# TheLadders Scraper (`lexis-solutions/theladders-scraper`) Actor Scrape TheLadders job listings with structured data — title, company, location, salary, employment type, skills & more. Ideal for job market research, recruitment intelligence & lead generation. - **URL**: https://apify.com/lexis-solutions/theladders-scraper.md - **Developed by:** [Lexis Solutions](https://apify.com/lexis-solutions) (community) - **Categories:** Jobs, Lead generation, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.90 / 1,000 listings 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 ## TheLadders Scraper ![banner](https://i.imgur.com/sBwRfwZ.png) TheLadders (theladders.com) is a job marketplace focused on professional roles. This actor collects structured job detail data from TheLadders search and listing pages. ### Introduction The TheLadders scraper starts from search, listing, or job URLs, goes through result pages, and extracts structured job detail data such as title, company, location, salary fields, employment type, job description, qualifications, responsibilities, benefits, and more. ### Use Cases - **Job market research**: Track openings, salary ranges, and hiring patterns for selected keywords. - **Recruitment intelligence**: Monitor companies, roles, and demand across target locations. - **Lead generation**: Build structured job datasets for outreach, enrichment, or sales workflows. - **Analytics pipelines**: Feed dashboards, warehousing, and labor market analysis systems. ### Input Provide the following fields: - `startUrls` (array, required): TheLadders search, listing, or job URLs. - `maxItems` (integer, optional): Maximum number of job detail items to extract per original URL. - `proxyConfiguration` (object, optional): Apify proxy settings. Notes: - If a `startUrl` is a search or listing URL, the actor paginates result pages and collects job detail pages. - If a `startUrl` is a job detail URL, the actor extracts that job page directly. - Pagination increments the `page` query parameter automatically: `page=1`, `page=2`, `page=3`, and so on. - Crawling stops per source URL when `maxItems` is reached. - Proxies are recommended for larger runs and better reliability. ### Input Examples **1) Start URLs** ```json { "startUrls": [ { "url": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design" }, { "url": "https://www.theladders.com/job/designer-interactive-apple-san-francisco-ca_86484693" } ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true } } ```` ### Output Each dataset item contains fields like: ```json { "url": "https://www.theladders.com/job/designer-interactive-apple-san-francisco-ca_86484693", "originalUrl": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design", "jobId": "86484693", "title": "Designer, Interactive", "companyName": "Apple", "companyWebsite": "", "companyLogo": "", "location": "San Francisco, CA, US", "city": "San Francisco", "state": "CA", "postalCode": "", "country": "US", "workplaceType": "Hybrid", "employmentType": "FULL_TIME", "salaryText": "$140,000 - $200,000", "salaryMin": 140000, "salaryMax": 200000, "salaryCurrency": "USD", "salaryUnit": "YEAR", "datePosted": "2026-04-10", "validThrough": "", "postedAtText": "4 days ago", "industry": "Technology", "experienceText": "5-7 years of experience", "qualifications": [], "responsibilities": [], "benefits": [], "skills": [], "applicantLocationRequirements": [], "directApply": false, "descriptionText": "Full job description text...", "metaDescription": "Meta description text..." } ``` The scraper paginates through listing results and stops when `maxItems` is reached per start URL or when no more result items are found. ### Why use the TheLadders Scraper? - **Focused**: Built specifically for TheLadders listing and job detail flows. - **Structured output**: Ready-to-use JSON records for automation and analysis. - **Per-URL limits**: `maxItems` is enforced per start URL. - **Pagination support**: Automatically follows `page` query increments. - **Apify-native**: Works with Apify datasets, request queue, and proxy config. ### FAQ - **How many jobs can it extract?**\ Controlled by `maxItems` per source URL. - **Do I need proxies?**\ Not always, but proxies are recommended for larger runs and stability. - **Can I start from a job detail URL?**\ Yes. The actor can extract supported TheLadders job detail pages directly. - **What if TheLadders changes their website structure?**\ The actor may require updates to keep extraction stable. ### Need to scrape other job platforms? Check out our other scrapers: - [Dice.com US Tech Jobs Scraper](https://apify.com/lexis-solutions/dice-com-jobs-scraper). - [Reed.co.uk Scraper](https://apify.com/lexis-solutions/reed-co-uk-scraper). - [Totaljobs Scraper](https://apify.com/lexis-solutions/totaljobs-scraper). - [Lever.co Scraper](https://apify.com/lexis-solutions/lever-co-scraper). *** **Need help or want a custom solution?** Lexis Solutions is a certified Apify Partner. We can help with custom data extraction projects. Contact us over [Email](mailto:scraping@lexis.solutions) or [LinkedIn](https://www.linkedin.com/company/lexis-solutions). ### Support Our Work If you're happy with our work and scrapers, you're welcome to leave us a company review [here](https://apify.com/partners/find/lexis-solutions/review) and leave a review for the scrapers you're subscribed to. ### Image Credit Image credit: theladders.com. # Actor input Schema ## `startUrls` (type: `array`): Listing or job URLs to start with. ## `maxItems` (type: `integer`): Maximum number of scraped job detail items per original URL. ## `proxyConfiguration` (type: `object`): Your proxy configuration from Apify. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design" } ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": 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 = { "startUrls": [ { "url": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("lexis-solutions/theladders-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 = { "startUrls": [{ "url": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design" }] } # Run the Actor and wait for it to finish run = client.actor("lexis-solutions/theladders-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 '{ "startUrls": [ { "url": "https://www.theladders.com/jobs/searchresults-jobs?keywords=design" } ] }' | apify call lexis-solutions/theladders-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lexis-solutions/theladders-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TheLadders Scraper", "description": "Scrape TheLadders job listings with structured data — title, company, location, salary, employment type, skills & more. Ideal for job market research, recruitment intelligence & lead generation.", "version": "1.0", "x-build-id": "6DSix78zapyGs41Ao" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lexis-solutions~theladders-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lexis-solutions-theladders-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lexis-solutions~theladders-scraper/runs": { "post": { "operationId": "runs-sync-lexis-solutions-theladders-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lexis-solutions~theladders-scraper/run-sync": { "post": { "operationId": "run-sync-lexis-solutions-theladders-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls", "maxItems" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "Listing or job URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Maximum number of items", "type": "integer", "description": "Maximum number of scraped job detail items per original URL.", "default": 10 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Your proxy configuration from Apify.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```