# Naukri Job Scraper (Pay-Per-Event) (`prodiger/naukri-scraper`) Actor Pay-per-event Naukri.com job scraper. Returns jobId, title, company, rating/reviews, location, work mode, experience, salary (parsed min/max), skills, description, posted date, and direct URLs. Batch keywords × locations in one run. Cheaper drop-in for automation-lab/naukri-scraper. - **URL**: https://apify.com/prodiger/naukri-scraper.md - **Developed by:** [Arnas](https://apify.com/prodiger) (community) - **Categories:** Jobs - **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 ## Naukri Job Scraper Scrape **job listings from Naukri.com** — India's largest job portal — by keyword and city. Returns the job title, company, AmbitionBox rating, location, work mode, experience band, parsed salary, skills, description snippet, posted date, and direct URLs. **Pay-per-event pricing, cheaper than the reference actor**, with run-level deduplication and batch keyword × location search. Built to run on the [Apify platform](https://apify.com): scheduling, API access, integrations, residential proxy rotation, and monitoring out of the box. ### What does Naukri Job Scraper do? Given one or more **keywords** (job title, skill, or technology) and optional **cities**, the actor searches [Naukri.com](https://www.naukri.com) and extracts structured data for every matching job. It drives a real browser through Apify's residential proxies — Naukri's job API is reCAPTCHA-gated, so the actor renders each search-results page and parses it, paginating automatically until your `maxJobs` limit is reached. Each keyword is combined with each location, so a single run can cover, say, `["java developer", "data scientist"]` across `["bangalore", "mumbai", "remote"]` in one go. ### Why use Naukri Job Scraper? - **Recruitment & sourcing** — build candidate-facing job boards or track which skills employers are hiring for. - **Market & salary research** — analyze experience bands, disclosed salaries, and skill demand by city. - **Competitive hiring intelligence** — monitor which companies are hiring for which roles, and how fresh the postings are. - **Lead generation** — surface hiring companies with their AmbitionBox ratings and review counts. ### How to use Naukri Job Scraper 1. Enter one or more **keywords** (e.g. `python developer`). 2. Optionally add **locations** (e.g. `bangalore`, `mumbai`, `remote`). Leave empty to search all of India. 3. Set **Max jobs per search**, and optionally filter by experience, minimum salary, work mode, or sort by date. 4. Keep the proxy on **Residential** (recommended — Naukri blocks datacenter IPs). 5. Run the actor and download the results as JSON, CSV, Excel, or HTML. ### Input | Field | Type | Description | | --------------------------------- | --------------- | --------------------------------------------------------------------------------------- | | `keyword` | string \| array | Job title / skill to search. Required. | | `location` | string \| array | Cities to filter by. Optional (defaults to all India). | | `maxJobs` | integer | Max unique jobs per (keyword × location). Default 100, max 5000. | | `experienceMin` / `experienceMax` | integer | Filter by years of experience. Optional. | | `salaryMin` | integer | Minimum disclosed salary in INR lakhs/year. Undisclosed-salary jobs are kept. Optional. | | `workMode` | enum | `any`, `remote`, `hybrid`, or `office`. | | `sortBy` | enum | `relevance` (default) or `date` (freshest first). | | `proxyConfiguration` | object | Apify proxy (Residential recommended). | ### Output One record per unique `jobId`. Example: ```json { "jobId": "150126031660", "jobUrl": "https://www.naukri.com/job-listings-python-developer-infosys-kolkata-150126031660", "title": "Python Developer", "companyName": "Infosys", "companyUrl": "https://www.naukri.com/infosys-jobs-careers-11244", "companyLogoUrl": "https://img.naukimg.com/logo_images/groups/v1/13832.gif", "companyRating": 3.5, "companyReviewsCount": 49204, "ambitionBoxUrl": "https://www.ambitionbox.com/reviews/infosys-reviews", "location": "Kolkata, Hyderabad, Bengaluru", "workMode": "Hybrid", "isRemote": false, "isHybrid": true, "experienceText": "5-10 Yrs", "experienceMin": 5, "experienceMax": 10, "salary": "₹ 10-15 Lacs PA", "salaryMin": 10, "salaryMax": 15, "salaryCurrency": "INR", "skills": ["Django", "Python", "Flask"], "skillsCount": 3, "jobDescription": "Educational Requirements MCA, BTech...", "postedDateRelative": "1 day ago", "postedDaysAgo": 1, "keyword": "python developer", "locationSearched": "bangalore", "searchUrl": "https://www.naukri.com/python-developer-jobs-in-bangalore", "scrapedAt": "2026-06-02T10:00:00.000Z" } ```` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. #### Data table | Field | Description | | -------------------------------------------------------- | -------------------------------------------------- | | `jobId`, `jobUrl` | Naukri job identifier and direct link | | `title`, `companyName`, `companyUrl`, `companyLogoUrl` | Role and company identity | | `companyRating`, `companyReviewsCount`, `ambitionBoxUrl` | AmbitionBox employer signals | | `location`, `workMode`, `isRemote`, `isHybrid` | Where and how the role is worked | | `experienceText`, `experienceMin`, `experienceMax` | Required experience (raw + parsed band) | | `salary`, `salaryMin`, `salaryMax`, `salaryCurrency` | Compensation (raw + parsed; null when undisclosed) | | `skills`, `skillsCount` | Required skills | | `jobDescription` | Description snippet from the listing | | `postedDateRelative`, `postedDaysAgo` | When the job was posted (relative + numeric days) | | `keyword`, `locationSearched`, `searchUrl`, `scrapedAt` | Search provenance | ### How much does it cost to scrape Naukri? Pay-per-event: **$0.001 per run start + $0.002 per job scraped** (deduplicated by `jobId`). Scraping 1,000 jobs costs about **$2.00**. Jobs are billed only after they are written to your dataset — you never pay for results you can't see. ### Tips - Use the **`date` sort** plus a small `maxJobs` for a fast "what's new" feed. - Combine several keywords and cities in one run — deduplication by `jobId` means overlapping searches never double-bill you. - If you see challenge pages in the log, raise **Max request retries** and keep the proxy on Residential; an India proxy country can also help. ### FAQ, disclaimers, and support - **Is scraping Naukri legal?** This actor collects only publicly available job listings. You are responsible for complying with Naukri's Terms of Service and applicable laws, and for how you use the data. - **Why are some salaries null?** Many Naukri listings mark salary "Not disclosed"; those rows carry `null` salary fields. - **Why are `postedDate`, `applyByDate`, and `vacancy` null?** Those live on the individual job-detail page; v0.1 reads only the search-results page. Detail enrichment is planned for v0.2. - **Found a bug or need a custom field?** Open an issue on the actor's Issues tab. # Actor input Schema ## `keyword` (type: `array`): Job title, skill, or technology to search. Each keyword runs a separate search. Examples: 'java developer', 'data scientist', 'product manager'. ## `location` (type: `array`): Cities to filter by (e.g. 'bangalore', 'mumbai', 'delhi', 'hyderabad', 'pune', 'remote'). Leave empty to search all of India. Each location is combined with each keyword. ## `maxJobs` (type: `integer`): Maximum unique jobs to return per (keyword × location) search. Naukri returns ~20 jobs per result page. ## `experienceMin` (type: `integer`): Only return jobs whose experience band includes at least this many years. Leave empty for no minimum. ## `experienceMax` (type: `integer`): Only return jobs whose experience band is at or below this many years. Leave empty for no maximum. ## `salaryMin` (type: `integer`): Only return jobs whose disclosed upper salary (in INR lakhs per annum) is at least this value. Jobs with undisclosed salary are kept. Leave empty for no filter. ## `workMode` (type: `string`): Filter by work arrangement. ## `sortBy` (type: `string`): Result ordering. 'relevance' is Naukri's default; 'date' surfaces the freshest postings first. ## `maxRequestRetries` (type: `integer`): Retry budget per page for blocks and challenge pages. Sessions rotate on each failure, so higher values improve completion on residential proxies. ## `proxyConfiguration` (type: `object`): Apify proxy. RESIDENTIAL is strongly recommended — Naukri blocks datacenter IPs. Leaving the default keeps you on RESIDENTIAL. ## Actor input object example ```json { "keyword": [ "java developer" ], "maxJobs": 100, "workMode": "any", "sortBy": "relevance", "maxRequestRetries": 3, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `dataset` (type: `string`): Scraped Naukri jobs. One record per unique jobId across the run. # 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 = { "keyword": [ "java developer" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("prodiger/naukri-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 = { "keyword": ["java developer"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("prodiger/naukri-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 '{ "keyword": [ "java developer" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call prodiger/naukri-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=prodiger/naukri-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Naukri Job Scraper (Pay-Per-Event)", "description": "Pay-per-event Naukri.com job scraper. Returns jobId, title, company, rating/reviews, location, work mode, experience, salary (parsed min/max), skills, description, posted date, and direct URLs. Batch keywords × locations in one run. Cheaper drop-in for automation-lab/naukri-scraper.", "version": "0.1", "x-build-id": "PmCQ0RHygyYuW6jIL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/prodiger~naukri-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-prodiger-naukri-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/prodiger~naukri-scraper/runs": { "post": { "operationId": "runs-sync-prodiger-naukri-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/prodiger~naukri-scraper/run-sync": { "post": { "operationId": "run-sync-prodiger-naukri-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keyword": { "title": "Keywords", "type": "array", "description": "Job title, skill, or technology to search. Each keyword runs a separate search. Examples: 'java developer', 'data scientist', 'product manager'.", "items": { "type": "string" } }, "location": { "title": "Locations", "type": "array", "description": "Cities to filter by (e.g. 'bangalore', 'mumbai', 'delhi', 'hyderabad', 'pune', 'remote'). Leave empty to search all of India. Each location is combined with each keyword.", "items": { "type": "string" } }, "maxJobs": { "title": "Max jobs per search", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum unique jobs to return per (keyword × location) search. Naukri returns ~20 jobs per result page.", "default": 100 }, "experienceMin": { "title": "Minimum experience (years)", "minimum": 0, "maximum": 50, "type": "integer", "description": "Only return jobs whose experience band includes at least this many years. Leave empty for no minimum." }, "experienceMax": { "title": "Maximum experience (years)", "minimum": 0, "maximum": 50, "type": "integer", "description": "Only return jobs whose experience band is at or below this many years. Leave empty for no maximum." }, "salaryMin": { "title": "Minimum salary (INR lakhs/year)", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Only return jobs whose disclosed upper salary (in INR lakhs per annum) is at least this value. Jobs with undisclosed salary are kept. Leave empty for no filter." }, "workMode": { "title": "Work mode", "enum": [ "any", "remote", "hybrid", "office" ], "type": "string", "description": "Filter by work arrangement.", "default": "any" }, "sortBy": { "title": "Sort by", "enum": [ "relevance", "date" ], "type": "string", "description": "Result ordering. 'relevance' is Naukri's default; 'date' surfaces the freshest postings first.", "default": "relevance" }, "maxRequestRetries": { "title": "Max request retries", "minimum": 1, "maximum": 10, "type": "integer", "description": "Retry budget per page for blocks and challenge pages. Sessions rotate on each failure, so higher values improve completion on residential proxies.", "default": 3 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify proxy. RESIDENTIAL is strongly recommended — Naukri blocks datacenter IPs. Leaving the default keeps you on RESIDENTIAL.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```