LinkedIn Post Generator 🚀

Automatically crawl three tech blogs and generate professional LinkedIn posts using AI.

Features

✨ Three Fixed Blog Sources - Crawls Fullstack Labs, React Native, and AWS DevOps blogs
🤖 AI-Powered Posts - Generate engaging LinkedIn posts using OpenAI GPT-3.5
📡 RSS Feed Support - Stable extraction using RSS feeds where available
🔒 Secure - API keys stored in .env file (not committed to git)

Blog Sources

The tool automatically crawls these three blogs:

1. Fullstack Labs - https://www.fullstack.com/labs/resources/blog
2. React Native - https://reactnative.dev/blog (via RSS feed)
3. AWS DevOps - https://aws.amazon.com/blogs/devops/

Quick Start

1. Setup

# Clone the repository
git clone https://github.com/yourusername/linkedin-post-generator.git
cd linkedin-post-generator

# Create virtual environment (optional but recommended)
python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2. Configure

# Copy environment template
cp .env.example .env

# Edit .env and add your OpenAI API key
nano .env  # or use your preferred editor

Add your API key to .env:

OPENAI_API_KEY=sk-proj-your-actual-api-key-here

3. Run

python3 main.py

That's it! The tool will crawl all three blogs and generate LinkedIn posts automatically.

Project Structure

linkedin-post-generator/
├── crawlers/
│   ├── __init__.py
│   ├── fullstack_crawler.py    # Fullstack Labs crawler
│   ├── expo_crawler.py          # React Native RSS crawler
│   └── aws_crawler.py           # AWS DevOps crawler
├── main.py                      # Main application entry point
├── config.py                    # Configuration management
├── post_generator.py            # AI post generator
├── output/                      # Generated posts (created automatically)
│   ├── linkedin_posts.csv
│   └── linkedin_posts.json
├── .env                         # Environment variables (not in git)
├── .env.example                 # Environment template
├── .gitignore                   # Git ignore rules
├── requirements.txt             # Python dependencies
└── README.md                    # This file

Configuration

Edit .env file:

# Required
OPENAI_API_KEY=sk-your-key-here

# Optional
MAX_ARTICLES_PER_URL=30        # Articles per blog (default: 30)
EXTRACT_CONTENT=false          # Extract full content (slower, default: false)
OUTPUT_FILE=output/linkedin_posts.csv  # Output filename

Configuration Options

• OPENAI_API_KEY (required): Your OpenAI API key
• MAX_ARTICLES_PER_URL (optional): Maximum articles to process per blog (default: 30)
• EXTRACT_CONTENT (optional): Set to true to extract full article content for better posts (slower)
• OUTPUT_FILE (optional): Path and filename for output CSV (default: output/linkedin_posts.csv)

Output

The tool generates two files in the output/ directory:

• linkedin_posts.csv - Spreadsheet format with all posts
• linkedin_posts.json - JSON format for programmatic use

Each post includes:

• Source (Fullstack, Expo, or AWS DevOps)
• Article URL
• Article title
• Generated LinkedIn post
• Timestamp

Example Output

======================================================================
✅ COMPLETED! Generated 45 LinkedIn posts
======================================================================

Breakdown by source:
  • Fullstack: 12 posts
  • Expo: 20 posts
  • AWS DevOps: 13 posts

Files created:
  📄 output/linkedin_posts.csv
  📄 output/linkedin_posts.json

API Costs

Using OpenAI GPT-3.5-turbo:

• ~$0.001-0.002 per post
• 30 posts ≈ $0.03-0.06
• 100 posts ≈ $0.10-0.20

Very affordable! 💰

Requirements

• Python 3.10+
• OpenAI API key (Get one here)
• Internet connection

Python Dependencies

All dependencies are listed in requirements.txt:

• openai>=1.0.0 - OpenAI API client
• requests>=2.31.0 - HTTP requests
• beautifulsoup4>=4.12.0 - HTML parsing
• lxml>=4.9.0 - XML/HTML parser

How It Works

1. Crawl Blogs - Each crawler extracts articles from its specific blog

   • Fullstack: Parses HTML structure
   • React Native: Uses RSS feed (most reliable)
   • AWS DevOps: Parses HTML structure

2. Generate Posts - For each article:

   • Sends article title (and content if enabled) to OpenAI
   • GPT-3.5 generates a professional LinkedIn post
   • Post includes hook, key takeaways, and hashtags

3. Save Results - Exports all posts to CSV and JSON formats

Troubleshooting

No articles found from a blog?

• Check your internet connection
• The blog's HTML structure may have changed
• Check the crawler file for that specific blog

API errors?

• Verify your OpenAI API key in .env
• Check you have credits in your OpenAI account
• Ensure .env file is in the project root directory

Import errors?

pip install -r requirements.txt

Permission denied error?

• Make sure OUTPUT_FILE in .env uses a relative path like output/linkedin_posts.csv
• Don't use absolute paths like /output/linkedin_posts.csv

Rate limiting?

• The script includes 1-second delays between API calls
• If you hit rate limits, reduce MAX_ARTICLES_PER_URL in .env

Customization

Adding a New Blog

1. Create a new crawler in crawlers/ (e.g., your_blog_crawler.py)
2. Implement the crawl() and extract_content() methods
3. Add the import to crawlers/__init__.py
4. Update main.py to use the new crawler

Changing the Prompt

Edit post_generator.py to customize the AI prompt for different post styles.

Contributing

Pull requests welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

MIT License - feel free to use for personal or commercial projects!

Support

Having issues? Open an issue , Inspired by linkedin-post-automator