# DOL OFLC Foreign Labor Disclosure Scraper (`jungle_synthesizer/dol-oflc-foreign-labor-disclosure-scraper`) Actor Extract H-2A, H-2B, PERM, Prevailing Wage, and CW-1 disclosure data from DOL OFLC quarterly XLSX files. Covers all non-H-1B foreign labor programs in one normalized schema with per-program filtering. - **URL**: https://apify.com/jungle\_synthesizer/dol-oflc-foreign-labor-disclosure-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, Other - **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. 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 ## DOL OFLC Foreign Labor Disclosure Scraper Scrapes the U.S. Department of Labor OFLC quarterly disclosure datasets for H-2A (agricultural), H-2B (seasonal), PERM (permanent labor certification), Prevailing Wage, and CW-1 programs. The only actor covering all five non-H-1B OFLC programs in one normalized schema. ### What This Actor Does The DOL publishes quarterly XLSX disclosure files at the [OFLC performance disclosure index](https://www.dol.gov/agencies/eta/foreign-labor/performance). This actor: 1. Fetches the index page to auto-discover all available quarterly files per program 2. Filters by your requested programs, fiscal year, and quarter 3. Downloads each XLSX directly from dol.gov (0.5 MB CW-1 to ~120 MB Prevailing Wage) 4. Stream-parses every row with per-program column mapping 5. Outputs a flat normalized dataset No authentication, proxy, or captcha required — all data is publicly available. ### Use Cases - **Immigration attorneys**: track petition outcomes across H-2A/H-2B/PERM by employer or state - **Agricultural staffing**: monitor seasonal H-2A approvals by region - **Wage benchmarking**: compare offered wages against prevailing wage determinations - **Compliance research**: analyze denial patterns by program, industry, or state - **Policy research**: longitudinal trends across OFLC programs and fiscal years ### Programs | Program | Description | File size | |---------|-------------|-----------| | H-2A | Agricultural temporary workers | ~16 MB/quarter | | H-2B | Non-agricultural seasonal workers | ~66 MB/quarter | | PERM | Permanent labor certification | ~36 MB/quarter | | PW | Prevailing Wage determinations | ~120 MB/quarter | | CW-1 | CNMI transitional workers | ~0.5 MB/quarter | ### Input | Field | Type | Description | |-------|------|-------------| | `programs` | array | Programs: H-2A, H-2B, PERM, PW, CW-1. Empty = all. | | `fiscalYear` | integer | Fiscal year (e.g. 2026). 0 = auto-detect latest. | | `fiscalQuarter` | string | Q1/Q2/Q3/Q4. Empty = auto-detect latest. | | `worksiteState` | string | Filter by worksite state (e.g. CA). | | `employerName` | string | Filter by employer name substring. | | `caseStatus` | string | Filter by case status (Certified, Denied, Withdrawn). | | `maxItems` | integer | Max records (0 = no limit). | ### Output Each record includes: program, case_number, case_status, received_date, decision_date, employer_name, employer_city, employer_state, employer_fein, job_title, soc_code, soc_title, worksite_city, worksite_state, num_workers_requested, num_workers_certified, wage_offer, wage_unit, prevailing_wage, period_of_employment_start, period_of_employment_end, attorney_agent_name, fiscal_year, fiscal_quarter, source_file. ### Notes on Large Files The Prevailing Wage (PW) file is ~120 MB with ~1 million rows. Use state/employer filters or maxItems to manage volume. The actor streams rows without loading the full file into memory. Default memory: 1024 MB. DOL publishes new data quarterly: Q1 (Oct-Dec) around February, Q2 (Jan-Mar) around May, Q3 (Apr-Jun) around August, Q4 (Jul-Sep) around November. # 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. ## `maxItems` (type: `integer`): Maximum number of records to return across all selected files. 0 = unlimited. ## `programs` (type: `array`): Programs to include. Valid values: H-2A, H-2B, PERM, PW, CW-1. Leave empty to include all programs. ## `fiscalYear` (type: `integer`): Filter to a specific fiscal year (e.g. 2026). Leave empty to auto-select the latest available quarter per program. ## `fiscalQuarter` (type: `string`): Filter to a specific fiscal quarter: Q1, Q2, Q3, or Q4. Leave empty to auto-select the latest. ## `worksiteState` (type: `string`): Filter records to this US state code (e.g. "CA", "TX"). Leave empty for all states. ## `employerName` (type: `string`): Filter to records whose employer name contains this string (case-insensitive). ## `caseStatus` (type: `string`): Filter to a specific case status (e.g. "Certified", "Denied"). Leave empty for all statuses. ## 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...", "maxItems": 100, "programs": [] } ```` # 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...", "maxItems": 100, "programs": [] }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/dol-oflc-foreign-labor-disclosure-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...", "maxItems": 100, "programs": [], } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/dol-oflc-foreign-labor-disclosure-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...", "maxItems": 100, "programs": [] }' | apify call jungle_synthesizer/dol-oflc-foreign-labor-disclosure-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/dol-oflc-foreign-labor-disclosure-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "DOL OFLC Foreign Labor Disclosure Scraper", "description": "Extract H-2A, H-2B, PERM, Prevailing Wage, and CW-1 disclosure data from DOL OFLC quarterly XLSX files. Covers all non-H-1B foreign labor programs in one normalized schema with per-program filtering.", "version": "0.1", "x-build-id": "h4danv7UBcQ8r6WT8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~dol-oflc-foreign-labor-disclosure-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-dol-oflc-foreign-labor-disclosure-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~dol-oflc-foreign-labor-disclosure-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-dol-oflc-foreign-labor-disclosure-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~dol-oflc-foreign-labor-disclosure-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-dol-oflc-foreign-labor-disclosure-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": [ "maxItems" ], "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." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return across all selected files. 0 = unlimited." }, "programs": { "title": "Programs", "type": "array", "description": "Programs to include. Valid values: H-2A, H-2B, PERM, PW, CW-1. Leave empty to include all programs.", "items": { "type": "string" } }, "fiscalYear": { "title": "Fiscal Year", "type": "integer", "description": "Filter to a specific fiscal year (e.g. 2026). Leave empty to auto-select the latest available quarter per program." }, "fiscalQuarter": { "title": "Fiscal Quarter", "type": "string", "description": "Filter to a specific fiscal quarter: Q1, Q2, Q3, or Q4. Leave empty to auto-select the latest." }, "worksiteState": { "title": "Worksite State", "type": "string", "description": "Filter records to this US state code (e.g. \"CA\", \"TX\"). Leave empty for all states." }, "employerName": { "title": "Employer Name", "type": "string", "description": "Filter to records whose employer name contains this string (case-insensitive)." }, "caseStatus": { "title": "Case Status", "type": "string", "description": "Filter to a specific case status (e.g. \"Certified\", \"Denied\"). Leave empty for all statuses." } } }, "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 } } } } } } } } } } ```