# Apna Job Detail Scraper (`getdataforme/apna-job-detail-jb-scraper`) Actor Apna Job Detail Scraper is an Apify Actor designed to extract comprehensive job details from the Apna website, providing data on titles, salaries, locations, and more. It offers high-quality, accurate information for market research, competitive intelligence, and business automation.... - **URL**: https://apify.com/getdataforme/apna-job-detail-jb-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Jobs, Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## README.md ### Apna Job Detail Scraper #### Introduction Apna Job Detail Scraper is an Apify Actor designed to efficiently extract detailed job information from the Apna website. It provides comprehensive data on various job postings, including titles, locations, salaries, and more, enabling businesses and individuals to make informed decisions. #### Features - **Comprehensive Data Extraction**: Extracts detailed job information such as title, salary, location, and company details. - **High-Quality Data**: Ensures reliable and accurate data extraction for better decision-making. - **User-Friendly Setup**: Easy configuration with a simple input schema. - **Versatile Applications**: Suitable for market research, competitive intelligence, and more. - **Seamless Integration**: Outputs in multiple formats like JSON, CSV, and Excel. #### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|-------------------------------------------------------------------------| | startUrls | array | Yes | URLs to start with. These are the job listing pages from which data will be extracted. | `[{"url": "https://apna.co/job/new-delhi/personal-office-assistant-427011484"}]` | #### Example Usage ##### Input JSON ```json { "startUrls": [ { "url": "https://apna.co/job/noida/social-media-specialist-461489084" } ] } ```` ##### Output JSON ```json [ { "url": "https://apna.co/job/noida/social-media-specialist-461489084", "jobId": "461489084", "jobTitle": "Social Media Specialist", "organizationName": "Dr. J's HealthVitals LLP", "location": "Sector 61, Noida", "salaryRange": "₹20,000 - ₹28,000 monthly", "fixedSalary": "₹20,000 - ₹28,000", "earningPotential": "₹28,000", "workFrom": "Work from Office", "employmentType": "Full Time", "experience": "Min. 1 year", "englishLevel": "Good (Intermediate / Advanced) English", "jobDescription": "content writing , graphic designing & posting creatives on instagram & Facebook", "workLocation": "30, D Block Ln, near Dr. Kunal Das Clinic, Gautam Buddha Nagar, Block D, Sector 52, Noida, Uttar Pradesh, India", "department": "Marketing / Brand / Digital Marketing", "roleCategory": "Brand Marketing", "shift": "Day Shift", "education": "Graduate", "gender": "Any gender", "ageLimit": "", "jobPostedBy": "Dr. J's HealthVitals LLP", "jobHighlights": [ { "heading": "8 applicants", "description": "" } ], "uiTags": [ "Work from Office", "Full Time", "Min. 1 year", "Good (Intermediate / Advanced) English" ], "faqs": [ { "question": "How much salary can I expect as a Social Media Specialist in Dr. J's HealthVitals LLP in Delhi-NCR?", "answer": "You can expect a minimum salary of 20,000 INR and can go up to 28,000 INR. The salary offered will depend on your skills, experience and performance in the interview." }, { "question": "What is the eligibility criteria to apply for Social Media Specialist in Dr. J's HealthVitals LLP in Delhi-NCR?", "answer": "The candidate should have completed Graduate degree and people who have 1 to 31 years are eligible to apply for this job. You can apply for more jobs in Delhi-NCR to get hired quickly." }, { "question": "Is there any specific skill required for this job?", "answer": "The candidate should have Good (Intermediate / Advanced) English skills and sound communication skills for this job." }, { "question": "Who can apply for this job?", "answer": "Both Male and Female candidates can apply for this job." }, { "question": "Is it a work from home job?", "answer": "No, it's not a work from home job and can't be done online. You can explore and apply for other work from home jobs in Delhi-NCR at apna." }, { "question": "Are there any charges or deposits required while applying for the role or while joining?", "answer": "No work-related deposit needs to be made during your employment with the company." }, { "question": "How can I apply for this job?", "answer": "Go to the apna app and apply for this job. Click on the apply button and call HR directly to schedule your interview." }, { "question": "What is the last date to apply?", "answer": "The last date to apply for this job is 28 Jul 2026. For more details, download apna app and find Full Time jobs in Delhi-NCR . Through apna, you can find jobs in 64 cities across India. Join NOW!" } ], "similarJobs": [ { "title": "Digital Marketing Intern", "company": "Reva Graphics", "location": "", "salary": "", "tags": [ "Work from Office", "Full Time", "Any experience", "Basic English" ], "url": "https://apna.co/job/new-delhi/digital-marketing-intern-34462406" }, { "title": "E-Commerce Executive", "company": "Fabulous Home Decoration and Candels", "location": "", "salary": "", "tags": [ "Work from Office", "Full Time", "Min. 6 months", "Basic English" ], "url": "https://apna.co/job/new-delhi/e-commerce-executive-79424336" }, { "title": "Field Marketing Executive", "company": "Ushaprakash Health Care Private Limited", "location": "", "salary": "", "tags": [ "Field Job", "Full Time", "Any experience", "No English Required" ], "url": "https://apna.co/job/new-delhi/field-marketing-executive-156416604" }, { "title": "Digital Marketing Trainer", "company": "Edunova Technology", "location": "", "salary": "", "tags": [ "Work from Office", "Full Time", "Any experience", "Basic English" ], "url": "https://apna.co/job/new-delhi/digital-marketing-trainer-751468297" }, { "title": "Digital Marketing Executive", "company": "Acent India Technoart", "location": "", "salary": "", "tags": [ "Work from Office", "Full Time", "Any experience", "Basic English" ], "url": "https://apna.co/job/delhi-ncr/digital-marketing-executive-907277609" }, { "title": "E-Commerce Executive", "company": "Fabulous Home Decoration and Candels", "location": "", "salary": "", "tags": [ "Work from Office", "Full Time", "Min. 6 months", "Basic English" ], "url": "https://apna.co/job/new-delhi/e-commerce-executive-79424336" } ] } ] ``` #### Use Cases - **Market Research and Analysis**: Gather insights into job market trends. - **Competitive Intelligence**: Monitor competitor hiring strategies. - **Price Monitoring**: Track salary ranges across different sectors. - **Content Aggregation**: Compile job listings for newsletters or reports. - **Academic Research**: Support studies on employment patterns. - **Business Automation**: Integrate with HR systems for recruitment processes. #### Installation and Usage 1. Search for "Apna Job Detail Scraper" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters by providing the `startUrls`. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). #### Output Format The output is a JSON array where each object represents a job listing with fields such as: - **url**: The URL of the job posting. - **jobId**: Unique identifier for the job. - **jobTitle**: Title of the job position. - **organizationName**: Name of the hiring organization. - **location**: Job location. - **salaryRange**: Salary range offered. - **workFrom**: Work arrangement (e.g., office, remote). - **employmentType**: Type of employment (e.g., full-time, part-time). - **experience**: Required experience level. - **englishLevel**: English proficiency required. - **jobDescription**: Description of job responsibilities. #### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! *** ## Description Unlock comprehensive job insights with Apna Job Detail Scraper. Extract detailed job information, including titles, salaries, and locations, for market research, competitive intelligence, and more. Seamlessly integrate into your workflow and make informed decisions today! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## Actor input object example ```json { "startUrls": [ { "url": "https://apna.co/job/new-delhi/personal-office-assistant-427011484" } ] } ``` # 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 = { "startUrls": [ { "url": "https://apna.co/job/new-delhi/personal-office-assistant-427011484" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/apna-job-detail-jb-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://apna.co/job/new-delhi/personal-office-assistant-427011484" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/apna-job-detail-jb-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://apna.co/job/new-delhi/personal-office-assistant-427011484" } ] }' | apify call getdataforme/apna-job-detail-jb-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/apna-job-detail-jb-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apna Job Detail Scraper", "description": "Apna Job Detail Scraper is an Apify Actor designed to extract comprehensive job details from the Apna website, providing data on titles, salaries, locations, and more. It offers high-quality, accurate information for market research, competitive intelligence, and business automation....", "version": "0.0", "x-build-id": "jskUGBYbr24GJnWX1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~apna-job-detail-jb-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-apna-job-detail-jb-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~apna-job-detail-jb-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-apna-job-detail-jb-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~apna-job-detail-jb-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-apna-job-detail-jb-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```