Eventbrite Scraper — Events by Location & Topic

What does Eventbrite Scraper — Events by Location & Topic do

Eventbrite Scraper — Events by Location & Topic collects publicly available Eventbrite event listings. It can discover events through Eventbrite search results using a location, topic, or both, and it can collect details from a specific public Eventbrite event URL.

For each event, the actor saves the information displayed by Eventbrite when available. Output can include the event name, Eventbrite URL, date, time, location, organizer, price, image URL, and description.

Use location-based search to collect events in a city, region, or country. Add a topic to narrow results to a subject such as technology, music, business, fitness, or food and drink. Use a direct event URL when you need information about a known event rather than a list of search results.

The actor processes public Eventbrite pages only. Available event details can differ between listings. For example, online events may not have a physical venue, free events may not display a ticket price range, and some organizers may provide limited descriptions.

Collected records are saved to the Apify dataset for the run. Dataset data can be viewed in the Apify Console, exported in supported formats, or accessed through the Apify API.

Input

Configure the actor with the following fields:

Field	Description
location	Location for the Eventbrite event search. Enter a city, region, country, or another location recognized by Eventbrite.
topic	Topic or keyword used to narrow search results. Examples include technology, music, business, and food and drink.
event_url	Full URL of a public Eventbrite event page to scrape directly.
max_events	Maximum number of event records to collect and save.

Provide location, topic, or both to search Eventbrite listings. Use event_url for a specific event page. The actor may return fewer records than max_events if there are fewer matching public events or if event information is unavailable.

Example input for a location and topic search:

{
  "location": "Austin, TX",
  "topic": "technology",
  "max_events": 25
}

Example input for a known event:

{
  "event_url": "https://www.eventbrite.com/e/austin-tech-networking-meetup-tickets-123456789012",
  "max_events": 1
}

Output example

Each dataset item represents one Eventbrite event. Fields can be empty when the corresponding information is not displayed on the source page.

{
  "event_name": "Austin Tech Networking Meetup",
  "event_url": "https://www.eventbrite.com/e/austin-tech-networking-meetup-tickets-123456789012",
  "event_date": "Thursday, June 20",
  "event_time": "6:00 PM - 8:00 PM CDT",
  "location": "Capital Factory, 701 Brazos St, Austin, TX 78701",
  "organizer": "Austin Technology Community",
  "price": "Free",
  "image_url": "https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F123456789%2Fexample.jpg",
  "description": "An in-person networking event for technology professionals, founders, and developers in Austin."
}

For online events, location may contain an online-event label rather than a street address. The price value may be Free, a single ticket price, or a price range.

Use cases

• Build event calendars for a city, region, or event topic.
• Collect public listings for conferences, workshops, meetups, and networking events.
• Research local event activity for business, technology, music, education, food, fitness, and other topics.
• Monitor event dates and URLs for editorial calendars, newsletters, or internal planning.
• Identify public organizers and recurring events in a selected location.
• Export event records to a spreadsheet, database, or API-based workflow.
• Retrieve structured details from a specific public Eventbrite event page.

Pricing

This actor uses pay-per-event pricing. You are charged for the event records collected by the actor.

You also pay for your own Apify platform compute usage while the actor runs. Compute charges depend on the resources and runtime required for the run.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.