# New Job Posts Finder (`spartany/new-job-posts-finder`) Actor Pulls every fresher and entry-level tech job posted in the last 24 hours across Naukri, Indeed, LinkedIn, Internshala, Foundit, and Hirist into one clean, structured list. Set your role and location, run it once, and get everything worth applying to β€” no account needed, no manual searching. - **URL**: https://apify.com/spartany/new-job-posts-finder.md - **Developed by:** [Arnav Ignatius](https://apify.com/spartany) (community) - **Categories:** Jobs, Automation, Agents - **Stats:** 995 total users, 130 monthly users, 7.3% runs succeeded, 5 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.00005 / actor start 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 ## Indian Jobs Scraper Scrapes **fresher / fresh-graduate job listings** from six major Indian job portals simultaneously: - [LinkedIn](https://linkedin.com/jobs) - [Indeed India](https://in.indeed.com) - [Naukri](https://naukri.com) - [Internshala](https://internshala.com) - [Foundit (formerly Monster India)](https://foundit.in) - [Hirist](https://hirist.tech) Results are **deduplicated**, **zone-mapped** (Remote / South-1 / South-2 / West / North), and filtered to **0–1 yr experience** roles only. --- ### Features - πŸ” **Multi-keyword search** β€” search dozens of role titles in one run - πŸ—ΊοΈ **Zone mapping** β€” each job is tagged with its Indian geographic zone - 🧹 **Semantic deduplication** β€” same job posted on multiple platforms is merged into one record - πŸŽ“ **Fresher filter** β€” only jobs with 0–1 yr experience requirements are returned - πŸ“‚ **Category bucketing** β€” results grouped across Software Engineering, Data Analyst, Digital Marketing, Cloud & Cybersecurity --- ### Input | Field | Type | Default | Description | |---|---|---|---| | `scraperMode` | String (enum) | `deduplicated` | Which scraping strategy to use | | `keywords` | String | _(all)_ | Comma-separated job titles, e.g. `Software Engineer, Data Analyst` | | `location` | String | `India` | City or region to search in | | `maxJobsPerZone` | Integer | `0` (no limit) | Cap results per geographic zone | #### `scraperMode` values | Value | Description | |---|---| | `deduplicated` | All scrapers in parallel, semantically merged, zone-mapped (**recommended**) | | `all` | All scrapers in parallel, raw per-source results | | `linkedin` | LinkedIn only | | `indeed` | Indeed only | | `naukri` | Naukri only | | `internshala` | Internshala only | | `foundit` | Foundit only | | `hirist` | Hirist only | | `linkedin-posts` | LinkedIn feed posts (not job listings) | --- ### Output Each item in the dataset represents one job listing: | Field | Type | Description | |---|---|---| | `title` | String | Job title | | `company` | String | Company name | | `location` | String | City/region (comma-separated when merged) | | `link` | String | Direct URL to the job posting | | `source` | String | Platform the job was scraped from | | `keyword` | String | Matched keyword(s) | | `datePosted` | String | Date posted as reported by the source | --- ### Built-in Categories & Keywords When no keywords are specified, the Actor searches all built-in keywords across four categories: - **Software Engineering** β€” `Software Engineer`, `Frontend Developer`, `React Developer`, `Full Stack Developer`, and more - **Data Analyst** β€” `Data Analyst`, `Business Analyst`, `AI Engineer`, `ML Engineer`, and more - **Digital Marketing** β€” `SEO Executive`, `Social Media Manager`, `Content Writer`, and more - **Cloud Computing & Cybersecurity** β€” `Cloud Engineer`, `DevOps Engineer`, `Security Analyst`, and more --- ### Usage #### Via Apify Console Set the inputs in the auto-generated UI and click **Run**. #### Via API ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "scraperMode": "deduplicated", "keywords": "Software Engineer, Data Analyst", "location": "Bangalore" }' ```` #### Locally (with Apify CLI) ```bash npm install npx apify run ``` Input is read from `storage/key_value_stores/default/INPUT.json`.\ Output is written to `storage/datasets/default/`. #### Local Express API (development only) The original Express API is still available for local development: ```bash npm run start:api ## GET http://localhost:3000/scrape/deduplicated?keyword=Software+Engineer&location=Bangalore ``` # Actor input Schema ## `scraperMode` (type: `string`): Which scraping strategy to run. - **deduplicated** – All scrapers, semantically deduplicated and zone-mapped (recommended). - **all** – All scrapers, raw per-source results. - **linkedin-posts** – LinkedIn feed posts (not job listings). - Any individual source name runs only that scraper. ## `keywords` (type: `string`): Comma-separated job titles (e.g. `Software Engineer, Data Analyst`). Leave blank to use all built-in keywords across all categories. ## `location` (type: `string`): City or region to search in (e.g. `Bangalore`, `Mumbai`, `India`). Defaults to `India`. ## `maxJobsPerZone` (type: `integer`): Cap the number of jobs per geographic zone (Remote, South-1, South-2, West, North). Set to 0 for no limit. ## Actor input object example ```json { "scraperMode": "deduplicated", "location": "India", "maxJobsPerZone": 0 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("spartany/new-job-posts-finder").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("spartany/new-job-posts-finder").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call spartany/new-job-posts-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=spartany/new-job-posts-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "New Job Posts Finder", "description": "Pulls every fresher and entry-level tech job posted in the last 24 hours across Naukri, Indeed, LinkedIn, Internshala, Foundit, and Hirist into one clean, structured list. Set your role and location, run it once, and get everything worth applying to β€” no account needed, no manual searching.", "version": "0.0", "x-build-id": "tLS7XO3c1mnxUEbQE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/spartany~new-job-posts-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-spartany-new-job-posts-finder", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/spartany~new-job-posts-finder/runs": { "post": { "operationId": "runs-sync-spartany-new-job-posts-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/spartany~new-job-posts-finder/run-sync": { "post": { "operationId": "run-sync-spartany-new-job-posts-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "scraperMode": { "title": "Scraper mode", "enum": [ "deduplicated", "all", "linkedin", "indeed", "naukri", "internshala", "foundit", "hirist", "linkedin-posts" ], "type": "string", "description": "Which scraping strategy to run.\n\n- **deduplicated** – All scrapers, semantically deduplicated and zone-mapped (recommended).\n- **all** – All scrapers, raw per-source results.\n- **linkedin-posts** – LinkedIn feed posts (not job listings).\n- Any individual source name runs only that scraper.", "default": "deduplicated" }, "keywords": { "title": "Keywords", "type": "string", "description": "Comma-separated job titles (e.g. `Software Engineer, Data Analyst`). Leave blank to use all built-in keywords across all categories." }, "location": { "title": "Location", "type": "string", "description": "City or region to search in (e.g. `Bangalore`, `Mumbai`, `India`). Defaults to `India`.", "default": "India" }, "maxJobsPerZone": { "title": "Max jobs per zone", "minimum": 0, "type": "integer", "description": "Cap the number of jobs per geographic zone (Remote, South-1, South-2, West, North). Set to 0 for no limit.", "default": 0 } } }, "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 } } } } } } } } } } ```