# Naukri Jobs Scraper (`gio21/naukri-jobs-scraper`) Actor Scrape Naukri.com (India's largest job portal) listings by keyword and location. Returns job title, company, salary range, experience required, location, skills, and posting date. Useful for recruitment intelligence, salary benchmarking, and India market analysis. - **URL**: https://apify.com/gio21/naukri-jobs-scraper.md - **Developed by:** [Gio](https://apify.com/gio21) (community) - **Categories:** E-commerce, Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 job scrapeds 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 ## Naukri Jobs Scraper Scrape Naukri.com (India's largest job portal) listings by keyword and location. Returns job title, company, salary, experience required, location, skills, and posting date. Useful for **recruitment intelligence**, **salary benchmarking**, **skills gap analysis**, and **India market research**. ### Free vs. paid - **Free plan:** 15 clearly-labelled mock jobs (so you can inspect the output shape). - **Paid plan:** real, live Naukri data. ### Input | Field | Type | Description | |-------|------|-------------| | `searchTerm` | String (required) | Job role keyword. | | `location` | String | City or region (`bangalore`, `mumbai`, etc.). Empty = India-wide. | | `maxItems` | Integer | Default 100, max 2000. | | `debug` | Boolean | Verbose logs. | ### Output ```json { "jobId": "010125000123", "title": "Software Engineer - Backend", "url": "https://www.naukri.com/job-listings-...", "company": "Acme Tech Pvt Ltd", "companyRating": "3.8", "experience": "3-6 Yrs", "salary": "12-18 LPA", "location": "Bangalore", "postedDate": "2 days ago", "skills": ["Java", "Spring Boot", "AWS"], "description": "We are looking for..." } ```` ### Pricing Billed **per job returned** ($0.010/job). The Indian recruitment market reports ~6-12M active job seekers monthly; useful for HR tech, salary surveys, and competitor monitoring. ### How fast? Naukri pages render ~3-5s with Playwright. 20 jobs/page. 100 jobs ≈ 30-60 seconds. ### Limitations - Naukri uses dynamic React rendering, so this actor uses Playwright (4GB RAM, slower than HTTP-only actors). - Naukri's selectors change occasionally. The actor tries multiple selector variants to stay resilient. If this actor helped you, please leave a review on the Apify Store. # Actor input Schema ## `searchTerm` (type: `string`): Job role keyword (e.g. 'software engineer', 'data analyst', 'product manager'). ## `location` (type: `string`): City or region (e.g. 'bangalore', 'mumbai', 'delhi'). Leave empty for India-wide. ## `maxItems` (type: `integer`): Maximum number of jobs to return. ## `debug` (type: `boolean`): Enable verbose logging. ## Actor input object example ```json { "searchTerm": "software engineer", "maxItems": 100, "debug": false } ``` # Actor output Schema ## `results` (type: `string`): Full job record per Naukri listing: jobId, title, company, companyRating, experience, salary, location, skills, description, postedDate, url. # 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 = { "searchTerm": "software engineer", "location": "", "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("gio21/naukri-jobs-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 = { "searchTerm": "software engineer", "location": "", "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("gio21/naukri-jobs-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 '{ "searchTerm": "software engineer", "location": "", "maxItems": 100 }' | apify call gio21/naukri-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gio21/naukri-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Naukri Jobs Scraper", "description": "Scrape Naukri.com (India's largest job portal) listings by keyword and location. Returns job title, company, salary range, experience required, location, skills, and posting date. Useful for recruitment intelligence, salary benchmarking, and India market analysis.", "version": "0.0", "x-build-id": "Ty3oUH35WVMX8coGa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gio21~naukri-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gio21-naukri-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gio21~naukri-jobs-scraper/runs": { "post": { "operationId": "runs-sync-gio21-naukri-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gio21~naukri-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-gio21-naukri-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchTerm" ], "properties": { "searchTerm": { "title": "Job keyword", "type": "string", "description": "Job role keyword (e.g. 'software engineer', 'data analyst', 'product manager')." }, "location": { "title": "Location", "type": "string", "description": "City or region (e.g. 'bangalore', 'mumbai', 'delhi'). Leave empty for India-wide." }, "maxItems": { "title": "Max jobs", "minimum": 10, "maximum": 2000, "type": "integer", "description": "Maximum number of jobs to return.", "default": 100 }, "debug": { "title": "Debug logs", "type": "boolean", "description": "Enable verbose logging.", "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 } } } } } } } } } } ```