TicketCity Scraper

A Python scraper for extracting event listings from TicketCity.com using the ScrapingAnt web scraping API.

Features

• Scrapes event listings from TicketCity.com across multiple categories
• Supports NBA, NFL, MLB, NHL teams and concerts
• Extracts comprehensive event details:
  • Event title (game matchup or artist name)
  • Date (month and day)
  • Day of week
  • Year
  • Time
  • Venue name and location
  • Hot Event indicator
  • Category
• Handles JavaScript "Show More" button to load all events
• Exports data to CSV and JSON formats
• Deduplicates events automatically
• Uses CSS selectors and URL patterns for reliable extraction

Prerequisites

• Python 3.8+
• ScrapingAnt API key (Get free API key)

Note: The ScrapingAnt free plan has a concurrency limit of 1 thread. For higher throughput, consider upgrading to a paid plan.

Installation

1. Clone this repository:

git clone https://github.com/kami4ka/ticketcity-scraper.git
cd ticketcity-scraper

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set your ScrapingAnt API key:

export SCRAPINGANT_API_KEY="your_api_key_here"

Usage

Basic Usage

Scrape events from default categories (Lakers and Bad Bunny):

python main.py

Command Line Options

python main.py [OPTIONS]

Options:
  --category TEXT          Scrape a specific category only
  --categories TEXT...     Scrape multiple specific categories
  --all-categories         Scrape all available categories
  --no-show-more           Don't click Show More button (get fewer events)
  -o, --output PATH        Output CSV file path (default: output/ticketcity_events.csv)
  --json                   Also export to JSON format
  -v, --verbose            Enable verbose output
  --api-key TEXT           ScrapingAnt API key (or set SCRAPINGANT_API_KEY env var)
  --list-categories        List available categories and exit

Examples

Scrape with verbose output:

python main.py --verbose

Scrape a specific category:

python main.py --category nba/los-angeles-lakers-tickets.html --verbose

Scrape multiple categories:

python main.py --categories nba/los-angeles-lakers-tickets.html nba/golden-state-warriors-tickets.html --verbose

Scrape all available categories:

python main.py --all-categories --verbose

Export to both CSV and JSON:

python main.py --json -o output/events.csv

List available categories:

python main.py --list-categories

Available Categories

NBA Teams

• nba/los-angeles-lakers-tickets.html - Los Angeles Lakers
• nba/golden-state-warriors-tickets.html - Golden State Warriors
• nba/boston-celtics-tickets.html - Boston Celtics
• nba/new-york-knicks-tickets.html - New York Knicks
• nba/chicago-bulls-tickets.html - Chicago Bulls
• nba/miami-heat-tickets.html - Miami Heat

NFL Teams

• nfl/dallas-cowboys-tickets.html - Dallas Cowboys
• nfl/new-england-patriots-tickets.html - New England Patriots
• nfl/green-bay-packers-tickets.html - Green Bay Packers

MLB Teams

• mlb/new-york-yankees-tickets.html - New York Yankees
• mlb/los-angeles-dodgers-tickets.html - Los Angeles Dodgers

NHL Teams

• nhl/new-york-rangers-tickets.html - New York Rangers
• nhl/boston-bruins-tickets.html - Boston Bruins

Concerts

• concerts/bad-bunny-tickets.html - Bad Bunny
• concerts/taylor-swift-tickets.html - Taylor Swift
• concerts/beyonce-tickets.html - Beyonce
• concerts/drake-tickets.html - Drake
• concerts/morgan-wallen-tickets.html - Morgan Wallen

Output Format

CSV Fields

Field	Description	Example
title	Event name/matchup	Atlanta Hawks at Los Angeles Lakers
date	Month and day	Jan 13
day_of_week	Day of the week	Tue
year	Event year	2026
time	Event time	7:30 PM
venue	Venue name	Crypto.com Arena
location	City, State/Country	Los Angeles, CA
is_hot	Hot event indicator	True/False
event_url	Event page URL	https://www.ticketcity.com/...
category	Category name	Los Angeles Lakers
scraped_at	Timestamp	2026-01-10T10:30:00Z

Sample Output

title,date,day_of_week,year,time,venue,location,is_hot,event_url,category,scraped_at
Atlanta Hawks at Los Angeles Lakers,Jan 13,Tue,2026,7:30 PM,Crypto.com Arena,Los Angeles, CA,False,https://www.ticketcity.com/los-angeles-tickets/...,Los Angeles Lakers,2026-01-10T10:30:00Z

Project Structure

TicketCityScraper/
├── config.py          # Configuration settings and categories
├── models.py          # Event and EventCollection data classes
├── utils.py           # Utility functions for parsing
├── scraper.py         # Main scraper class
├── main.py            # CLI entry point
├── requirements.txt   # Python dependencies
├── .gitignore         # Git ignore patterns
├── output/            # Output directory for scraped data
│   └── .gitkeep
└── README.md          # This file

How It Works

The scraper fetches event listing pages from TicketCity.com using ScrapingAnt's browser rendering capability with residential proxies.

Each event listing contains:

• Event title (game matchup or performer name)
• Date components (day, month, year)
• Time
• Venue and location
• Hot Event badge (optional)

The scraper:

1. Navigates to the category's event listing page
2. Uses JavaScript to click "Show More" button to reveal all events
3. Parses the HTML to extract event data using CSS selectors and URL patterns
4. Deduplicates events based on title, date, year, and venue
5. Exports to CSV/JSON format

License

MIT License

Disclaimer

This scraper is for educational purposes only. Please respect TicketCity.com's terms of service and rate limits when using this tool. Always ensure your scraping activities comply with applicable laws and website policies.