# Pracuj Jobs Scraper (`powerai/pracuj-jobs-scraper`) Actor

Scrape job listings from Pracuj.pl by providing a search URL, with automatic pagination and comprehensive job information extraction.

- **URL**: https://apify.com/powerai/pracuj-jobs-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 18 total users, 2 monthly users, 100.0% runs succeeded, 2 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## 💼 Pracuj Jobs Scraper

This actor allows you to scrape job listings from Pracuj.pl by providing a search URL. It automatically handles pagination and extracts comprehensive job information including salaries, company details, locations, and job requirements.

### Features

- **URL-based Scraping:** Extract job listings by providing a complete Pracuj.pl search URL
- **Automatic Pagination:** Automatically navigates through pages and loads more job listings until reaching the end or max items limit
- **Comprehensive Job Data:** Extract detailed information about each job listing including:
  - Job title and description
  - Salary information
  - Company details with logos
  - Job location
  - Additional information (seniority level, employment type, contract type, etc.)
  - Publication date
  - Quick apply availability
- **Company Information:** Includes company name, profile link, and logo
- **Job Details:** Captures job descriptions, requirements, and additional tags

### Input Parameters

| Field      | Type    | Required | Description                                    |
|------------|---------|----------|------------------------------------------------|
| `searchUrl`| string  | Yes      | Complete Pracuj.pl search URL to scrape       |
| `maxItems` | integer | No       | Maximum number of job listings to fetch               |

### Output

The output is a main list of job listing objects, each containing:

- `searchUrl`: The original search URL used
- `offerId`: Unique identifier for the job offer
- `offerUrl`: URL to the full job listing page
- `offerTitle`: Title of the job position
- `salary`: Salary range or information
- `company`: Company information object containing:
  - `name`: Company name
  - `link`: URL to company profile
  - `logo`: URL to company logo image
- `location`: Job location
- `additionalInfo`: Array of additional information tags (seniority, employment type, contract type, etc.)
- `superOfferLabel`: Label indicating if it's a "super offer"
- `description`: Job description and requirements
- `dateAdded`: Publication date of the job listing
- `isQuickApply`: Whether quick apply is available
- `scrapedAt`: Timestamp of when the listing was scraped

Example output:

```json
[
  {
    "searchUrl": "https://www.pracuj.pl/praca/ai;kw",
    "offerId": "1004481750",
    "offerUrl": "https://www.pracuj.pl/praca/machine-learning-engineer-warszawa-aleja-niepodleglosci-18,oferta,1004481750?s=50cd1cf4&searchId=MTc2MzQ0NjkxMDc0Mi44NTI4&ref=top_boosterAI_L0_1_1_1",
    "offerTitle": "Machine Learning Engineer",
    "salary": "26 880–42 000 zł netto (+ VAT) / mies.",
    "company": {
      "name": "ACAISOFT POLAND Sp. z o.o.",
      "link": "https://pracodawcy.pracuj.pl/company/20303751?pid=1004481750",
      "logo": "https://logos.gpcdn.pl/loga-firm/20303751/ee4d0000-5df0-0015-4848-08da283012e1_280x280.png"
    },
    "location": "Warszawa, Mokotów",
    "additionalInfo": [
      "Starszy specjalista (Senior)",
      "Pełny etat",
      "Kontrakt B2B",
      "Praca od zaraz",
      "Praca zdalna"
    ],
    "superOfferLabel": "Superoferta",
    "description": "Your responsibilities, Design and implement RL environments that support large-scale agent evaluation and reinforcement learning experiments., Build task generation pipelines, dynamic datasets, and scripted environments with controlled complexity...",
    "dateAdded": "17 listopada 2025",
    "isQuickApply": true,
    "scrapedAt": "2025-11-18T06:22:42.217Z"
  },
  ...
]
```

### Use Cases

- Job market research and analysis
- Salary benchmarking and compensation analysis
- Company hiring trend tracking
- Job search automation
- Recruitment market intelligence
- Skills demand analysis

### Notes

- Results are automatically paginated until reaching the end or max items limit
- All job listings include comprehensive company and position details
- Publication dates are captured for tracking new listings
- Quick apply availability is indicated for each listing

# Actor input Schema

## `searchUrl` (type: `string`):

The complete Pracuj.pl search URL to scrape

## `maxItems` (type: `integer`):

Maximum number of job listings to fetch

## `proxyConfiguration` (type: `object`):

Proxy settings for the actor

## Actor input object example

```json
{
  "searchUrl": "https://www.pracuj.pl/praca/ai;kw",
  "maxItems": 50,
  "proxyConfiguration": {
    "useApifyProxy": false,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("powerai/pracuj-jobs-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("powerai/pracuj-jobs-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 powerai/pracuj-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=powerai/pracuj-jobs-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/rVeYbt0WgElVLRgmg/builds/U7Up21a6kOMpQzmHC/openapi.json