# Fuel Economy & Vehicle Specs Scraper (EPA FuelEconomy.gov) (`crawlerbros/fuel-economy-scraper`) Actor Scrape the US Department of Energy's official FuelEconomy.gov database with EPA-verified fuel economy ratings, engine specs, emissions scores, and cost estimates for every vehicle sold in the US since 1984. No API key required. - **URL**: https://apify.com/crawlerbros/fuel-economy-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 7 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Fuel Economy & Vehicle Specs Scraper (EPA FuelEconomy.gov) Extract official EPA fuel economy ratings, engine specifications, emissions scores, and annual fuel cost estimates from the **US Department of Energy's FuelEconomy.gov** database. Covers every vehicle sold in the United States from 1984 to 2027, including electric vehicles, hybrids, and plug-in hybrids. No API key required. Data is 100% free and publicly available. ### What You Get Each scraped record contains: | Field | Description | |---|---| | `vehicleId` | Unique FuelEconomy.gov vehicle ID | | `url` | Direct link to the vehicle's fuel economy comparison page | | `year` | Model year | | `make` | Vehicle manufacturer (e.g. Toyota, Ford) | | `model` | Model name (e.g. Camry, F-150) | | `baseModel` | Base model name without trim | | `vehicleClass` | EPA vehicle class (e.g. Midsize Cars, SUV, Pickup Trucks) | | `drive` | Drivetrain (FWD, RWD, AWD, 4WD) | | `transmission` | Transmission type (e.g. Automatic (S8)) | | `cylinders` | Number of engine cylinders | | `displacement` | Engine displacement in liters | | `engineDescription` | Engine technology description | | `fuelType` | Primary fuel type | | `fuelType2` | Secondary fuel type (PHEVs / FFVs) | | `mpgCity` | City fuel economy (MPG) | | `mpgHighway` | Highway fuel economy (MPG) | | `mpgCombined` | Combined fuel economy (MPG) | | `mpgeCityAlt` | City MPGe for alternative fuel (EVs / PHEVs) | | `mpgeHwyAlt` | Highway MPGe for alternative fuel | | `mpgeCombinedAlt` | Combined MPGe for alternative fuel | | `co2GramsPerMile` | CO₂ tailpipe emissions in grams per mile | | `fuelEconomyScore` | EPA fuel economy score (1–10) | | `ghgScore` | Greenhouse gas score (1–10) | | `annualFuelCostUsd` | Estimated annual fuel cost in USD | | `evMotor` | Electric motor description (EVs) | | `electricRange` | All-electric range in miles (EVs / PHEVs) | | `chargeTime240vHours` | Time to charge on 240V Level 2 charger (hours) | | `phevCombinedMpge` | PHEV combined MPGe | | `turbocharged` | True if turbocharged | | `supercharged` | True if supercharged | | `hasStartStopTechnology` | True if equipped with start-stop | | `scrapedAt` | ISO 8601 timestamp | ### Input Options #### Mode: Search Vehicles Search by make + model + optional year. Returns all trim variants. ```json { "mode": "search", "make": "Toyota", "model": "Camry", "year": 2023, "maxItems": 50 } ```` Omit `year` to get all model years for that make/model combination. #### Mode: Browse All Models for a Make Get every vehicle variant ever produced by a manufacturer, with optional year range. ```json { "mode": "makeModels", "make": "Tesla", "yearMin": 2017, "yearMax": 2024, "maxItems": 200 } ``` #### Mode: List All Makes Get a list of all manufacturers with vehicles in the EPA database for a given year. ```json { "mode": "allMakes", "queryYear": 2023, "maxItems": 100 } ``` #### Mode: Fetch by Vehicle ID Fetch specific vehicles by their FuelEconomy.gov ID (found in the URL on the website). ```json { "mode": "byVehicleId", "vehicleIds": ["45719", "45726", "45720"] } ``` #### Filters Use `fuelTypeFilter` and `driveTrainFilter` to narrow results: ```json { "mode": "search", "make": "Ford", "model": "F-150", "fuelTypeFilter": "Regular Gasoline", "driveTrainFilter": "4-Wheel Drive", "maxItems": 50 } ``` ### Use Cases - **Car shopping research**: Compare EPA-verified MPG ratings across makes, models, and years - **Fleet management**: Identify fuel-efficient vehicles by class and drivetrain - **Environmental analysis**: Study CO₂ emissions and GHG scores by vehicle segment - **EV research**: Find electric vehicle range and charging time specifications - **Market research**: Track which manufacturers offer the most fuel-efficient lineups - **Academic research**: Build datasets of vehicle emissions for climate studies ### Data Source Data comes from the **US Department of Energy's FuelEconomy.gov** public REST API — the official source for EPA fuel economy testing results. Coverage includes: - All model years from 1984 to 2027 - 50+ manufacturers in recent years - Conventional, hybrid, plug-in hybrid, battery electric, fuel cell, and flex-fuel vehicles ### FAQ **Is an API key required?** No. FuelEconomy.gov is a free US government open data service with no authentication required. **How current is the data?** The EPA tests and publishes data for each new model year. 2026 and 2027 model year data may be partial (pre-production estimates). **Can I get historical data back to 1984?** Yes — set `yearMin: 1984` in makeModels mode to retrieve the full history for any manufacturer. **What's the difference between MPG and MPGe?** MPG (miles per gallon) is for conventional fuel. MPGe (miles per gallon equivalent) is used for electric vehicles, measuring equivalent energy in terms of gasoline. **Why are some EV records missing city/highway MPG?** For pure electric vehicles, the primary fuel economy metrics appear in `mpgeCityAlt` and `mpgeHwyAlt` (the alternative fuel columns), while `mpgCity`/`mpgHighway` are zero and omitted. # Actor input Schema ## `mode` (type: `string`): What to fetch from FuelEconomy.gov. ## `make` (type: `string`): Vehicle manufacturer (mode=search or mode=makeModels). E.g. 'Toyota', 'Ford', 'Honda'. Case-insensitive. ## `model` (type: `string`): Vehicle model name (mode=search). E.g. 'Camry', 'F-150', 'Civic'. Partial matches supported. ## `year` (type: `integer`): Model year to filter by. Leave blank to search all years. Range: 1984–2027. ## `yearMin` (type: `integer`): Minimum model year for mode=makeModels. Scrapes all years from yearMin to yearMax. ## `yearMax` (type: `integer`): Maximum model year for mode=makeModels. Defaults to current year if unset. ## `queryYear` (type: `integer`): Which model year to list makes for (mode=allMakes). Defaults to 2023. ## `fuelTypeFilter` (type: `string`): Only return vehicles with this fuel type. Leave blank for all. ## `driveTrainFilter` (type: `string`): Only return vehicles with this drive configuration. Leave blank for all. ## `vehicleIds` (type: `array`): List of FuelEconomy.gov vehicle IDs to fetch. E.g. \['45719', '45726']. ## `maxItems` (type: `integer`): Maximum number of vehicle records to emit. ## Actor input object example ```json { "mode": "search", "make": "Toyota", "model": "Camry", "queryYear": 2023, "fuelTypeFilter": "", "driveTrainFilter": "", "vehicleIds": [], "maxItems": 50 } ``` # Actor output Schema ## `vehicles` (type: `string`): Dataset containing all scraped vehicle records from FuelEconomy.gov. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "mode": "search", "make": "Toyota", "model": "Camry", "queryYear": 2023, "fuelTypeFilter": "", "driveTrainFilter": "", "vehicleIds": [], "maxItems": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/fuel-economy-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "mode": "search", "make": "Toyota", "model": "Camry", "queryYear": 2023, "fuelTypeFilter": "", "driveTrainFilter": "", "vehicleIds": [], "maxItems": 50, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/fuel-economy-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "search", "make": "Toyota", "model": "Camry", "queryYear": 2023, "fuelTypeFilter": "", "driveTrainFilter": "", "vehicleIds": [], "maxItems": 50 }' | apify call crawlerbros/fuel-economy-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/fuel-economy-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fuel Economy & Vehicle Specs Scraper (EPA FuelEconomy.gov)", "description": "Scrape the US Department of Energy's official FuelEconomy.gov database with EPA-verified fuel economy ratings, engine specs, emissions scores, and cost estimates for every vehicle sold in the US since 1984. No API key required.", "version": "1.0", "x-build-id": "643kbJoHJuSpJ8f2n" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~fuel-economy-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-fuel-economy-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~fuel-economy-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-fuel-economy-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~fuel-economy-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-fuel-economy-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "search", "makeModels", "allMakes", "byVehicleId" ], "type": "string", "description": "What to fetch from FuelEconomy.gov.", "default": "search" }, "make": { "title": "Make", "type": "string", "description": "Vehicle manufacturer (mode=search or mode=makeModels). E.g. 'Toyota', 'Ford', 'Honda'. Case-insensitive.", "default": "Toyota" }, "model": { "title": "Model", "type": "string", "description": "Vehicle model name (mode=search). E.g. 'Camry', 'F-150', 'Civic'. Partial matches supported.", "default": "Camry" }, "year": { "title": "Year", "minimum": 1984, "maximum": 2027, "type": "integer", "description": "Model year to filter by. Leave blank to search all years. Range: 1984–2027." }, "yearMin": { "title": "Year (min)", "minimum": 1984, "maximum": 2027, "type": "integer", "description": "Minimum model year for mode=makeModels. Scrapes all years from yearMin to yearMax." }, "yearMax": { "title": "Year (max)", "minimum": 1984, "maximum": 2027, "type": "integer", "description": "Maximum model year for mode=makeModels. Defaults to current year if unset." }, "queryYear": { "title": "Year (for allMakes mode)", "minimum": 1984, "maximum": 2027, "type": "integer", "description": "Which model year to list makes for (mode=allMakes). Defaults to 2023.", "default": 2023 }, "fuelTypeFilter": { "title": "Fuel type filter", "enum": [ "", "Regular Gasoline", "Premium Gasoline", "Midgrade Gasoline", "Diesel", "Electricity", "Natural Gas", "Hydrogen", "E85" ], "type": "string", "description": "Only return vehicles with this fuel type. Leave blank for all.", "default": "" }, "driveTrainFilter": { "title": "Drive train filter", "enum": [ "", "Front-Wheel Drive", "Rear-Wheel Drive", "All-Wheel Drive", "4-Wheel Drive", "4-Wheel or All-Wheel Drive", "Part-time 4-Wheel Drive" ], "type": "string", "description": "Only return vehicles with this drive configuration. Leave blank for all.", "default": "" }, "vehicleIds": { "title": "Vehicle IDs (mode=byVehicleId)", "type": "array", "description": "List of FuelEconomy.gov vehicle IDs to fetch. E.g. ['45719', '45726'].", "default": [], "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of vehicle records to emit.", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```