# Amtrak Rail Network Scraper — Routes, Stations, Alerts (`jungle_synthesizer/amtrak-rail-network-scraper`) Actor Amtrak's full US passenger rail network: every route (Acela, Northeast Regional, Silver Meteor, Coast Starlight and ~50 others), 1,000+ stations with codes, state, timezone and amenity flags (wheelchair, staffed, QuikTrak), and current service alerts. - **URL**: https://apify.com/jungle\_synthesizer/amtrak-rail-network-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Travel, Business, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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. 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 ## Amtrak Rail Network Scraper Scrapes the entire US passenger rail network from [Amtrak](https://www.amtrak.com). Returns every published route — Acela, Northeast Regional, Coast Starlight, California Zephyr, Silver Meteor and ~50 others — plus all 1,000+ stations with codes, state, timezone, amenity flags, and current service alerts. --- ### Amtrak Rail Network Scraper Features - Returns 53 published Amtrak routes with their full city paths. - Returns 1,026 stations with the 3-letter codes, city, state, timezone, and amenity flags everyone keeps re-typing into spreadsheets. - Reports per-station accessibility — wheelchair-accessible building, wheelchair lift, staffed booth, QuikTrak kiosk. - Pulls current service alerts for each route on a given travel date. - Filter by route name or 4-letter route code (Acela, COAS, Northeast Regional). Leave the filter empty for the whole network. - Pure JSON-API scraping. No headless browser, no captcha plumbing, no dramatics. --- ### Who Uses Amtrak Rail Network Data? - **Travel-tech startups** — power route lookup, fare-comparison front-ends, and itinerary builders without paying for a GTFS feed you'll have to clean anyway. - **Transportation researchers** — study network coverage, accessibility distribution, and service patterns across the US passenger-rail system. - **Booking & comparison sites** — keep an authoritative reference of every Amtrak station and route, refreshed on a schedule. - **Accessibility analytics** — audit which stations actually have wheelchair lifts versus only an "accessible building" flag, which is not the same thing. - **Internal tools** — populate dropdowns and validate user-typed origin / destination cities against the real Amtrak station catalog. --- ### How Amtrak Rail Network Scraper Works 1. Pulls the routes catalog from Amtrak's published `routes-list.json`. 2. Pulls the station master and amenity tables in parallel and joins them on station code. 3. Optionally fans out a small alert lookup per filtered route on the requested travel date. 4. Emits one record per route and one record per station, capped by `maxItems`. The scraper hits public Amtrak content endpoints with a Chrome TLS fingerprint and a US residential proxy. Booking-flow journey searches sit behind a separate Akamai Bot Manager layer and are intentionally out of scope. --- ### Input ```json { "routeFilter": [], "includeStations": true, "alertDate": "", "maxItems": 15, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "countryCode": "US" } } ```` | Field | Type | Default | Description | |-------|------|---------|-------------| | `routeFilter` | string\[] | `[]` | Route names or 4-letter codes to include (case-insensitive substring match). Empty = every route. | | `includeStations` | boolean | `true` | When true, emits one record per station in addition to per-route records. | | `alertDate` | string | today | Date for the route service-alert query. Accepts `MM/DD/YYYY` or `YYYY-MM-DD`. | | `maxItems` | integer | `15` | Cap on total records (routes + stations combined). Set higher to crawl the full ~1,080-record network. | | `proxyConfiguration` | object | Apify residential / US | Standard Apify proxy block. Residential US is recommended. | #### Run a single route ```json { "routeFilter": ["Acela"], "includeStations": false, "maxItems": 5 } ``` #### Run the whole network ```json { "routeFilter": [], "includeStations": true, "maxItems": 1100 } ``` *** ### Amtrak Rail Network Scraper Output Fields Records carry a `record_type` of either `route` or `station`. Route fields are populated for routes; station fields are populated for stations; the unused side is empty / `false`. #### Route record example ```json { "record_type": "route", "route_code": "COAS", "route_name": "Coast Starlight", "route_url": "https://www.amtrak.com/train-routes/coast-starlight-train.html", "cities_served": [ "Seattle", "Tacoma", "Portland", "Sacramento", "San Francisco area", "Los Angeles" ], "service_alerts": [], "station_code": "", "station_name": "", "station_city": "", "station_state": "", "station_timezone": "", "station_quiktrak": false, "station_staffed": false, "station_accessible": false, "station_wheelchair_lift": false, "source_url": "https://www.amtrak.com/services/routes-list.json", "scraped_at": "2026-04-27T14:40:11.718Z" } ``` #### Station record example ```json { "record_type": "station", "route_code": "", "route_name": "", "route_url": "", "cities_served": [], "service_alerts": [], "station_code": "NYP", "station_name": "New York, NY", "station_city": "New York", "station_state": "NY", "station_timezone": "E", "station_quiktrak": true, "station_staffed": true, "station_accessible": true, "station_wheelchair_lift": true, "source_url": "https://www.amtrak.com/services/data.stations.json", "scraped_at": "2026-04-27T14:40:11.722Z" } ``` | Field | Type | Description | |-------|------|-------------| | `record_type` | string | `route` or `station`. | | `route_code` | string | 4-letter Amtrak route code (e.g. `ACEL`, `COAS`). Empty for station records. | | `route_name` | string | Human-readable route name (e.g. `Acela`, `Coast Starlight`). | | `route_url` | string | Public Amtrak route page URL. | | `cities_served` | string\[] | Ordered list of cities along the route, parsed from Amtrak's published `cityServed` string. | | `service_alerts` | string\[] | One-line summaries of any service alerts published for this route on `alertDate`. | | `station_code` | string | 3-letter Amtrak station code (e.g. `NYP`, `WAS`, `CHI`). | | `station_name` | string | Full station display name. | | `station_city` | string | City the station is in. | | `station_state` | string | Two-letter US/CA state code. | | `station_timezone` | string | `E`, `C`, `M`, `P`, `A`, or `H`. | | `station_quiktrak` | boolean | Self-service QuikTrak ticketing kiosk available. | | `station_staffed` | boolean | Station has Amtrak staff on site. | | `station_accessible` | boolean | Station building is wheelchair-accessible. | | `station_wheelchair_lift` | boolean | Wheelchair lift available for boarding. | | `source_url` | string | Source endpoint the record was derived from. | | `scraped_at` | string | ISO 8601 timestamp when the record was scraped. | *** ### FAQ #### How do I scrape Amtrak data? Amtrak Rail Network Scraper hits Amtrak's public content endpoints, joins the route catalog with the station master and amenity tables, and emits one flat record per route or station. Configure the input — usually leaving everything at defaults works — and run it. #### Does Amtrak Rail Network Scraper return live fares or seat availability? No. Amtrak's booking flow sits behind Akamai Bot Manager with sensor cookies and is intentionally out of scope. The actor returns the published network catalog (routes, stations, amenities) and route-level service alerts, not per-search journey results. #### Does Amtrak Rail Network Scraper need proxies? Yes — the static endpoints use Akamai TLS fingerprinting that rejects standard HTTP clients. The actor ships with the Apify residential US proxy preset and a Chrome TLS fingerprint, which is enough. #### Can I filter to a single route? Yes. Pass `routeFilter: ["Acela"]` (or `["COAS"]`, `["Northeast Regional"]`, etc.) to narrow the scrape. Filter terms are case-insensitive substring matches on the route code and route name. Leaving the filter empty pulls the entire 53-route catalog. #### How many records does a full run produce? Around 1,080 — 53 routes plus 1,026 stations. Set `maxItems` accordingly. Default is 15 to keep test runs fast. #### How fresh is the data? Routes and stations are published catalogs that change a handful of times a year. Service alerts are queried in real time for the date you supply. *** ### Need More Features? Need bus / Greyhound / Megabus coverage, a journey-search mode, or a different cut of the data? File an issue or get in touch. ### Why Use Amtrak Rail Network Scraper? - **Cheap** — pay-per-event pricing, ~$0.0015 per record at the default coefficient. The whole 1,080-record network costs less than a Northeast Regional sandwich. - **Clean output** — flat JSON, consistent field names, station codes uppercased, dates ISO-formatted. You spend less time normalizing and more time using the data. - **Stable** — no headless browser, no captcha solver, no scraping-the-DOM heuristics. Just published Amtrak content endpoints over HTTP. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `routeFilter` (type: `array`): Optional list of Amtrak route names or codes to include (e.g. \["Acela", "COAS", "Northeast Regional"]). Leave empty to scrape every route in Amtrak's published catalog. ## `includeStations` (type: `boolean`): When enabled, the actor emits one record per Amtrak station (~1,000 records) in addition to per-route records. Each station record includes its 3-letter code, city, state, timezone, and amenity flags. ## `alertDate` (type: `string`): Date to query for route service alerts. Defaults to today. Format: MM/DD/YYYY. ## `maxItems` (type: `integer`): Cap on total records emitted (routes + stations combined). Default and prefill are 15 to keep test runs fast; set higher to crawl the full ~1,080-record network. ## `proxyConfiguration` (type: `object`): No description ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "routeFilter": [], "includeStations": true, "maxItems": 15, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "countryCode": "US" } } ``` # Actor output Schema ## `results` (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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "routeFilter": [], "includeStations": true, "alertDate": "", "maxItems": 15, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "countryCode": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/amtrak-rail-network-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "routeFilter": [], "includeStations": True, "alertDate": "", "maxItems": 15, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "countryCode": "US", }, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/amtrak-rail-network-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "routeFilter": [], "includeStations": true, "alertDate": "", "maxItems": 15, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "countryCode": "US" } }' | apify call jungle_synthesizer/amtrak-rail-network-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/amtrak-rail-network-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amtrak Rail Network Scraper — Routes, Stations, Alerts", "description": "Amtrak's full US passenger rail network: every route (Acela, Northeast Regional, Silver Meteor, Coast Starlight and ~50 others), 1,000+ stations with codes, state, timezone and amenity flags (wheelchair, staffed, QuikTrak), and current service alerts.", "version": "1.0", "x-build-id": "IbAfeJiAmcSuuWDzl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~amtrak-rail-network-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-amtrak-rail-network-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/jungle_synthesizer~amtrak-rail-network-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-amtrak-rail-network-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/jungle_synthesizer~amtrak-rail-network-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-amtrak-rail-network-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": [ "sp_intended_usage", "sp_improvement_suggestions" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "routeFilter": { "title": "Route Filter", "type": "array", "description": "Optional list of Amtrak route names or codes to include (e.g. [\"Acela\", \"COAS\", \"Northeast Regional\"]). Leave empty to scrape every route in Amtrak's published catalog.", "items": { "type": "string" } }, "includeStations": { "title": "Include Station Catalog", "type": "boolean", "description": "When enabled, the actor emits one record per Amtrak station (~1,000 records) in addition to per-route records. Each station record includes its 3-letter code, city, state, timezone, and amenity flags.", "default": true }, "alertDate": { "title": "Alert Travel Date (MM/DD/YYYY)", "type": "string", "description": "Date to query for route service alerts. Defaults to today. Format: MM/DD/YYYY." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Cap on total records emitted (routes + stations combined). Default and prefill are 15 to keep test runs fast; set higher to crawl the full ~1,080-record network.", "default": 15 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "" } } }, "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 } } } } } } } } } } ```