# Eurostar Scraper — Train Tickets, Prices & Schedule Data (`studio-amba/eurostar-scraper`) Actor Scrape Eurostar high-speed train schedules, prices, and availability. Search by route and date to get departure/arrival times, durations, ticket prices by class, and seat availability. Covers London, Paris, Brussels, Amsterdam, Cologne, and more. No login or cookies required. - **URL**: https://apify.com/studio-amba/eurostar-scraper.md - **Developed by:** [Studio Amba](https://apify.com/studio-amba) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ### What does Eurostar Scraper do? **Eurostar Scraper** extracts train schedules, ticket prices, and seat availability from [Eurostar.com](https://www.eurostar.com). Search by origin, destination, and travel date to get departure and arrival times, journey durations, prices by ticket class, train numbers, and availability status. Covers routes between London, Paris, Brussels, Amsterdam, Cologne, and other European cities. No login or cookies required. Use it on the Apify platform to access structured data via API, schedule price monitoring, and integrate with tools like Zapier, Make, Google Sheets, and Slack. ### How to scrape Eurostar data 1. Go to the Eurostar Scraper on the Apify Store. 2. Click **Try for free** to open the actor in the Apify Console. 3. Enter your origin city (e.g. "London") and destination city (e.g. "Paris"). 4. Set the departure date in YYYY-MM-DD format (must be a future date). 5. Optionally adjust the number of passengers (default: 1). 6. Click **Start** and wait for the run to finish. 7. Download your data as JSON, CSV, Excel, or HTML from the Output tab. ### Why use Eurostar Scraper? - **Price monitoring** -- Track Eurostar ticket prices over time to find the best deals on specific routes. - **Travel planning** -- Compare departure times, durations, and prices across different dates and routes. - **Competitive analysis** -- Travel agencies and comparison platforms can collect Eurostar pricing data alongside flights and buses. - **Revenue management** -- Analyze pricing patterns across routes, dates, and ticket classes. - **Research** -- Gather transport data for academic or market research on European high-speed rail. ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `origin` | String | Yes | Departure city or station name (e.g. "London", "Paris", "Brussels", "Amsterdam"). | | `destination` | String | Yes | Arrival city or station name (e.g. "Paris", "Brussels", "London", "Amsterdam"). | | `departureDate` | String | Yes | Travel date in YYYY-MM-DD format (e.g. "2026-06-15"). Must be a future date. | | `passengers` | Integer | No | Number of adult passengers, 1-9 (default: 1). | | `maxResults` | Integer | No | Maximum number of train results to return (default: 20, max: 100). | | `proxyConfiguration` | Object | No | Proxy settings. Residential proxies recommended for bot protection. | ### Output Each result contains structured data about a single Eurostar train service. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. #### Example output ```json { "origin": "London St Pancras", "destination": "Paris Gare du Nord", "departureTime": "2026-06-15T07:01:00", "arrivalTime": "2026-06-15T10:17:00", "duration": "2h 16m", "price": 78.00, "currency": "GBP", "class": "Standard", "trainNumber": "ES9014", "available": true, "url": "https://www.eurostar.com/search?origin=London&destination=Paris&date=2026-06-15", "scrapedAt": "2026-05-11T10:30:00.000Z" } ```` ### Data fields | Field | Type | Description | |-------|------|-------------| | `origin` | String | Departure station name | | `destination` | String | Arrival station name | | `departureTime` | String | Departure date and time (ISO 8601) | | `arrivalTime` | String | Arrival date and time (ISO 8601) | | `duration` | String | Journey duration (e.g. "2h 16m") | | `price` | Number | Lowest available ticket price (null if sold out) | | `currency` | String | Currency code (EUR or GBP) | | `class` | String | Ticket class (Standard, Standard Premier, Business Premier) | | `trainNumber` | String | Eurostar train number | | `available` | Boolean | Whether seats are available at this price | | `url` | String | Search URL on Eurostar.com | | `scrapedAt` | String | ISO 8601 timestamp of when the data was collected | ### Cost estimate This actor uses approximately **1 compute unit per search** (one route and date). With the Apify free tier you can run a limited number of searches at no cost. For price monitoring across multiple dates, expect roughly $0.50 per 100 date searches at standard Apify pricing. ### Tips - Search one route and date per run for the most reliable results. - Schedule daily runs on the same route to build a price history and spot when fares drop. - Combine multiple runs across dates to compare pricing for flexible travel plans. - Residential proxies are recommended since Eurostar.com has bot protection. - Use the Apify API to integrate results directly into your travel comparison workflow. ### Limitations - Prices shown are for adult passengers only. Child and youth fares may differ. - Eurostar occasionally changes its website structure, which may temporarily affect results. - Only direct Eurostar services are returned -- connecting trains are not included. - Data is scraped from the public website and may change without notice. ### FAQ and support **Is it legal to scrape Eurostar.com?** Scraping publicly available data is generally permitted. This actor only accesses public search results that require no login. **How accurate are the prices?** Prices are scraped in real time from Eurostar.com each time the actor runs. They reflect what is available at that moment but can change quickly. **I found a bug or have a feature request.** Open an issue in the Issues tab on the actor page. You can also request a custom scraping solution. # Actor input Schema ## `origin` (type: `string`): Departure city or station name (e.g. 'London', 'Paris', 'Brussels', 'Amsterdam', 'Cologne'). ## `destination` (type: `string`): Arrival city or station name (e.g. 'Paris', 'Brussels', 'London', 'Amsterdam'). ## `departureDate` (type: `string`): Travel date in YYYY-MM-DD format (e.g. '2026-05-01'). Must be a future date. ## `passengers` (type: `integer`): Number of adult passengers (1-9). ## `maxResults` (type: `integer`): Maximum number of train results to return. ## `proxyConfiguration` (type: `object`): Proxy settings. Residential proxies recommended for Eurostar (bot protection). ## Actor input object example ```json { "origin": "London", "destination": "Paris", "departureDate": "2026-05-01", "passengers": 1, "maxResults": 20 } ``` # 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 = { "origin": "London", "destination": "Paris", "departureDate": "2026-05-01" }; // Run the Actor and wait for it to finish const run = await client.actor("studio-amba/eurostar-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 = { "origin": "London", "destination": "Paris", "departureDate": "2026-05-01", } # Run the Actor and wait for it to finish run = client.actor("studio-amba/eurostar-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 '{ "origin": "London", "destination": "Paris", "departureDate": "2026-05-01" }' | apify call studio-amba/eurostar-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=studio-amba/eurostar-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Eurostar Scraper — Train Tickets, Prices & Schedule Data", "description": "Scrape Eurostar high-speed train schedules, prices, and availability. Search by route and date to get departure/arrival times, durations, ticket prices by class, and seat availability. Covers London, Paris, Brussels, Amsterdam, Cologne, and more. No login or cookies required.", "version": "0.1", "x-build-id": "HBUDrPn6vqieKitBw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/studio-amba~eurostar-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-studio-amba-eurostar-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/studio-amba~eurostar-scraper/runs": { "post": { "operationId": "runs-sync-studio-amba-eurostar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/studio-amba~eurostar-scraper/run-sync": { "post": { "operationId": "run-sync-studio-amba-eurostar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "origin", "destination", "departureDate" ], "properties": { "origin": { "title": "Origin Station", "type": "string", "description": "Departure city or station name (e.g. 'London', 'Paris', 'Brussels', 'Amsterdam', 'Cologne').", "default": "London" }, "destination": { "title": "Destination Station", "type": "string", "description": "Arrival city or station name (e.g. 'Paris', 'Brussels', 'London', 'Amsterdam').", "default": "Paris" }, "departureDate": { "title": "Departure Date", "type": "string", "description": "Travel date in YYYY-MM-DD format (e.g. '2026-05-01'). Must be a future date." }, "passengers": { "title": "Number of Passengers", "minimum": 1, "maximum": 9, "type": "integer", "description": "Number of adult passengers (1-9).", "default": 1 }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of train results to return.", "default": 20 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Residential proxies recommended for Eurostar (bot protection)." } } }, "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 } } } } } } } } } } ```