# Scraping Job Boards Using Firecrawl Actions and OpenAI

![Scraping Job Boards Using Firecrawl Actions and OpenAI image](https://www.firecrawl.dev/images/blog/firecrawl-openai-job-scraping.jpg)

Scraping job boards to extract structured data can be a complex task, especially when dealing with dynamic websites and unstructured content. In this guide, we’ll walk through how to use [Firecrawl Actions](https://firecrawl.dev/) and OpenAI models to efficiently scrape job listings and extract valuable information.

### Why Use Firecrawl and OpenAI?

- **Firecrawl** simplifies web scraping by handling dynamic content and providing actions like clicking and scrolling.
- **OpenAI’s `o1` and `4o` models** excel at understanding and extracting structured data from unstructured text. `o1` is best for more complex reasoning tasks while `4o` is best for speed and cost.

### Prerequisites

- Python 3.7 or higher
- API keys for both [Firecrawl](https://firecrawl.dev/) and [OpenAI](https://openai.com/)
- Install required libraries:

```bash
pip install requests python-dotenv openai

```

### Step 1: Set Up Your Environment

Create a `.env` file in your project directory and add your API keys:

```
FIRECRAWL_API_KEY=your_firecrawl_api_key
OPENAI_API_KEY=your_openai_api_key

```

### Step 2: Initialize API Clients

```python
import os
import requests
import json
from dotenv import load_dotenv
import openai