# DAT Freight Rates Scraper (`automation-lab/dat-freight-rates-scraper`) Actor 🚚 Extract public DAT Trendlines freight rates, load-to-truck ratios, regional rates, state ratios, and diesel fuel prices for logistics analytics. - **URL**: https://apify.com/automation-lab/dat-freight-rates-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 dat record extracteds 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 ## DAT Freight Rates Scraper Extract public DAT Trendlines freight market data for logistics analytics, broker pricing, shipper benchmarking, and trucking market monitoring. The actor collects spot and contract rates, load-to-truck ratios, regional rates, state/province demand signals, national trend changes, and diesel fuel prices from DAT's public Trendlines experience. ### What does DAT Freight Rates Scraper do? DAT Freight Rates Scraper turns the public DAT Trendlines pages into structured JSON records. It is designed for recurring freight market monitoring. It can extract: - 🚚 Van, reefer, and flatbed market data - πŸ“ˆ National monthly spot rates - πŸ“‰ National monthly contract rates - βš–οΈ Load-to-truck ratios - πŸ—ΊοΈ State and province demand/capacity ratios - 🌎 Regional rate-per-mile values - β›½ Diesel fuel prices - πŸ” Week-over-week, month-over-month, and year-over-year changes ### Who is it for? Freight brokers use it to monitor pricing conditions before quoting lanes. Dispatchers use it to understand equipment-specific market tightness. Shippers use it to benchmark current conditions against recent months. Logistics analysts use it to feed BI dashboards and recurring reports. Freight tech teams use it to enrich internal pricing and planning workflows. ### Why use this scraper? DAT Trendlines is useful but not packaged as a clean export for automation. This actor provides repeatable extraction without manual copying. It normalizes multiple DAT widgets into one dataset. It includes source URLs and scrape timestamps for auditing. It avoids paid DAT products and uses only public Trendlines data. ### What data can you extract? | Data group | Example records | | --- | --- | | Snapshot trends | Van spot rate YoY change, national load postings WoW | | National rates | Van spot all-in rate by month | | Load/truck history | Reefer monthly ratio and recent weekly ratios | | State ratios | CA van loads, trucks, and load-to-truck ratio | | Regional rates | West flatbed trip rate per mile | | Fuel price | Latest diesel price per gallon | ### Output fields | Field | Description | | --- | --- | | `recordType` | Dataset group such as `nationalRates` or `regionalRates` | | `equipmentType` | `VAN`, `REEFER`, or `FLATBED` | | `metric` | Human-readable metric name | | `period` | Month, week, or date when available | | `periodType` | `month`, `week`, `year`, or `current` | | `rateType` | `SPOT` or `CONTRACT` | | `country` | Country code when applicable | | `regionCode` | DAT region code | | `regionName` | Friendly region label | | `stateCode` | State or province code | | `stateCodes` | States included in a region | | `loadCount` | Public DAT load count signal | | `truckCount` | Public DAT truck count signal | | `loadToTruckRatio` | Demand/capacity ratio | | `rateUsd` | Linehaul rate in USD | | `fuelSurchargeUsd` | Fuel surcharge in USD | | `allInRateUsd` | Rate plus fuel surcharge or regional trip rate | | `fuelPriceUsdPerGallon` | Diesel price per gallon | | `percentChange` | Trend change percentage | | `sourceUrl` | Source endpoint/page | | `scrapedAt` | ISO scrape timestamp | ### How much does it cost to scrape DAT freight rates? The actor uses pay-per-event pricing. There is no separate start fee in the current platform pricing. Billing is based on DAT records written to the dataset. The current BRONZE per-record price is about `$0.000020117`, with lower per-record prices on higher Apify subscription tiers. Small monitoring runs can limit `maxItems`. Full Trendlines runs usually produce hundreds of records, so increase `maxItems` above the cheap default when you want the complete public Trendlines export. Always check the Apify run cost and output count for your exact configuration. ### How to use DAT Freight Rates Scraper 1. Open the actor on Apify. 2. Choose one or more equipment types. 3. Choose the DAT Trendlines datasets you need. 4. Keep the default `maxItems` of 20 for a cheap smoke test, or increase it for a complete public Trendlines export. 5. Start the actor. 6. Export JSON, CSV, Excel, or connect the dataset to your workflow. ### Input options #### Equipment types Select `VAN`, `REEFER`, `FLATBED`, or all three. #### Datasets Choose from snapshot trends, national rates, load/truck history, state ratios, regional rates, and fuel price. #### Maximum records Use `maxItems` to control spend or sample a subset. #### Raw data Turn on `includeRawData` only when debugging. ### Example input ```json { "equipmentTypes": ["VAN", "REEFER", "FLATBED"], "datasets": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ], "maxItems": 500, "includeRawData": false } ```` ### Example output ```json { "recordType": "nationalRates", "equipmentType": "VAN", "metric": "spot all-in national rate", "period": "2026-05", "periodType": "month", "rateType": "SPOT", "country": "US", "rateUsd": 1.68, "fuelSurchargeUsd": 0.5, "allInRateUsd": 2.18, "sourceUrl": "https://analytics.api.dat.com/v2/trendlines/nationalHistory", "scrapedAt": "2026-06-28T00:00:00.000Z" } ``` ### Tips for freight analytics Run the actor daily or weekly to capture a time series snapshot. Filter by `recordType` before loading dashboards. Use `equipmentType` to separate van, reefer, and flatbed markets. Use `allInRateUsd` for quick benchmark comparisons. Use `loadToTruckRatio` to detect tighter capacity markets. ### Integrations Export the Apify dataset to Google Sheets for broker teams. Send results to a warehouse such as BigQuery, Snowflake, or Postgres. Trigger a Make or Zapier workflow when the actor run finishes. Use Apify webhooks to notify pricing analysts after each scrape. Combine results with internal tender, quote, and shipment data. ### API usage #### Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/dat-freight-rates-scraper').call({ equipmentTypes: ['VAN', 'REEFER'], maxItems: 300 }); console.log(run.defaultDatasetId); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient('MY_APIFY_TOKEN') run = client.actor('automation-lab/dat-freight-rates-scraper').call(run_input={ 'equipmentTypes': ['VAN', 'REEFER'], 'maxItems': 300, }) print(run['defaultDatasetId']) ``` #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/automation-lab~dat-freight-rates-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"equipmentTypes":["VAN"],"maxItems":100}' ``` ### MCP usage Use this actor from Claude Desktop, Claude Code, or other MCP clients through Apify MCP. MCP tool URL: `https://mcp.apify.com/?tools=automation-lab/dat-freight-rates-scraper` Claude Code setup: ```bash claude mcp add apify-dat-freight-rates https://mcp.apify.com/?tools=automation-lab/dat-freight-rates-scraper ``` Claude Desktop JSON setup: ```json { "mcpServers": { "apify-dat-freight-rates": { "url": "https://mcp.apify.com/?tools=automation-lab/dat-freight-rates-scraper" } } } ``` Example prompts: - "Run the DAT freight rates scraper for van and reefer and summarize rate changes." - "Extract DAT Trendlines regional rates and show the highest flatbed regions." - "Get load-to-truck ratios for all equipment types and create a capacity table." ### Scheduling Create an Apify schedule to run this actor every Monday morning. Use the dataset export as a weekly freight-market snapshot. Store each run's dataset ID in your BI pipeline. Compare output records over time using `period`, `recordType`, and `equipmentType`. ### Common workflows Freight broker rate desk: - Run weekly. - Export national spot and contract rates. - Compare against internal quotes. Shipper analytics: - Run monthly. - Monitor `allInRateUsd` and `loadToTruckRatio`. - Flag volatile regions. Carrier operations: - Run daily. - Track state/province demand signals. - Prioritize markets with higher load-to-truck ratios. ### Data freshness DAT controls the update cadence of the public Trendlines app. The actor captures whatever public data is available at run time. Each record includes `scrapedAt` for auditability. Period fields show the DAT month, week, or current snapshot where available. ### Limitations This actor does not log into DAT. It does not scrape paid RateView, Market Conditions, or private account data. It only extracts public DAT Trendlines data. If DAT changes the public app endpoints, the actor may need an update. ### Legality This actor collects publicly available web data. You are responsible for using the data in accordance with applicable laws, DAT terms, and your internal compliance policies. Do not use the actor to access private accounts or paid DAT products. ### FAQ #### Is this an official DAT API? No. This actor extracts public DAT Trendlines data exposed by DAT's public web experience. #### Does it access paid DAT tools? No. It avoids authenticated DAT products and paid RateView or Market Conditions account areas. ### Troubleshooting #### Why did I get fewer records than expected? Check `maxItems`. The actor stops when the cap is reached. Also confirm that the selected datasets and equipment types include the records you need. #### Why are some fields empty? Different DAT widgets expose different fields. For example, fuel records do not have `equipmentType`, and state ratio records do not have rates. #### Can I scrape one equipment type only? Yes. Set `equipmentTypes` to a single value such as `["VAN"]`. ### Related scrapers Explore other Automation Lab actors at `https://apify.com/automation-lab/`. Relevant portfolio directions include logistics data, business intelligence, market monitoring, and B2B data extraction. ### Support If DAT changes its public Trendlines app or you need another freight-market field, open an issue on the actor page. Include your input JSON and run ID so the issue can be reproduced quickly. ### Version notes Version 0.1 focuses on public DAT Trendlines datasets. Future versions may add additional public freight-market pages if they are stable and commercially useful. ### Output quality checklist Records are normalized. Numeric values are emitted as numbers. Every record includes a source URL. Every record includes a scrape timestamp. Optional raw payloads are available for debugging. # Actor input Schema ## `equipmentTypes` (type: `array`): DAT equipment categories to collect. Select one or more of VAN, REEFER, and FLATBED. ## `datasets` (type: `array`): Choose which public DAT Trendlines datasets to extract. ## `maxItems` (type: `integer`): Stop after this many output records. Prefill is intentionally small for a cheap first run; increase it for full Trendlines exports. ## `includeRawData` (type: `boolean`): Attach the source DAT API object to each result for debugging or downstream validation. ## Actor input object example ```json { "equipmentTypes": [ "VAN", "REEFER", "FLATBED" ], "datasets": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ], "maxItems": 20, "includeRawData": false } ``` # 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 = { "equipmentTypes": [ "VAN", "REEFER", "FLATBED" ], "datasets": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ], "maxItems": 20, "includeRawData": false }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/dat-freight-rates-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "equipmentTypes": [ "VAN", "REEFER", "FLATBED", ], "datasets": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice", ], "maxItems": 20, "includeRawData": False, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/dat-freight-rates-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "equipmentTypes": [ "VAN", "REEFER", "FLATBED" ], "datasets": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ], "maxItems": 20, "includeRawData": false }' | apify call automation-lab/dat-freight-rates-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/dat-freight-rates-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "DAT Freight Rates Scraper", "description": "🚚 Extract public DAT Trendlines freight rates, load-to-truck ratios, regional rates, state ratios, and diesel fuel prices for logistics analytics.", "version": "0.1", "x-build-id": "b4HbRQx0WNqKTjzYW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~dat-freight-rates-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-dat-freight-rates-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~dat-freight-rates-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-dat-freight-rates-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~dat-freight-rates-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-dat-freight-rates-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", "properties": { "equipmentTypes": { "title": "Equipment types", "uniqueItems": true, "type": "array", "description": "DAT equipment categories to collect. Select one or more of VAN, REEFER, and FLATBED.", "items": { "type": "string", "enum": [ "VAN", "REEFER", "FLATBED" ], "enumTitles": [ "Van", "Reefer", "Flatbed" ] }, "default": [ "VAN", "REEFER", "FLATBED" ] }, "datasets": { "title": "Trendline datasets", "uniqueItems": true, "type": "array", "description": "Choose which public DAT Trendlines datasets to extract.", "items": { "type": "string", "enum": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ], "enumTitles": [ "Snapshot percent changes", "National spot and contract rates", "Monthly/weekly load-to-truck history", "State/province load-to-truck ratios", "Regional rates", "Diesel fuel price" ] }, "default": [ "snapshotTrends", "nationalRates", "loadTruckHistory", "stateLoadTruckRatios", "regionalRates", "fuelPrice" ] }, "maxItems": { "title": "Maximum records", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Stop after this many output records. Prefill is intentionally small for a cheap first run; increase it for full Trendlines exports.", "default": 20 }, "includeRawData": { "title": "Include raw API data", "type": "boolean", "description": "Attach the source DAT API object to each result for debugging or downstream validation.", "default": false } } }, "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 } } } } } } } } } } ```