# Txdot Scraper (`flamboyant_liner/txdot-scraper`) Actor TxDOT Bid Tabulations Scraper. Structured data export for lead generation, enrichment, and competitive research. - **URL**: https://apify.com/flamboyant\_liner/txdot-scraper.md - **Developed by:** [Khrystyna Skotte](https://apify.com/flamboyant_liner) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## TxDOT Bid Tabulations Scraper ### Overview Scrapes Texas Department of Transportation (TxDOT) bid tabulations and construction letting data via the Texas Open Data Portal (Socrata API). Access all contractor bids, engineer estimates, and project details. Updated daily. ### Features - Search by keywords to find specific results - Filter results by category or type - Export data in JSON, CSV, or Excel formats ### Use Cases - **Track** - Track federal government data releases and updates - **Build** - Build datasets for policy research and analysis - **Monitor** - Monitor regulatory changes and compliance requirements - **Aggregate** - Aggregate public government data for transparency projects ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `dataType` | string | Type of data to fetch | `bidTabulations` | | `district` | string | Filter by TxDOT district name or number | | | `county` | string | Filter by Texas county name | | | `projectType` | string | Filter by project classification | | | `lettingDateStart` | string | Start date for letting date range (YYYY-MM-DD) | | | `lettingDateEnd` | string | End date for letting date range (YYYY-MM-DD) | | | `contractor` | string | Filter by contractor/bidder name (partial match) | | | `minBidAmount` | integer | Filter to bids >= this amount in USD | | | `limit` | integer | Maximum number of records to return | `1000` | ### Output Example Each result contains structured data like this: ```json { "projectId": "ABC-12345", "lettingDate": "2025-01-15", "district": "Sample district", "county": 127, "contractor": "Sample contractor", "bidAmount": 50000, "engineerEstimate": "Sample engineerEstimate", "projectType": "Sample projectType", "description": "Detailed description of the item...", "awarded": "Sample awarded" } ```` ### Pricing This actor uses pay-per-result pricing: - **$0.001** per result - **$1.00** per 1,000 results No monthly fees. You only pay for what you scrape. [Apify Free plan](https://apify.com/pricing) includes $5/month in platform credits. ### How to Run #### Apify Console 1. Go to the [TxDOT Bid Tabulations Scraper](https://apify.com/fortuitous_pirate/txdot-scraper) actor page 2. Configure your input parameters 3. Click **Start** and wait for the results 4. Download data in JSON, CSV, or Excel format #### API ```bash curl -X POST "https://api.apify.com/v2/acts/fortuitous_pirate~txdot-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"maxItems": 10}' ``` #### Python SDK ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("fortuitous_pirate/txdot-scraper").call( run_input={"maxItems": 10} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Integration Connect TxDOT Bid Tabulations Scraper with your existing tools and workflows: - **API access** - Programmatic access via [Apify API](https://docs.apify.com/api/v2) - **Webhooks** - Get notified when scraping completes - **Scheduling** - Set up recurring runs on any schedule - **Zapier / Make** - Connect with 5,000+ apps via [Apify integrations](https://apify.com/integrations) - **Python / Node.js SDKs** - Native client libraries for easy integration # Actor input Schema ## `dataType` (type: `string`): Type of data to fetch ## `district` (type: `string`): Filter by TxDOT district name or number ## `county` (type: `string`): Filter by Texas county name ## `projectType` (type: `string`): Filter by project classification ## `lettingDateStart` (type: `string`): Start date for letting date range (YYYY-MM-DD) ## `lettingDateEnd` (type: `string`): End date for letting date range (YYYY-MM-DD) ## `contractor` (type: `string`): Filter by contractor/bidder name (partial match) ## `minBidAmount` (type: `integer`): Filter to bids >= this amount in USD ## `limit` (type: `integer`): Maximum number of records to return ## Actor input object example ```json { "dataType": "bidTabulations", "lettingDateStart": "2024-01-01", "limit": 1000 } ``` # 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 = { "lettingDateStart": "2024-01-01" }; // Run the Actor and wait for it to finish const run = await client.actor("flamboyant_liner/txdot-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 = { "lettingDateStart": "2024-01-01" } # Run the Actor and wait for it to finish run = client.actor("flamboyant_liner/txdot-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 '{ "lettingDateStart": "2024-01-01" }' | apify call flamboyant_liner/txdot-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=flamboyant_liner/txdot-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Txdot Scraper", "description": "TxDOT Bid Tabulations Scraper. Structured data export for lead generation, enrichment, and competitive research.", "version": "1.0", "x-build-id": "fLWBRl8tGxatOnPuW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/flamboyant_liner~txdot-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-flamboyant_liner-txdot-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/flamboyant_liner~txdot-scraper/runs": { "post": { "operationId": "runs-sync-flamboyant_liner-txdot-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/flamboyant_liner~txdot-scraper/run-sync": { "post": { "operationId": "run-sync-flamboyant_liner-txdot-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "dataType": { "title": "Data Type", "enum": [ "bidTabulations", "lettingSchedule", "both" ], "type": "string", "description": "Type of data to fetch", "default": "bidTabulations" }, "district": { "title": "District Filter", "type": "string", "description": "Filter by TxDOT district name or number" }, "county": { "title": "County Filter", "type": "string", "description": "Filter by Texas county name" }, "projectType": { "title": "Project Type", "type": "string", "description": "Filter by project classification" }, "lettingDateStart": { "title": "Letting Date Start", "type": "string", "description": "Start date for letting date range (YYYY-MM-DD)" }, "lettingDateEnd": { "title": "Letting Date End", "type": "string", "description": "End date for letting date range (YYYY-MM-DD)" }, "contractor": { "title": "Contractor Filter", "type": "string", "description": "Filter by contractor/bidder name (partial match)" }, "minBidAmount": { "title": "Minimum Bid Amount", "minimum": 0, "type": "integer", "description": "Filter to bids >= this amount in USD" }, "limit": { "title": "Maximum Results", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Maximum number of records to return", "default": 1000 } } }, "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 } } } } } } } } } } ```