Automated Job Search: LinkedIn Jobs to Notion Board

A Python-based job scraping system that pulls LinkedIn listings into a structured Notion database. Repository: jobs-scrape-to-notion

Setup Steps

1. Clone the repository:

git clone https://github.com/namanvashistha/jobs-scrape-to-notion
cd jobs-scrape-to-notion

1. Install dependencies:

pip install -r requirements.txt

1. Configure Notion:

   • Create a Notion integration at notion.so/my-integrations
   • Create a new Notion database
   • Share your database with the integration
   • Copy the database ID from its URL

2. Set environment variables:
   

cp .env.example .env

Update .env with your credentials:

NOTION_API_KEY=your_integration_token
NOTION_DATABASE_ID=your_database_id

Key Features

Job Scraping

def fetch_jobs(search_terms, location, results_wanted=20):
    # Scrapes LinkedIn jobs based on multiple search terms
    # Returns a pandas DataFrame with job details

Notion Integration

• Creates structured database entries
• Handles rich text, URLs, dates, and company logos
• Prevents duplicate entries
• Manages API rate limits

Data Processing

• Sanitizes input data
• Formats salary ranges for Indian currency
• Handles company metadata
• Manages file attachments for logos

Running the Scraper

python main.py

Default configuration:

• Search terms: ["Software Engineer", "Backend", "SDE"]
• Location: India
• Results per term: 20
• Platform: LinkedIn

Customization

Modify main() in scraper.py:

search_terms = ["Your", "Preferred", "Terms"]
location = "Your Location"
results_wanted = 30  # Number of results per term

Error Handling

The system includes:

• Comprehensive logging
• Rate limit management
• Duplicate prevention
• Data validation

Visit the repository for source code and detailed documentation.