A complete web scraping tool that captures event data from Eventbrite Singapore.
Eventbrite is a popular platform hosting various types of events including concerts, workshops, meetups, and seminars.
It is designed to handle dynamic JavaScript-rendered content using Selenium and outputs the data in structured CSV and JSON formats.
The scraper was built using Python and Selenium, with a headless Chrome browser for dynamic rendering support. It includes pagination support, modular architecture, and options for easy future extensions.
.
├── scraper.py # Main script to orchestrate scraping flow
├── utils/
│ ├── helpers.py # Utility functions: event parsing and data export
│ └── constants.py # CSS selectors, keywords, config
├── data/
│ ├── eventbrite.csv # Extracted data in CSV format
│ └── eventbrite.json # Extracted data in JSON format
├── diagrams/
│ ├── event-category-distribution.png # Bar chart of event categories
│ └── event-prices-distribution.png # Histogram of event prices
└──requirements.txt # Python package dependencies
Before you begin, make sure the following are installed on your system:
- Python 3.8+
- Google Chrome (required for Selenium to launch a headless browser and render JavaScript content)
git clone https://github.com/gowthaman-01/eventbrite-scraper.git
cd eventbrite-scraperpython -m venv venv
source venv/bin/activate # On Windows: venv\\Scripts\\activate
pip install -r requirements.txtYou can specify how many pages to scrape with the --pages flag. If no arguments are provided, the scraper will default to 10 pages:
python scraper.py --pages 5- Launch a headless Chrome browser.
- Visit Eventbrite’s Singapore listings for pages 1 to 10.
- For each page, wait for full render and extract all event cards.
- Parse each card and save event data into:
data/eventbrite.csvdata/eventbrite.json
Each event in the output files contains the following fields:
| Field | Description |
|---|---|
| Title | Name of the event |
| URL | Direct link to the event page |
| Location | Physical location or city |
| Paid Status | 'paid' or 'free' |
| Category | Event category (e.g., music, arts, business) |
| Urgency | Status text like “Sales end soon” or “Almost full” |
| Date & Time | Human-readable event time string |
| Price | Ticket price range or minimum |
| Host | Organizer or venue |
The project was structured with clarity and modularity in mind. The scraper.py script serves as the entry point, orchestrating the page navigation, data collection, and export process. All CSS selectors, urgency keywords, and output paths were centralized in constants.py for easy maintenance. The logic for parsing each event card and exporting the results was encapsulated in helpers.py.
Eventbrite loads some of its card details (title and p tags) dynamically via JavaScript. To extract content reliably, the scraper uses:
driver.execute_script("return arguments[0].innerText;", element)This approach retrieves the visible text post-render, bypassing limitations of .text or .get_attribute().
The scraper uses formatted URLs with the ?page={n} query parameter, allowing it to iterate over multiple pages:
for page in range(1, 11):
url = EVENTBRITE_BASE_URL.format(page=page)To prevent overloading Eventbrite’s servers and avoid bot detection:
- Each page is fetched with a
WAIT_TIME = 3seconds delay - Headless browser is used to simulate human browsing
- No aggressive concurrency or request spoofing is employed
- Over 200 unique events captured
- Most common categories: music, arts, business, health
- Prices range from $0.00 (free) to $300+
- Several events are marked with urgency tags, indicating high demand
- Some events may have missing
urgencyorhostfields due to inconsistent HTML - Titles are used to deduplicate events; if Eventbrite reuses titles, some records may be skipped