# Belmeta.com Scraper (`unfenced-group/belmeta-scraper`) Actor Scrape job listings from Belmeta.com — Belarus's largest job board with 95,000+ vacancies. Filter by keyword, location, date. Structured salary output. - **URL**: https://apify.com/unfenced-group/belmeta-scraper.md - **Developed by:** [Unfenced Group](https://apify.com/unfenced-group) (community) - **Categories:** Jobs - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.49 / 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 ## Belmeta.com Scraper Extract job listings from [Belmeta.com](https://belmeta.com) — the largest job board in Belarus with 95,000+ active vacancies. ![Belmeta Scraper](https://i.imgur.com/4QJFZrj.png) ### Features - 🔍 **Keyword + location search** — filter by profession, company, city, or region - 📅 **Date range filter** — limit to last 24 hours, 3 days, or 7 days - 📋 **Full job details** — description, employment type, experience, schedule - 💰 **Structured salary data** — BYN values as numeric fields, no regex needed - 🔁 **Cross-run deduplication** — skip already-seen jobs (90-day TTL) - 🔗 **Start URL support** — scrape any Belmeta search or job detail URL ### Input | Field | Type | Description | |-------|------|-------------| | `keyword` | string | Job title, profession, or company (e.g. `программист`) | | `location` | string | City or region (e.g. `Минск`, `Гродно`) | | `dateRange` | select | `24 часа` / `3 дня` / `7 дней` / all time | | `maxItems` | integer | Max results to return (default: 100) | | `fetchDetails` | boolean | Fetch detail page for description & extra fields (default: true) | | `skipDuplicates` | boolean | Skip job IDs seen in prior runs within 90 days (default: true) | | `startUrls` | array | Optional Belmeta search or job detail URLs to scrape | ### Output Each item in the dataset represents one job listing: ```json { "jobId": "14957553", "title": "Программист 1С", "company": "ООО ТехноМир", "location": "Беларусь, Минск", "employmentType": "Полная занятость", "schedule": "Стандартный график", "experience": "От 1 года до 3 лет", "salary": "от 2500 до 3500 BYN", "salaryMin": 2500, "salaryMax": 3500, "salaryCurrency": "BYN", "salaryPeriod": null, "description": "Разработка и поддержка конфигураций 1С...", "snippet": "Требуется опытный программист 1С...", "quickApply": false, "publishedAt": "2026-04-09", "applyUrl": "https://belmeta.com/redir?id=14957553", "url": "https://belmeta.com/redir?id=14957553", "scrapedAt": "2026-04-09T10:00:00.000Z" } ```` #### Output fields | Field | Type | Description | |-------|------|-------------| | `jobId` | string | Belmeta internal job ID | | `title` | string | Job title | | `company` | string | Employer name | | `location` | string | City/address from job detail | | `employmentType` | string | Employment type (Полная/Частичная занятость, etc.) | | `schedule` | string | Work schedule | | `experience` | string | Required experience | | `salary` | string | Raw salary string as displayed | | `salaryMin` | number|null | Minimum salary (numeric) | | `salaryMax` | number|null | Maximum salary (numeric) | | `salaryCurrency` | string|null | `BYN` | | `salaryPeriod` | string|null | `monthly`/`hourly`/`yearly`/null | | `description` | string|null | Full job description (requires `fetchDetails: true`) | | `snippet` | string | Short preview from listing page | | `quickApply` | boolean | Whether quick-apply is available | | `publishedAt` | string | Publication date (YYYY-MM-DD) | | `applyUrl` | string | Link to apply / view on Belmeta | | `url` | string | Job URL | | `scrapedAt` | string | ISO timestamp of scrape | #### 💰 Structured salary data — machine-ready Salary is returned as numeric fields — no regex required on your end: | Field | Type | Example | |-------|------|---------| | `salaryMin` | number|null | `2500` | | `salaryMax` | number|null | `3500` | | `salaryCurrency` | string|null | `"BYN"` | | `salaryPeriod` | string|null | `null` | Most competing scrapers return salary as a raw string (e.g. `"от 2 500 до 3 500 BYN"`), leaving the parsing to you. This scraper delivers numeric fields directly — ready for `WHERE salaryMin > 2000` queries or salary distribution charts. ### Performance - \~20 jobs per listing page - With `fetchDetails: true`: ~1.5–2 req/s (rate-limited to stay polite) - With `fetchDetails: false`: ~5–10 pages/s (listing only, no detail fetching) - 95,000+ total jobs indexed on Belmeta.com ### Pricing **$1.49 per 1,000 results.** ### Notes - Belmeta.com is a Russian-language Belarusian job board. Job titles and descriptions are in Russian. - Currency is BYN (Belarusian ruble). Some older listings may show BYR (pre-2016 denomination) — treated as BYN. - `quickApply` (Быстрый отклик) listings allow one-click application through Belmeta. # Actor input Schema ## `keyword` (type: `string`): Job title, profession, or company name to search for. ## `location` (type: `string`): City or region to filter by (e.g. Минск, Гродно). ## `dateRange` (type: `string`): Filter jobs by posting date. ## `maxItems` (type: `integer`): Maximum number of job listings to return. ## `fetchDetails` (type: `boolean`): When enabled, visits each job's detail page to retrieve description, experience, employment type and schedule. Disable for faster, listing-only results. ## `skipDuplicates` (type: `boolean`): Skip job IDs seen in previous runs within 90 days. ## `startUrls` (type: `array`): Optional list of Belmeta.com search or job detail URLs to scrape instead of using the keyword/location inputs. ## Actor input object example ```json { "keyword": "программист", "location": "Минск", "dateRange": "", "maxItems": 100, "fetchDetails": true, "skipDuplicates": true } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("unfenced-group/belmeta-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 = {} # Run the Actor and wait for it to finish run = client.actor("unfenced-group/belmeta-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 '{}' | apify call unfenced-group/belmeta-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=unfenced-group/belmeta-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Belmeta.com Scraper", "description": "Scrape job listings from Belmeta.com — Belarus's largest job board with 95,000+ vacancies. Filter by keyword, location, date. Structured salary output.", "version": "0.0", "x-build-id": "pqQqW1w2ZPcL8aoSF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/unfenced-group~belmeta-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-unfenced-group-belmeta-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/unfenced-group~belmeta-scraper/runs": { "post": { "operationId": "runs-sync-unfenced-group-belmeta-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/unfenced-group~belmeta-scraper/run-sync": { "post": { "operationId": "run-sync-unfenced-group-belmeta-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Search keyword", "type": "string", "description": "Job title, profession, or company name to search for." }, "location": { "title": "Location", "type": "string", "description": "City or region to filter by (e.g. Минск, Гродно)." }, "dateRange": { "title": "Date range", "enum": [ "", "24 часа", "3 дня", "7 дней" ], "type": "string", "description": "Filter jobs by posting date.", "default": "" }, "maxItems": { "title": "Max results", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of job listings to return.", "default": 100 }, "fetchDetails": { "title": "Fetch job details", "type": "boolean", "description": "When enabled, visits each job's detail page to retrieve description, experience, employment type and schedule. Disable for faster, listing-only results.", "default": true }, "skipDuplicates": { "title": "Skip duplicates (cross-run)", "type": "boolean", "description": "Skip job IDs seen in previous runs within 90 days.", "default": true }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Optional list of Belmeta.com search or job detail URLs to scrape instead of using the keyword/location inputs.", "items": { "type": "object" } } } }, "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 } } } } } } } } } } ```