🎾 GTA Tennis Clubs Waitlist Database

A comprehensive database and web dashboard for tracking 306 Greater Toronto Area tennis clubs with automated data collection and elegant Wimbledon-inspired UI.

📋 Project Overview

This project centralizes tennis club information across the GTA, tracking 9 key data fields:

1. Club Name
2. Location
3. Email
4. Club Type (Private/Community/Public)
5. Membership Status (Open/Waitlist/Full)
6. Current Waitlist Length
7. Number of Courts
8. Court Surface (Hard/Clay/Grass/Indoor)
9. Operating Season (Year-round/Seasonal)

Problem Statement

Tennis club information is scattered across hundreds of individual websites with inconsistent formats. This makes it difficult to:

• Find clubs with open memberships
• Compare waitlist lengths
• Identify clubs by specific criteria (court type, location, season)

Solution

A centralized database with:

• Automated web scraping for baseline data
• AI-powered extraction using Claude for complex parsing
• Email monitoring system for membership status updates
• Professional web dashboard for data visualization and export

🎨 Features

Dashboard (Wimbledon Theme)

• Live Statistics: Real-time progress tracking (306 total, 80 processed, 226 remaining)
• Four Main Views:
  • Overview with quick actions
  • Processed clubs table with search
  • Remaining clubs list
  • Data quality report with completion metrics
• Batch Scraping: Click-to-copy URLs for AI-assisted extraction
• CSV Export: One-click data download
• Responsive Design: Works on desktop and mobile

Data Collection Methods

1. Tennis Ontario Directory: Official structured data (primary source)
2. Individual Club Websites: AI-powered extraction via Claude
3. Email Campaigns: Manual outreach for sensitive data (waitlist, membership)

Technologies

• Backend: Flask (Python)
• Data Processing: Pandas, OpenPyXL
• Frontend: Vanilla JavaScript, HTML5, CSS3
• AI Assistant: Anthropic Claude (via API for scraping)
• Data Storage: Excel (.xlsx) with dual-sheet structure

🚀 Quick Start

Prerequisites

python 3.8+
pip (Python package manager)

Installation

1. Clone the repository

git clone https://github.com/YFC-ophey/GTA-tennis-clubs-waitlist.git
cd GTA-tennis-clubs-waitlist

2. Install dependencies

pip install -r requirements.txt

3. Verify data file Ensure data/GTA_Tennis_clubs_data_.xlsx exists with two sheets:

• data: All 306 clubs (Club Name, Website URL)
• run: Processed clubs with complete data

4. Run the application

python app.py

5. Access dashboard Open your browser to: COMING SOON

📊 Data Structure

Excel File Structure

Sheet: data

Club Name	Website URL
10XTO	https://www.10xto.com/tennis
A Love of Tennis	http://www.aloveoftennis.org/
...	...

Sheet: run

Club Name	Location	Email	Club Type	Membership Status	Waitlist Length	Number of Courts	Court Surface	Operating Season	Website URL	Date Scraped	URL Status

Success Metrics (Current)

• Total Clubs: 306
• Processed: 80 (26.1%)
• Data Completeness:
  • Location: 67.5%
  • Email: 33.8%
  • Club Type: 45.0%
  • Court Surface: 28.7%
  • Membership Status: 33.8%

🔧 Usage

Scraping Workflow

1. Click "Get Next 10 Clubs" in the dashboard
2. Copy a club URL using the copy button
3. Ask Claude to scrape it:

   Please scrape this club: http://www.clubname.ca/
   

4. Claude extracts all 9 fields automatically
5. Data is added to your spreadsheet
6. Refresh dashboard to see updates

Manual Data Entry

For clubs requiring phone calls or email outreach:

1. Contact the club directly
2. Collect the 9 required fields
3. Manually update the Excel file
4. Refresh dashboard

Export Data

Click "Export CSV" in the dashboard to download current data in CSV format.

📁 Project Structure

GTA-tennis-clubs-waitlist/
├── app.py                          # Flask application
├── templates/
│   └── dashboard.html              # Wimbledon-themed dashboard
├── data/
│   └── GTA_Tennis_clubs_data_.xlsx # Main database
├── docs/
│   ├── SETUP.md                    # Detailed setup instructions
│   ├── API.md                      # API documentation
│   └── SCRAPING_GUIDE.md          # Web scraping methodology
├── requirements.txt                # Python dependencies
├── .gitignore                      # Git ignore file
└── README.md                       # This file

🎯 Roadmap

Phase 1: Foundation (✅ Complete)

• Database schema design
• Excel file structure
• Basic web dashboard
• Manual scraping workflow

Phase 2: Automation (In Progress)

• Wimbledon-themed UI redesign
• Batch scraping system
• Claude API integration for automated scraping
• Gmail monitoring for email responses
• Automated Tennis Ontario directory scraping

Phase 3: Enhancement (Planned)

• Database migration to PostgreSQL
• User authentication system
• Public search interface
• Email campaign management
• Automated reminder system for stale data
• Mobile app (React Native)

🤝 Contributing

Contributions welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Tennis Ontario for official club directory
• Anthropic Claude for AI-powered data extraction
• Wimbledon for design inspiration
• All GTA tennis clubs for their public information

📧 Contact

Ophelia Chen

• GitHub: @YFC-ophey
• Project Link: https://github.com/YFC-ophey/GTA-tennis-clubs-waitlist

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