Google Maps Scraper & Viewer

Overview

This project allows you to scrape business details from Google Maps (including Open Hours and Popular Times) and view the results in a nice web interface.

Prerequisites

• Python 3.8+
• PHP 7.4+ (for the viewer)
• Google Chrome (for Playwright)

Quick Start

macOS

# Make script executable and run
chmod +x run.sh
./run.sh

This will:

• Set up a Python virtual environment
• Install all dependencies
• Start the PHP web server
• Open your browser to the interface
• Provide instructions for running the scraper

Windows/Linux

# Create virtual environment
python -m venv .venv

# Activate (Windows)
.venv\Scripts\activate
# Or (macOS/Linux)
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt
playwright install chromium

# Start PHP server
php -S localhost:8000

# Run scraper (in another terminal)
python scraper.py "restaurants near arugambay"

Usage

Running the Scraper

# Activate virtual environment first
source .venv/bin/activate  # macOS/Linux
# or
.venv\Scripts\activate     # Windows

# Run with your query
python scraper.py "your search query"

Results are saved in scrapings/query_name/timestamp.json.

Viewing Results

The web interface provides:

• Browse all scraped places
• Search and filter results
• Follow/unfollow places
• View detailed information

Features

• Deep Scraping: Extracts Name, Address, Phone, Website, Ratings, Reviews, Weekly Open Hours, and Popular Times
• Infinite Scroll: Automatically scrolls to find all results
• Parallel Processing: Uses async Playwright for speed
• Clean Interface: Bootstrap-based viewer with search functionality
• Follow System: Mark places you're interested in

Project Structure

├── scraper.py          # Main scraping script
├── index.php           # Web interface
├── run.sh             # macOS setup script
├── requirements.txt    # Python dependencies
├── .gitignore         # Git ignore rules
└── scrapings/         # Scraped data (auto-generated)

Deployment

To host this online:

1. Upload to your web server
2. Ensure scrapings/ folder is writable
3. Point your domain to the folder
4. Access via browser

License

MIT License - feel free to use and modify.