# Prakse.lv Scraper (`unfenced-group/prakse-lv-scraper`) Actor Scrape job vacancies and internships from Prakse.lv, Latvia's leading student career platform. - **URL**: https://apify.com/unfenced-group/prakse-lv-scraper.md - **Developed by:** [Unfenced Group](https://apify.com/unfenced-group) (community) - **Categories:** Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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 ## Prakse.lv Scraper ![Prakse.lv Scraper](https://i.imgur.com/mQGLQkh.png) ![Prakse.lv Scraper](https://i.imgur.com/UdYMQi2.png) Extract job vacancies and internships from [Prakse.lv](https://www.prakse.lv), Latvia's leading career platform for students and young professionals. --- ### Features - Scrapes all active vacancies and internships from Prakse.lv - Filters by type: internship, regular job, or all - Full vacancy detail: description, requirements, duties, company offer - Salary extraction: net/gross, min/max, currency, period - Application deadline extraction - Cross-run deduplication (90-day TTL) — skip previously seen vacancies - Direct URL mode: supply specific vacancy URLs - Respects `robots.txt` --- ### Input | Parameter | Type | Default | Description | |---|---|---|---| | `jobType` | select | `all` | Filter by type: `all`, `internship`, or `work` | | `maxItems` | integer | `0` | Maximum results (0 = no limit) | | `daysOld` | integer | `0` | Filter by deadline within N days (0 = no filter) | | `fetchDetails` | boolean | `true` | Fetch full description from detail pages | | `skipReposts` | boolean | `false` | Skip vacancies seen in previous runs | | `startUrls` | array | `[]` | Specific vacancy URLs to scrape directly | --- ### Output Each result contains: | Field | Type | Description | |---|---|---| | `id` | string | Vacancy ID | | `url` | string | Vacancy page URL | | `title` | string | Vacancy title | | `companyName` | string | Employer name | | `companyUrl` | string | Employer profile URL | | `jobType` | string | `Internship` or `Work` | | `schedule` | string | `Part time` or `Full time` | | `deadline` | string | Application deadline (YYYY-MM-DD) | | `location` | string | City and country | | `salaryText` | string | Raw salary string | | `salaryMin` | number | Minimum salary | | `salaryMax` | number | Maximum salary | | `salaryCurrency` | string | Currency code (e.g. `EUR`) | | `salaryPeriod` | string | `MONTHLY`, `HOURLY`, etc. | | `salaryType` | string | `net` or `gross` | | `descriptionHtml` | string | Full description as HTML | | `descriptionText` | string | Full description as plain text | | `descriptionMarkdown` | string | Full description as Markdown | | `requirementsText` | string | Requirements section | | `dutiesText` | string | Duties section | | `proposalText` | string | Employer offer section | | `publishDate` | string | Scrape date (YYYY-MM-DD) | | `source` | string | `prakse.lv` | | `isRepost` | boolean | Whether seen in a previous run | | `contentHash` | string | 16-char MD5 for change detection | #### Example output ```json { "id": "176361", "url": "https://www.prakse.lv/vacancy/176361/rigas-tehniskas-universitates-attistibas-fonds/projektesanas-inzeniera-asistents", "title": "PROJEKTĒŠANAS INŽENIERA ASISTENTS", "companyName": "Rīgas Tehniskās universitātes Attīstības fonds", "jobType": "Internship", "schedule": "Part time", "deadline": "2026-05-10", "location": "Rīga, Latvia", "salaryMin": 500, "salaryMax": 500, "salaryCurrency": "EUR", "salaryPeriod": "MONTHLY", "salaryType": "net", "salaryText": "Salary(net): 500 EUR monthly", "descriptionText": "2 prakses vietas. Apmērs: 500 EUR (30 stundas nedēļā)...", "publishDate": "2026-04-24", "source": "prakse.lv", "isRepost": false, "contentHash": "a3f8c21d9b4e0712" } ```` *** ### Usage examples **Scrape all active vacancies:** ```json { "jobType": "all", "fetchDetails": true } ``` **Internships only:** ```json { "jobType": "internship", "fetchDetails": true } ``` **Daily feed (new listings only, skip reposts):** ```json { "skipReposts": true, "fetchDetails": true } ``` **Specific vacancy URLs:** ```json { "startUrls": [ { "url": "https://www.prakse.lv/vacancy/176361/rigas-tehniskas-universitates-attistibas-fonds/projektesanas-inzeniera-asistents" }, { "url": "https://www.prakse.lv/vacancy/176360/if-insurance-baltic-if-p-amp-c-insurance-as/sales-support-group-intern" } ] } ``` **Max 50 results:** ```json { "maxItems": 50, "fetchDetails": true } ``` *** ### Pricing **$1.49 per 1,000 results.** Prakse.lv is a small board (~200–400 active vacancies). A full scrape with detail pages typically costs under $0.50. *** ### Notes - Prakse.lv is a Latvian platform covering internships and entry-level jobs. Listings are in Latvian, English, and Russian. - `publishDate` reflects the scrape date — Prakse.lv does not expose the original posting date on list pages. - Salary is available on approximately 40–50% of listings. # Actor input Schema ## `jobType` (type: `string`): Filter by vacancy type: all vacancies, internships only, or regular jobs only. ## `maxItems` (type: `integer`): Maximum number of results to return. Set to 0 for no limit. ## `daysOld` (type: `integer`): Only return vacancies with a deadline within this many days from now. Set to 0 for no filter. ## `fetchDetails` (type: `boolean`): Fetch full vacancy description, requirements, duties and proposal from detail pages. Recommended: true. ## `skipReposts` (type: `boolean`): Skip vacancies already seen in previous runs (cross-run deduplication with 90-day TTL). ## `startUrls` (type: `array`): Optional list of specific prakse.lv vacancy URLs to scrape directly (e.g. https://www.prakse.lv/vacancy/176361/...). ## Actor input object example ```json { "jobType": "all", "maxItems": 0, "daysOld": 0, "fetchDetails": true, "skipReposts": false, "startUrls": [] } ``` # 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/prakse-lv-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/prakse-lv-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/prakse-lv-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=unfenced-group/prakse-lv-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Prakse.lv Scraper", "description": "Scrape job vacancies and internships from Prakse.lv, Latvia's leading student career platform.", "version": "0.0", "x-build-id": "cSf9vraBlog1HaGpT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/unfenced-group~prakse-lv-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-unfenced-group-prakse-lv-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/unfenced-group~prakse-lv-scraper/runs": { "post": { "operationId": "runs-sync-unfenced-group-prakse-lv-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/unfenced-group~prakse-lv-scraper/run-sync": { "post": { "operationId": "run-sync-unfenced-group-prakse-lv-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "jobType": { "title": "Job type", "enum": [ "all", "internship", "work" ], "type": "string", "description": "Filter by vacancy type: all vacancies, internships only, or regular jobs only.", "default": "all" }, "maxItems": { "title": "Max results", "minimum": 0, "type": "integer", "description": "Maximum number of results to return. Set to 0 for no limit.", "default": 0 }, "daysOld": { "title": "Max age (days)", "minimum": 0, "type": "integer", "description": "Only return vacancies with a deadline within this many days from now. Set to 0 for no filter.", "default": 0 }, "fetchDetails": { "title": "Fetch detail pages", "type": "boolean", "description": "Fetch full vacancy description, requirements, duties and proposal from detail pages. Recommended: true.", "default": true }, "skipReposts": { "title": "Skip reposts", "type": "boolean", "description": "Skip vacancies already seen in previous runs (cross-run deduplication with 90-day TTL).", "default": false }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Optional list of specific prakse.lv vacancy URLs to scrape directly (e.g. https://www.prakse.lv/vacancy/176361/...).", "default": [], "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 } } } } } } } } } } ```