Choosing Car Data Sources

Carapis unifies 200+ car marketplaces across 10 regions behind one API. This guide helps you pick the right sources for your use case — by region, vehicle type and data depth.

Start with the question, not the marketplace

Before choosing sources, pin down what you’re building. Three questions narrow the field fast:

1. Which markets matter? A dealer pricing tool needs the marketplaces your customers actually buy and sell on. An import/export business needs the source and destination markets.
2. Which vehicle types? Used vs new, private vs dealer, retail vs auction — not every marketplace covers all of them.
3. How deep does the data need to be? A simple price feed needs less than a residual-value model that depends on inspection sheets and accident history.

Choosing by region

Carapis groups marketplaces by region. A few high-signal sources per region:

Browse the full set on the platforms page. If you need a market that isn’t listed, the same unified schema makes adding it straightforward.

Choosing by vehicle type

Different products need different inventory:

• Used cars — the broadest category; almost every marketplace covers it. Best for pricing tools and consumer apps.
• New cars — fewer sources; useful for new-vs-used price gap analysis.
• Dealer inventory — marketplaces with dealer feeds give you certified listings and richer seller metadata.
• Auction data — Japanese auction sources expose grades and inspection sheets; ideal for export businesses. See parsing Japanese car auction data.

You can filter on type at query time rather than choosing a single-purpose marketplace:

import requests
 
resp = requests.get(
    "https://api.carapis.com/v2/listings",
    params={"source": "encar", "vehicle_type": "dealer", "limit": 100},
    headers={"Authorization": f"Bearer {API_KEY}"},
)

Choosing by data depth

The richest decisions depend on condition data, which not every marketplace provides:

• Price-only feeds — every source gives you make/model/year/mileage/price. Enough for market-rate dashboards.
• Price history — sources that expose priceHistory let you detect motivated sellers and trends.
• Inspection sheets — Korean (Encar) and Japanese auction sources attach structured condition records. Essential for import/export vetting and residual-value modeling.
• Accident & repair history — closest thing to a CARFAX-style record on the marketplaces that carry it.

A quick way to compare depth across candidate sources:

SOURCES = ["encar", "mobile-de", "autotrader"]
 
for source in SOURCES:
    resp = requests.get(
        "https://api.carapis.com/v2/listings",
        params={"source": source, "limit": 1},
        headers={"Authorization": f"Bearer {API_KEY}"},
    )
    sample = resp.json()["results"][0]
    has_sheet = "inspectionSheet" in sample and sample["inspectionSheet"]
    has_history = bool(sample.get("priceHistory"))
    print(f"{source}: inspection_sheet={bool(has_sheet)} price_history={has_history}")

Combining sources

Because every marketplace returns the same schema, combining them is just a loop — no per-source parsing. This is how cross-market products (import/export arbitrage, multi-region pricing) are built:

def gather(sources, **filters):
    all_cars = []
    for source in sources:
        resp = requests.get(
            "https://api.carapis.com/v2/listings",
            params={"source": source, "limit": 200, **filters},
            headers={"Authorization": f"Bearer {API_KEY}"},
        )
        all_cars.extend(resp.json()["results"])
    return all_cars
 
 
cars = gather(["encar", "che168"], make="Hyundai", model="Santa Fe")
print(f"{len(cars)} listings across 2 markets")

Recommendations by use case

• Dealer pricing / appraisal — your local marketplaces plus one regional benchmark. See dealership intelligence.
• Import / export — source market with inspection sheets (Encar, Japanese auctions) + destination market for resale value. See import / export.
• Market research — breadth over depth; pull many marketplaces per region. See market research.
• Consumer “good deal” apps — used-car sources with price history in your target country.

Next steps

Once you’ve picked your sources, see the car data parsing guide for handling the normalized records, and the API reference for the full query surface.