto-data.net marks the 0-60 mph time as computed by the site, and stays empty otherwise.
• Electric consumption is in rawSpecs only. Electric cars have no fuel consumption or CO2 figure, and their energy consumption in kWh/100 km is not a flat column. Read it from rawSpecs.
• Old cars have sparse pages. Pages of cars from the 1970s, such as the Alpine 1300 and 1600, carry about a dozen figures, so many columns stay empty. These rows are billed like any other.
• Production years are copied as printed. auto-data.net can contradict itself, for example an end of production before its start on the Audi 100 C3 2.3 E Automatic. The Actor does not correct it.
• Pages are cached in your account for 30 days. Variant pages already read are kept in a key-value store named auto-data-html-cache in your Apify account, so a later run on the same models does not fetch them again. A cached page can be up to 30 days old. The store outlives the run and counts towards your storage usage. You can delete it at any time from Storage, and the next run starts a new one. The scrapedAt column is the time the row was emitted, so a row built from a cached page can rest on a page up to 30 days old. The cache saves requests to auto-data.net and not run time, because the list pages (brand, model, generation) are read again on every run. In a measured rerun of Audi RS3 with its 8 variant pages already cached, the run was not faster than the first one.

Frequently asked questions

How does Auto-Data.net Scraper work?

It resolves each requested brand or model into its list of generations and engine variants on auto-data.net, reads each variant page, normalizes the values to metric units and saves one row per variant. Variant pages already read are kept for 30 days in the auto-data-html-cache store of your account, so repeated runs on the same models are lighter on the source.

What is the difference between Auto-Data.net Scraper and Car Data Scraper?

Auto-Data.net Scraper reads auto-data.net only and returns one row per variant with the full spec sheet. Car Data Scraper is the multi-source version: it merges several sources into one consolidated row and traces every value back to where it came from.

Why are some rawSpecs entries missing?

Entries with no value are dropped, and so are the entries auto-data.net hides behind Log in to see. for visitors who are not signed in. The Actor never signs in.

Can I integrate Auto-Data.net Scraper with other apps?

Yes. Results can flow into Make, Zapier, n8n, Google Sheets, Looker Studio or Power BI through Apify's integrations, or be pulled directly with the Apify API.

Can I use Auto-Data.net Scraper as its own API?

Yes. Use apify-client for Node.js or Python to start runs and fetch the dataset. See the API tab on the Actor page.

Can I use Auto-Data.net Scraper via MCP?

Yes. Auto-Data.net Scraper can be accessed by AI assistants like Claude or ChatGPT through the Apify MCP server. Go to the MCP tab on the Actor page for setup, or connect to mcp.apify.com and add Auto-Data.net Scraper as a tool.

Your feedback

We're always working on improving the performance of our Actors. So if you've got any technical feedback for Auto-Data.net Scraper or simply found a bug, please create an issue on the Actor's Issues tab.

More free tools, scrapers, MCP servers and data studies from the same team: mr-bridge.com.

Related Actors

• Car Data Scraper: the multi-source version, which merges several car data sources into one consolidated row per variant.

Legal & responsible use

Auto-Data.net Scraper extracts vehicle technical specifications, which are factual data, not personal data. It does not extract names, contact details or any private user information.

auto-data.net has its own terms of use, and it may restrict automated access or commercial reuse. Before you rely on the output, in particular for commercial use, confirm that your use is permitted by those terms.

We believe that scraping public factual data for ethical purposes is safe. You remain responsible for how you use the results and for complying with the source's terms and with the laws that apply to you. If you're unsure whether your use is legitimate, consult your lawyers. You can also read the Apify blog post on the legality of web scraping.