# GlobalPetrolPrices Fuel Prices Scraper (`automation-lab/globalpetrolprices-fuel-prices-scraper`) Actor ⛽ Scrape public GlobalPetrolPrices country fuel price tables for gasoline, diesel, LPG, and electricity into clean datasets. - **URL**: https://apify.com/automation-lab/globalpetrolprices-fuel-prices-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## GlobalPetrolPrices Fuel Prices Scraper Scrape public country-level gasoline, diesel, LPG, and electricity price tables from GlobalPetrolPrices into clean Apify datasets. ### What does GlobalPetrolPrices Fuel Prices Scraper do? GlobalPetrolPrices Fuel Prices Scraper collects the public price tables published on GlobalPetrolPrices and turns them into structured rows. The actor is designed for repeat monitoring, dashboards, and API workflows where you need country-level fuel price snapshots without manually copying table data. It currently supports: - Gasoline prices - Diesel prices - LPG prices - Electricity prices Each output row represents one country or market in one selected table. ### Why use this scraper? GlobalPetrolPrices pages are useful for manual research, but the website is not a ready-to-query database. This actor normalizes the public tables into a consistent dataset so you can: - export rows to CSV, JSON, Excel, XML, or RSS, - connect price snapshots to BI dashboards, - compare fuel-price rankings across countries, - run scheduled monitoring tasks, - use the Apify API from applications and agents. ### Who is it for? #### Fleet and logistics teams Fleet operators can refresh country-level fuel assumptions for route planning, regional cost models, procurement analysis, or internal dashboards. Typical workflows: - compare diesel price levels across operating regions, - update monthly fuel-cost assumptions for cross-border routes, - enrich transport-cost models with country fuel benchmarks, - monitor whether a country has moved up or down in the public ranking. #### Market analysts and commodity researchers Analysts can collect repeatable snapshots of public fuel-price tables for reports, spreadsheets, or market intelligence systems. Typical workflows: - build a country-by-country fuel-price database, - compare gasoline, diesel, LPG, and electricity in one normalized export, - combine fuel-price rows with macroeconomic indicators, - refresh dashboard data on a schedule. #### Travel, route-cost, and mobility products Travel tools and mobility apps can use country-level fuel assumptions as one input in cost estimates. Typical workflows: - populate route-cost calculators with current gasoline or diesel assumptions, - show country-level fuel benchmarks in trip-planning content, - enrich destination pages with public fuel-price context, - keep fuel assumptions synchronized without manual table copying. #### Data journalists and researchers Journalists, academics, and public-policy researchers can quickly export comparable country rows for analysis and visualization. Typical workflows: - rank markets by public gasoline or diesel price, - create charts for energy-affordability stories, - compare fossil fuel and electricity price tables, - archive monthly public snapshots for longitudinal research. ### What data can it extract? The actor extracts the public country rows visible in GlobalPetrolPrices fuel and electricity tables. Supported table types: | Fuel type input | Source page type | Typical unit | | --- | --- | --- | | `gasoline` | Gasoline prices | liter | | `diesel` | Diesel prices | liter | | `lpg` | LPG prices | liter | | `electricity` | Electricity prices | kWh | The source may update available countries, values, dates, or labels over time. The actor saves what is visible in the public table at run time. ### Output fields | Field | Type | Description | | --- | --- | --- | | `fuelType` | string | Selected table type: gasoline, diesel, LPG, or electricity. | | `country` | string | Country or market label from the source table. | | `priceUsd` | number | Public price in USD as parsed from the table. | | `unit` | string | Unit such as liter or kWh. | | `currency` | string | Currency of the normalized price field, currently USD for `priceUsd`. | | `date` | string | Source table date when available. | | `rank` | integer | Row order from the source table, useful for ranking views. | | `countryUrl` | string | Country page URL when the source row links to one. | | `sourceUrl` | string | GlobalPetrolPrices table URL used for the row. | | `scrapedAt` | string | ISO timestamp when the row was collected. | | `url` | string | Canonical row/source URL for downstream tools. | ### Output example ```json { "fuelType": "gasoline", "country": "USA", "priceUsd": 0.9, "unit": "liter", "currency": "USD", "date": "2026-06-02", "rank": 48, "countryUrl": "https://www.globalpetrolprices.com/USA/gasoline_prices/", "sourceUrl": "https://www.globalpetrolprices.com/gasoline_prices/", "scrapedAt": "2026-06-08T09:00:00.000Z", "url": "https://www.globalpetrolprices.com/gasoline_prices/" } ```` ### Input options The actor keeps input intentionally small. #### `fuelTypes` Choose one or more public tables to scrape. Allowed values: - `gasoline` - `diesel` - `lpg` - `electricity` Default: `gasoline` and `diesel`. #### `maxItems` Maximum number of dataset rows to save across all selected fuel types. Use a small number for testing and a larger number when you want the full country table coverage. Default: `20`. ### How to use it in Apify Console 1. Open the actor on Apify. 2. Select the fuel types you need. 3. Set `maxItems` to the desired row cap. 4. Start the run. 5. Download the dataset or connect it to another integration. For a full snapshot, select all fuel types and set `maxItems` high enough to cover all rows you need. ### Scheduling fuel price monitoring Create an Apify task from a tested input and schedule it weekly or monthly. A scheduled task is useful when you need: - a recurring dashboard refresh, - a historical archive of public price snapshots, - alerts when downstream comparisons detect large changes, - repeat exports to cloud storage or Google Sheets. ### Pricing This actor uses pay-per-event pricing. There are two event types: 1. `Run started` — a one-time start event of `$0.005` per run. 2. `Result extracted` — a per-row event charged for each saved dataset item. Current result-event prices are: | User tier | Price per result | | --- | ---: | | FREE | `$0.0005175` | | BRONZE | `$0.00045` | | SILVER | `$0.000351` | | GOLD | `$0.00027` | | PLATINUM | `$0.00018` | | DIAMOND | `$0.000126` | ### Pricing examples Approximate charges before any platform taxes, credits, or account-level differences: | Example run | Tier | Formula | Approx. actor charge | | --- | --- | --- | ---: | | 20 rows | FREE | `$0.005 + 20 × $0.0005175` | `$0.01535` | | 150 rows | BRONZE | `$0.005 + 150 × $0.00045` | `$0.07250` | | 500 rows | SILVER | `$0.005 + 500 × $0.000351` | `$0.18050` | | 1,000 rows | GOLD | `$0.005 + 1,000 × $0.00027` | `$0.27500` | The exact total shown by Apify may include platform-level billing details outside the actor's event prices. ### Pricing note: platform minimum floor This is a very lightweight HTTP actor. Internal cost testing produced a formula-derived BRONZE result price below Apify's accepted minimum tier price. Because sub-minimum event prices are rejected by the Apify platform, the live BRONZE price uses the platform-safe floor of `$0.00045` per result. That floor is why the BRONZE result price is higher than a pure cost-plus formula would suggest for this specific actor. The price is still below many comparable fuel, vehicle, map, and market-data pay-per-event scrapers. ### Free-plan estimate A small test run with the default input (`fuelTypes`: gasoline and diesel, `maxItems`: 20) is designed to stay low-cost. At FREE-tier event pricing, the actor charge estimate is: ```text $0.005 start event + (20 rows × $0.0005175) = $0.01535 ``` If you only need a quick sample, keep `maxItems` near the default. If you need full coverage, increase `maxItems` and use the pricing table above to estimate the event charge. ### API usage with Node.js ```js import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor("automation-lab/globalpetrolprices-fuel-prices-scraper").call({ fuelTypes: ["gasoline", "diesel"], maxItems: 250, }); console.log(run.defaultDatasetId); ``` ### API usage with Python ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("automation-lab/globalpetrolprices-fuel-prices-scraper").call( run_input={"fuelTypes": ["gasoline"], "maxItems": 100} ) print(run["defaultDatasetId"]) ``` ### API usage with cURL ```bash curl -X POST "https://api.apify.com/v2/acts/automation-lab~globalpetrolprices-fuel-prices-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"fuelTypes":["gasoline","diesel"],"maxItems":250}' ``` ### Downloading results with the API After a run succeeds, use the dataset export endpoint. ```bash curl "https://api.apify.com/v2/datasets//items?format=json&clean=true&token=$APIFY_TOKEN" ``` You can replace `json` with `csv`, `xlsx`, `xml`, or another supported dataset format. ### MCP usage Use this actor from MCP clients with: ```text https://mcp.apify.com/?tools=automation-lab/globalpetrolprices-fuel-prices-scraper ``` Example prompt: ```text Scrape gasoline and diesel prices and summarize the five most expensive countries. ``` Claude Code setup: ```bash claude mcp add apify-globalpetrolprices https://mcp.apify.com/?tools=automation-lab/globalpetrolprices-fuel-prices-scraper ``` Claude Desktop JSON config: ```json { "mcpServers": { "apify-globalpetrolprices": { "url": "https://mcp.apify.com/?tools=automation-lab/globalpetrolprices-fuel-prices-scraper" } } } ``` ### Integration ideas Common integrations include: - Google Sheets for lightweight dashboarding, - BigQuery, Snowflake, or PostgreSQL for historical analysis, - Zapier or Make for alert workflows, - internal fleet-cost calculators, - notebooks for research and visualization, - AI agents that need current public fuel-price context. ### Data quality notes The actor reads public GlobalPetrolPrices HTML tables. It does not estimate missing values or infer hidden data. Keep these points in mind: - country coverage depends on the source table, - dates and labels may vary by fuel type, - source pages can change structure over time, - `maxItems` may intentionally limit saved rows, - rankings reflect the row order parsed from the source page. ### Limits This actor is not a station-level fuel-price scraper. It does not collect individual gas station addresses, city-level prices, live pump prices, or user-submitted local prices. It is intended for country-level public fuel and electricity price tables. ### Tips for best results - Use `maxItems` 10–30 when testing. - Select one fuel type when debugging a downstream workflow. - Select all fuel types for broad market dashboards. - Schedule runs at a cadence that matches your reporting needs. - Store previous datasets if you need historical comparisons. ### Troubleshooting #### The run returned fewer rows than expected Increase `maxItems` or select fewer fuel types. The cap applies across the whole run. #### A field is missing or null The value may not have been available in the source row. Check the `sourceUrl` and source page date. #### The page layout changed Open an actor issue with the run ID and input. Layout changes can require parser updates. #### The run is too small for my dashboard Increase `maxItems` and select all fuel types that your dashboard needs. ### Legality and responsible use This actor extracts publicly visible pages from GlobalPetrolPrices. You are responsible for using the data in accordance with applicable laws, source terms, attribution requirements, and your own compliance policies. Do not use this actor to overload the source website. Schedule reasonable runs and avoid unnecessary repetition. ### Related scrapers Other Automation Lab actors that may complement fuel-price analysis: - [Google Maps Scraper](https://apify.com/automation-lab/google-maps-scraper) — collect business/place data for route, retail, and local-market datasets. - [Google Maps Reviews Scraper](https://apify.com/automation-lab/google-maps-reviews-scraper) — collect review data for local businesses and service locations. - [Apple Maps Places Scraper](https://apify.com/automation-lab/apple-maps-places-scraper) — collect Apple Maps place data for local-market research. - [Autoscout24 Scraper](https://apify.com/automation-lab/autoscout24-scraper) — collect vehicle listings for automotive market analysis. - [Booking Scraper](https://apify.com/automation-lab/booking-scraper) — collect travel and accommodation data for trip-cost or destination research. ### FAQ #### Does it require login? No. It reads public pages. #### Does it use a browser? No. It uses HTTP requests and HTML parsing. #### Does it use proxies? No proxy is required for normal operation. #### Can I export to CSV? Yes. Apify datasets can be exported to CSV, JSON, Excel, XML, RSS, and other formats. #### Can I scrape only diesel prices? Yes. Set `fuelTypes` to `["diesel"]`. #### Can I get historical fuel prices? This actor saves the current public table at run time. To build history, schedule recurring runs and keep the datasets. ### Changelog Initial version extracts public country-level fuel price tables from GlobalPetrolPrices. # Actor input Schema ## `fuelTypes` (type: `array`): Choose which public GlobalPetrolPrices country tables to scrape. ## `maxItems` (type: `integer`): Maximum number of country price rows to save across all selected tables. ## Actor input object example ```json { "fuelTypes": [ "gasoline", "diesel" ], "maxItems": 20 } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "fuelTypes": [ "gasoline", "diesel" ], "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/globalpetrolprices-fuel-prices-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 = { "fuelTypes": [ "gasoline", "diesel", ], "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/globalpetrolprices-fuel-prices-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 '{ "fuelTypes": [ "gasoline", "diesel" ], "maxItems": 20 }' | apify call automation-lab/globalpetrolprices-fuel-prices-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/globalpetrolprices-fuel-prices-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GlobalPetrolPrices Fuel Prices Scraper", "description": "⛽ Scrape public GlobalPetrolPrices country fuel price tables for gasoline, diesel, LPG, and electricity into clean datasets.", "version": "0.1", "x-build-id": "h21Kz02OWbTTXUhBh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~globalpetrolprices-fuel-prices-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-globalpetrolprices-fuel-prices-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~globalpetrolprices-fuel-prices-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-globalpetrolprices-fuel-prices-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~globalpetrolprices-fuel-prices-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-globalpetrolprices-fuel-prices-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "fuelTypes" ], "properties": { "fuelTypes": { "title": "Fuel price tables", "uniqueItems": true, "type": "array", "description": "Choose which public GlobalPetrolPrices country tables to scrape.", "items": { "type": "string", "enum": [ "gasoline", "diesel", "lpg", "electricity" ], "enumTitles": [ "Gasoline", "Diesel", "LPG", "Electricity" ] }, "default": [ "gasoline", "diesel" ] }, "maxItems": { "title": "Maximum rows", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of country price rows to save across all selected tables.", "default": 20 } } }, "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 } } } } } } } } } } ```