# Glassdoor Scraper Pro – Reviews, Jobs & Salaries Extractor (`ahmed_jasarevic/glassdoor-scraper`) Actor Glassdoor Scraper Pro is a powerful Apify Actor built for reliable and large-scale extraction of Glassdoor reviews, jobs, and salary data — even behind aggressive Cloudflare and anti-bot protection. - **URL**: https://apify.com/ahmed\_jasarevic/glassdoor-scraper.md - **Developed by:** [Ahmed Jasarevic](https://apify.com/ahmed_jasarevic) (community) - **Categories:** Lead generation, Jobs, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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.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 ## Glassdoor Scraper Pro 🚀 A high-performance, production-ready Apify Actor designed to extract comprehensive data from Glassdoor.com while bypassing aggressive anti-bot protections. ### ✨ Key Features - **🛡️ Anti-Bot & Cloudflare Bypass**: Specialized Playwright Stealth engine. - **🍪 Automated Session Persistence (New!)**: Save your session once, and the Actor remembers it for next time! - **🛡️ Hidden Data Recovery**: Extracts "blurred" reviews and hidden text. - **📡 Hybrid Extraction Engine**: - **GraphQL Interception**: Captures high-fidelity JSON data directly from internal API calls. - **DOM Recovery**: Intelligent fallback that scrapes visible cards, including **Blurred/Hidden** review text. - **💾 Real-time Results**: Results appear in the dataset instantly as they are scraped. ### 🍪 Mandatory Cookie Setup (Cloud Success) To bypass Glassdoor's Cloudflare protection on the Apify Platform, you **must** provide fresh cookies from your own logged-in browser session. #### How to get your cookies: 1. Open Glassdoor in your browser and ensure you are logged in. 2. Use a browser extension like **"EditThisCookie"** or **"JSON Cookie"** to export your cookies as a JSON array. 3. Alternatively, open **Developer Tools (F12)** -> **Network** tab -> Refresh -> Right-click any request -> **Copy** -> **Copy as JSON**. 4. Paste the JSON array into the **`cookies`** input field in the Apify Console. > [!TIP] > You only need to provide cookies **once**! After the first successful run, the Actor will automatically save its session state. Subsequent runs will load this saved session from the Key-Value Store. ### ⚙️ Configuration | Field | Type | Description | | :--- | :--- | :--- | | `startUrls` | Array | List of Glassdoor URLs (Reviews, Jobs, etc.) | | `maxItems` | Number | Maximum items to collect per URL (Default: 100) | | `command` | String | Data type to target: `reviews`, `jobs`, `salaries` | | `cookies` | Array | Your session cookies (JSON format) | | `proxy` | Object | **MANDATORY**: Use Residential Proxy for Cloud runs. | ### 📦 Output Data is saved to `storage/datasets/default/`. Each record includes: - Review ID & Summary - Pros & Cons (Full Text) - Ratings (Overall & Sub-ratings) - Metadata (Date, Location, Job Title) - `_source`: Traceability for where the data was captured (GraphQL vs DOM) # Actor input Schema ## `startUrls` (type: `array`): List of Glassdoor company or job listing URLs. ## `command` (type: `string`): What data to scrape from the URLs. ## `maxItems` (type: `integer`): Maximum number of items to scrape from each input URL. ## `proxy` (type: `object`): Select proxies to be used. Residential recommended. ## `cookies` (type: `array`): Optional: Add cookies for an authenticated session. ## `includeAllReviews` (type: `boolean`): Include reviews in all available languages (eng, fra, por, spa, ita, nld, deu). ## `includeAllSalaries` (type: `boolean`): Include salaries in all available languages. ## `reviewsStartDate` (type: `string`): Filter reviews newer than this date (YYYY-MM-DD). ## `interviewsStartDate` (type: `string`): Filter interviews newer than this date (YYYY-MM-DD). ## `benefitsStartDate` (type: `string`): Filter benefits newer than this date (YYYY-MM-DD). ## Actor input object example ```json { "startUrls": [ { "url": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm" } ], "command": "reviews", "maxItems": 100, "proxy": { "useApifyProxy": true }, "includeAllReviews": false, "includeAllSalaries": false } ```` # 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.glassdoor.com/Reviews/Google-Reviews-E9079.htm" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("ahmed_jasarevic/glassdoor-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.glassdoor.com/Reviews/Google-Reviews-E9079.htm" }] } # Run the Actor and wait for it to finish run = client.actor("ahmed_jasarevic/glassdoor-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.glassdoor.com/Reviews/Google-Reviews-E9079.htm" } ] }' | apify call ahmed_jasarevic/glassdoor-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ahmed_jasarevic/glassdoor-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Glassdoor Scraper Pro – Reviews, Jobs & Salaries Extractor", "description": "Glassdoor Scraper Pro is a powerful Apify Actor built for reliable and large-scale extraction of Glassdoor reviews, jobs, and salary data — even behind aggressive Cloudflare and anti-bot protection.", "version": "0.0", "x-build-id": "ZIgjdSulYcIvNO8dj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ahmed_jasarevic~glassdoor-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ahmed_jasarevic-glassdoor-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ahmed_jasarevic~glassdoor-scraper/runs": { "post": { "operationId": "runs-sync-ahmed_jasarevic-glassdoor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ahmed_jasarevic~glassdoor-scraper/run-sync": { "post": { "operationId": "run-sync-ahmed_jasarevic-glassdoor-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "command" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of Glassdoor company or job listing URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "command": { "title": "Command", "enum": [ "reviews", "jobs", "salaries", "interviews", "locations", "overview", "cultureDiversity", "benefits" ], "type": "string", "description": "What data to scrape from the URLs.", "default": "reviews" }, "maxItems": { "title": "Max items per URL", "minimum": 1, "type": "integer", "description": "Maximum number of items to scrape from each input URL.", "default": 100 }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used. Residential recommended.", "default": { "useApifyProxy": true } }, "cookies": { "title": "Cookies", "type": "array", "description": "Optional: Add cookies for an authenticated session." }, "includeAllReviews": { "title": "Include All Languages (Reviews)", "type": "boolean", "description": "Include reviews in all available languages (eng, fra, por, spa, ita, nld, deu).", "default": false }, "includeAllSalaries": { "title": "Include All Languages (Salaries)", "type": "boolean", "description": "Include salaries in all available languages.", "default": false }, "reviewsStartDate": { "title": "Reviews Start Date", "type": "string", "description": "Filter reviews newer than this date (YYYY-MM-DD)." }, "interviewsStartDate": { "title": "Interviews Start Date", "type": "string", "description": "Filter interviews newer than this date (YYYY-MM-DD)." }, "benefitsStartDate": { "title": "Benefits Start Date", "type": "string", "description": "Filter benefits newer than this date (YYYY-MM-DD)." } } }, "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 } } } } } } } } } } ```