# Infobip Jobinfo Parser Spider (`getdataforme/infobip-jobinfo-parser-spider`) Actor The Infobip Jobinfo Parser Spider is a web scraping tool for extracting detailed job information from Infobip's careers site. It captures comprehensive data like titles, descriptions, and locations with high accuracy and efficiency.... - **URL**: https://apify.com/getdataforme/infobip-jobinfo-parser-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 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 --- ## Infobip Jobinfo Parser Spider ### Introduction The Infobip Jobinfo Parser Spider is a powerful web scraping tool designed to extract detailed job information from the Infobip careers website. It provides comprehensive data on job listings, including titles, descriptions, locations, and more, enabling users to gain valuable insights into career opportunities at Infobip. ### Features - **Comprehensive Data Extraction**: Captures all relevant job details such as title, description, location, and posting date. - **High-Quality Data**: Ensures data accuracy and reliability for informed decision-making. - **Flexible Configuration**: Allows users to set specific parameters like the number of jobs to extract. - **Efficient Performance**: Optimized for speed and efficiency in data retrieval. - **User-Friendly Interface**: Easy setup and execution through the Apify platform. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-----------------------------------------------------------------------------|----------------------------------| | URLs | Array | Yes | List of Infobip job listing URLs to scrape. | `["https://careers.infobip.com/en/job-listing"]` | | MaxItems | Number | No | Maximum number of job listings to extract. Default is all available listings.| `5` | ### Example Usage #### Input JSON ```json { "urls": ["https://careers.infobip.com/en/job-listing"], "maxItems": 2 } ```` #### Output JSON ```json [ { "id": "0ef629ee53b210019d0d3bdb91ed0000", "title": "Product Success Manager", "job_description": "Working at Infobip means being part of something truly global...", "location": "Zagreb (Croatia)", "additional_locations": [ "Split (Croatia)", "Rijeka (Croatia)" ], "posted_on": "Posted 10 Days Ago", "start_date": "2026-05-08", "time_type": "Full time", "job_req_id": "JR104456", "job_posting_id": "Senior-Product-Success-Manager_JR104456", "job_posting_site_id": "InfobipCareers", "country": "Croatia", "remote_type": "Hybrid", "external_url": "https://infobip.wd3.myworkdayjobs.com/InfobipCareers/job/Zagreb-Croatia/Senior-Product-Success-Manager_JR104456", "questionnaire_id": "635190ae3aee1001eb0cf3d287540000", "company": "Infobip BiH", "actor_id": "LkcAwPHCHEI1gLczF", "run_id": "EsTHu2d7av6kS1css" }, { "id": "0ef629ee53b210019d0d3bdb91ed0001", "title": "Another Job Title", "job_description": "Job description for another job...", "location": "Another Location", "posted_on": "Posted 5 Days Ago", "start_date": "2026-06-01", "time_type": "Part time", "job_req_id": "JR104457", "job_posting_id": "Another-Job-Posting-ID_JR104457", "job_posting_site_id": "InfobipCareers", "country": "Another Country", "remote_type": "Remote", "external_url": "https://infobip.wd3.myworkdayjobs.com/InfobipCareers/job/Another-Location/Another-Job-Title_JR104457", "questionnaire_id": "635190ae3aee1001eb0cf3d287540001", "company": "Infobip Another", "actor_id": "LkcAwPHCHEI1gLczF", "run_id": "EsTHu2d7av6kS1css" } ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into Infobip's job market trends. - **Competitive Intelligence**: Understand Infobip's hiring strategies and growth areas. - **Price Monitoring**: Track salary ranges and benefits offered by Infobip. - **Content Aggregation**: Compile comprehensive reports on career opportunities at Infobip. - **Academic Research**: Use data for studies related to employment trends in the tech industry. - **Business Automation**: Integrate job data into HR systems for streamlined recruitment processes. ### Installation and Usage 1. Search for "Infobip Jobinfo Parser Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 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 data is structured as an array of job objects, each containing fields such as `id`, `title`, `job_description`, `location`, `posted_on`, `start_date`, `time_type`, `job_req_id`, `job_posting_id`, `job_posting_site_id`, `country`, `remote_type`, `external_url`, `questionnaire_id`, `company`, `actor_id`, and `run_id`. This format ensures comprehensive coverage of job details for analysis. ### 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! *** # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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("getdataforme/infobip-jobinfo-parser-spider").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 = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/infobip-jobinfo-parser-spider").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 '{}' | apify call getdataforme/infobip-jobinfo-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/infobip-jobinfo-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Infobip Jobinfo Parser Spider", "description": "The Infobip Jobinfo Parser Spider is a web scraping tool for extracting detailed job information from Infobip's careers site. It captures comprehensive data like titles, descriptions, and locations with high accuracy and efficiency....", "version": "0.0", "x-build-id": "YoDGM88qXPzyHLVIN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~infobip-jobinfo-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-infobip-jobinfo-parser-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~infobip-jobinfo-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-infobip-jobinfo-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~infobip-jobinfo-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-infobip-jobinfo-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```