📍 Google Maps Lead Scraper Pro

Extract Business Leads from Google Maps Automatically 🚀

A professional automation tool to scrape business data (name, phone, website, emails) from Google Maps with a beautiful web interface.

---

🎯 What This Does (Ek Sentence Mein)

Problem: Manual data collection = time-consuming, error-prone
Solution: This tool automatically extracts 100+ business leads from Google Maps in minutes

---

⚡ Use Cases

✅ Business Development - Find prospects automatically
✅ Sales Lead Generation - Build targeted contact lists
✅ Market Research - Analyze competitor presence
✅ Real Estate - Find property-related businesses
✅ Franchise Research - Compare business density by area

---

🚀 Quick Start (3 Steps)

Step 1: Install

pip install -r requirements.txt
playwright install chromium

Step 2: Run

python app.py

Step 3: Open Browser

http://localhost:5000

Then:

1. Enter business type (e.g., "Restaurant", "Plumber", "Cafe")
2. Enter city (e.g., "New York", "Mumbai", "London")
3. Click "Start Scraping"
4. Download CSV or JSON

That's it! ✅

---

🧪 Verify Installation

Run the test suite:

python test_setup.py

Output:

✅ All tests passed! Ready to run.

---

📊 What You Get

Field	Example
Business Name	Starbucks Coffee
Address	123 Main St, New York, NY 10001
Phone	(212) 555-0123
Website	https://starbucks.com
Emails	manager@starbucks.com

Sample Output (CSV)

name,address,phone,website,emails
Starbucks,"123 Main St, New York","(212) 555-0123","https://starbucks.com","manager@starbucks.com"
Blue Bottle Coffee,"456 Park Ave, New York","(212) 555-0456","https://bluebottlecoffee.com","contact@bluebottlecoffee.com"
Joe Coffee Company,"789 Broadway, New York","(212) 555-0789","https://joecoffee.com","N/A"

Sample Output (JSON)

[
  {
    "name": "Starbucks",
    "address": "123 Main St, New York",
    "phone": "(212) 555-0123",
    "website": "https://starbucks.com",
    "emails": "manager@starbucks.com"
  }
]

---

🎮 Usage Examples

Example 1: Find All Pizza Places in NYC

Keyword: Pizza
City: New York
Max Results: Leave empty (get all)
Timeout: 15 minutes
Skip Emails: OFF (get emails too)
Result: 150+ pizza restaurants with phone & email

Example 2: Quick Test (5 Restaurants)

Keyword: Restaurant
City: Los Angeles
Max Results: 5
Timeout: 5 minutes
Skip Emails: ON (faster)
Result: Quick list in ~3 minutes

Example 3: B2B Lead Generation

Keyword: Digital Marketing Agency
City: San Francisco
Max Results: 100
Timeout: 20 minutes
Skip Emails: OFF
Result: 100 agencies with contact info

---

⚙️ Features

Web Interface

✅ No coding needed - just click and fill
✅ Real-time progress tracking
✅ Beautiful dashboard with stats
✅ Mobile responsive

Smart Scraping

✅ Automatic retry on errors
✅ Smart rate limiting (won't get banned)
✅ Email validation (no false positives)
✅ Duplicate removal

Professional Output

✅ CSV format (for Excel/Sheets)
✅ JSON format (for APIs)
✅ Detailed logs for debugging
✅ Resume capability (don't lose progress)

---

📋 Settings Explained

Setting	What It Does
Keyword	Type of business (e.g., "Cafe", "Gym", "Lawyer")
City	Location to search (e.g., "New York", "Mumbai")
Max Results	Stop after N businesses (leave empty for all)
Timeout	Max time to run (5-30 minutes)
Skip Emails	Faster if you don't need emails
Headless Mode	Faster (no visible browser)

---

📈 Performance

Scenario	Results	Time
Small city search	30-50	3-5 min
Medium city	100-150	10-15 min
Large city (no emails)	200+	15-20 min
Large city (with emails)	100-150	20-30 min

---

🛠️ How It Works

1. Search → Opens Google Maps & searches your keyword
2. Scroll → Loads all available results (not just first page)
3. Extract → Gets name, phone, website, address
4. Email Mine → Visits websites & extracts emails (optional)
5. Deduplicate → Removes duplicates & validates data
6. Export → Saves as CSV & JSON

See detailed workflow: HOW_IT_WORKS.md

---

📁 Output Files

output/
├── businesses.csv      ← Open in Excel
└── businesses.json     ← Use in APIs

logs/
└── scraper_*.log       ← Debugging info

---

💻 Command Line (Advanced)

If you prefer terminal:

# Basic search
python maps_scraper.py --keyword "Restaurant" --city "New York"

# With limits
python maps_scraper.py --keyword "Cafe" --city "London" --max-results 50

# Fast mode (no emails)
python maps_scraper.py --keyword "Gym" --city "Paris" --no-emails --headless

# Resume from checkpoint
python maps_scraper.py --keyword "Plumber" --city "Mumbai" --resume --timeout 900

---

⚡ Tips for Best Results

1. Start with 10 results → Test before big scrape
2. Use headless mode → 2-3x faster (default: ON)
3. Skip emails first → Get all businesses, extract emails later
4. Specific keywords work better → "Italian Restaurant" > "Restaurant"
5. Run at off-hours → Less chance of getting blocked

---

⚠️ Important

• ✅ Legal for personal/business use
• ✅ Respects rate limits (built-in delays)
• ⚠️ Don't scrape too aggressively (may get IP blocked)
• 💡 Consider proxies for large-scale scraping

---

🐛 Troubleshooting

Problem	Solution
No results found	Try simpler keyword or different city
Very slow	Enable "Skip Emails", reduce timeout
Getting blocked	Wait 2-3 hours, try different city
Crashes midway	Use "Resume" feature to continue

See HOW_IT_WORKS.md for complete guide.

---

📦 Requirements

• Python 3.8+
• Flask 3.0+
• Playwright (Chromium browser)

---

🚀 Installation (Detailed)

1. Clone Repository

git clone https://github.com/parnika-sa/maps.git
cd maps

2. Create Virtual Environment

python -m venv venv
venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt
playwright install chromium

4. Verify Setup

python test_setup.py

5. Run

python app.py

6. Open Browser

http://localhost:5000

Done! 🎉

---

🤝 Contributing

Want to improve this? Check CONTRIBUTING.md for guidelines.

---

📝 License

MIT License - See LICENSE for details

Free to use for personal & commercial projects

---

📞 Support

Questions? Check HOW_IT_WORKS.md for detailed documentation.

---

⭐ If This Helps, Star It!

Your support motivates me to improve this tool 🙏

---

Made with ❤️ by Ankit Maurya